repo stringclasses 454
values | file_path stringlengths 5 201 | extension stringclasses 1
value | content stringlengths 8 509k | num_lines int64 3 16.9k | size_bytes int64 8 511k |
|---|---|---|---|---|---|
numpy | numpy/core/__init__.py | .py | """
The `numpy.core` submodule exists solely for backward compatibility
purposes. The original `core` was renamed to `_core` and made private.
`numpy.core` will be removed in the future.
"""
from numpy import _core
from ._utils import _raise_warning
# We used to use `np.core._ufunc_reconstruct` to unpickle.
# This i... | 34 | 1,290 |
numpy | numpy/core/overrides.py | .py | def __getattr__(attr_name):
from numpy._core import overrides
from ._utils import _raise_warning
ret = getattr(overrides, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.overrides' has no attribute {attr_name}")
_raise_warning(attr_name, "overrides")
... | 11 | 335 |
numpy | numpy/core/_internal.py | .py | from numpy._core import _internal
# Build a new array from the information in a pickle.
# Note that the name numpy.core._internal._reconstruct is embedded in
# pickles of ndarrays made with NumPy before release 1.0
# so don't remove the name here, or you'll
# break backward compatibility.
def _reconstruct(subtype, sh... | 28 | 949 |
numpy | numpy/core/_multiarray_umath.py | .py | from numpy import ufunc
from numpy._core import _multiarray_umath
for item in _multiarray_umath.__dir__():
# ufuncs appear in pickles with a path in numpy.core._multiarray_umath
# and so must import from this namespace without warning or error
attr = getattr(_multiarray_umath, item)
if isinstance(attr,... | 58 | 2,098 |
numpy | numpy/core/umath.py | .py | def __getattr__(attr_name):
from numpy._core import umath
from ._utils import _raise_warning
ret = getattr(umath, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.umath' has no attribute {attr_name}")
_raise_warning(attr_name, "umath")
return ret
| 11 | 319 |
numpy | numpy/core/shape_base.py | .py | def __getattr__(attr_name):
from numpy._core import shape_base
from ._utils import _raise_warning
ret = getattr(shape_base, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.shape_base' has no attribute {attr_name}")
_raise_warning(attr_name, "shape_bas... | 11 | 339 |
numpy | numpy/core/arrayprint.py | .py | def __getattr__(attr_name):
from numpy._core import arrayprint
from ._utils import _raise_warning
ret = getattr(arrayprint, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.arrayprint' has no attribute {attr_name}")
_raise_warning(attr_name, "arrayprin... | 11 | 339 |
numpy | numpy/core/numerictypes.py | .py | def __getattr__(attr_name):
from numpy._core import numerictypes
from ._utils import _raise_warning
ret = getattr(numerictypes, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.numerictypes' has no attribute {attr_name}")
_raise_warning(attr_name, "num... | 11 | 347 |
numpy | numpy/core/_dtype.py | .py | def __getattr__(attr_name):
from numpy._core import _dtype
from ._utils import _raise_warning
ret = getattr(_dtype, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core._dtype' has no attribute {attr_name}")
_raise_warning(attr_name, "_dtype")
return r... | 11 | 323 |
numpy | numpy/core/fromnumeric.py | .py | def __getattr__(attr_name):
from numpy._core import fromnumeric
from ._utils import _raise_warning
ret = getattr(fromnumeric, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core.fromnumeric' has no attribute {attr_name}")
_raise_warning(attr_name, "fromnu... | 11 | 343 |
numpy | numpy/core/_dtype_ctypes.py | .py | def __getattr__(attr_name):
from numpy._core import _dtype_ctypes
from ._utils import _raise_warning
ret = getattr(_dtype_ctypes, attr_name, None)
if ret is None:
raise AttributeError(
f"module 'numpy.core._dtype_ctypes' has no attribute {attr_name}")
_raise_warning(attr_name, "... | 11 | 351 |
numpy | numpy/core/multiarray.py | .py | from numpy._core import multiarray
# these must import without warning or error from numpy.core.multiarray to
# support old pickle files
for item in ["_reconstruct", "scalar"]:
globals()[item] = getattr(multiarray, item)
# Pybind11 (in versions <= 2.11.1) imports _ARRAY_API from the multiarray
# submodule as a pa... | 26 | 793 |
numpy | numpy/tests/test__all__.py | .py |
import collections
import numpy as np
def test_no_duplicates_in_np__all__():
# Regression test for gh-10198.
dups = {k: v for k, v in collections.Counter(np.__all__).items() if v > 1}
assert len(dups) == 0
| 11 | 222 |
numpy | numpy/tests/test_matlib.py | .py | import numpy as np
import numpy.matlib
from numpy.testing import assert_, assert_array_equal
def test_empty():
x = numpy.matlib.empty((2,))
assert_(isinstance(x, np.matrix))
assert_(x.shape, (1, 2))
def test_ones():
assert_array_equal(numpy.matlib.ones((2, 3)),
np.matrix([[ 1.,... | 60 | 1,854 |
numpy | numpy/tests/test_configtool.py | .py | import importlib.metadata
import os
import pathlib
import subprocess
import pytest
import numpy as np
import numpy._core.include
import numpy._core.lib.pkgconfig
from numpy.testing import HAS_SUBPROCESSES, IS_EDITABLE, IS_INSTALLED, NUMPY_ROOT
INCLUDE_DIR = NUMPY_ROOT / '_core' / 'include'
PKG_CONFIG_DIR = NUMPY_ROO... | 52 | 1,828 |
numpy | numpy/tests/test_reloading.py | .py | import pickle
import sys
import textwrap
from importlib import reload
import pytest
import numpy.exceptions as ex
from numpy.testing import HAS_SUBPROCESSES, assert_, assert_equal, assert_raises
from numpy.testing._private.utils import run_subprocess
@pytest.mark.thread_unsafe(reason="reloads global module")
def te... | 70 | 2,587 |
numpy | numpy/tests/test_numpy_config.py | .py | """
Check the numpy config is valid.
"""
from unittest.mock import patch
import pytest
import numpy as np
pytestmark = pytest.mark.skipif(
not hasattr(np.__config__, "_built_with_meson"),
reason="Requires Meson builds",
)
class TestNumPyConfigs:
REQUIRED_CONFIG_KEYS = [
"Compilers",
"Ma... | 48 | 1,317 |
numpy | numpy/tests/test_scripts.py | .py | """ Test scripts
Test that we can run executable scripts that have been installed with numpy.
"""
import os
import subprocess
import sys
from os.path import dirname
import pytest
import numpy as np
from numpy.testing import HAS_SUBPROCESSES, assert_equal
def find_f2py_commands():
if sys.platform == 'win32':
... | 46 | 1,507 |
numpy | numpy/tests/test_lazyloading.py | .py | import sys
import textwrap
import pytest
from numpy.testing import HAS_SUBPROCESSES
from numpy.testing._private.utils import run_subprocess
@pytest.mark.skipif(not HAS_SUBPROCESSES, reason="platform cannot start subprocesses")
def test_lazy_load():
# gh-22045. lazyload doesn't import submodule names into the na... | 36 | 1,163 |
numpy | numpy/tests/test_ctypeslib.py | .py | import sys
import sysconfig
import weakref
from pathlib import Path
import pytest
import numpy as np
from numpy.ctypeslib import as_array, load_library, ndpointer
from numpy.testing import assert_, assert_array_equal, assert_equal, assert_raises
try:
import ctypes
except ImportError:
ctypes = None
else:
... | 407 | 13,544 |
numpy | numpy/tests/test_numpy_version.py | .py | """
Check the numpy version is valid.
Note that a development version is marked by the presence of 'dev0' or '+'
in the version string, all else is treated as a release. The version string
itself is set from the output of ``git describe`` which relies on tags.
Examples
--------
Valid Development: 1.22.0.dev0 1.22.0.... | 55 | 1,744 |
numpy | numpy/tests/test_warnings.py | .py | """
Tests which scan for certain occurrences in the code, they may not find
all of these occurrences but should catch almost all.
"""
import ast
import tokenize
from pathlib import Path
import pytest
import numpy
class ParseCall(ast.NodeVisitor):
def __init__(self):
self.ls = []
def visit_Attribute... | 82 | 2,546 |
numpy | numpy/tests/test_public_api.py | .py | import functools
import importlib
import inspect
import pkgutil
import sys
import sysconfig
import types
import warnings
import pytest
import numpy
import numpy as np
from numpy.testing import HAS_SUBPROCESSES
from numpy.testing._private.utils import run_subprocess
try:
import ctypes
except ImportError:
ctyp... | 723 | 25,046 |
numpy | numpy/doc/ufuncs.py | .py | """
===================
Universal Functions
===================
Ufuncs are, generally speaking, mathematical functions or operations that are
applied element-by-element to the contents of an array. That is, the result
in each output array element only depends on the value in the corresponding
input array (or arrays) a... | 139 | 5,424 |
numpy | numpy/_pyinstaller/hook-numpy.py | .py | """This hook should collect all binary files and any hidden modules that numpy
needs.
Our (some-what inadequate) docs for writing PyInstaller hooks are kept here:
https://pyinstaller.readthedocs.io/en/stable/hooks.html
"""
from PyInstaller.compat import is_pure_conda
from PyInstaller.utils.hooks import collect_dynami... | 36 | 1,339 |
numpy | numpy/_pyinstaller/tests/pyinstaller-smoke.py | .py | """A crude *bit of everything* smoke test to verify PyInstaller compatibility.
PyInstaller typically goes wrong by forgetting to package modules, extension
modules or shared libraries. This script should aim to touch as many of those
as possible in an attempt to trip a ModuleNotFoundError or a DLL load failure
due to ... | 33 | 1,143 |
numpy | numpy/_pyinstaller/tests/test_pyinstaller.py | .py | import subprocess
from pathlib import Path
import pytest
# PyInstaller has been very unproactive about replacing 'imp' with 'importlib'.
@pytest.mark.filterwarnings('ignore::DeprecationWarning')
# It also leaks io.BytesIO()s.
@pytest.mark.filterwarnings('ignore::ResourceWarning')
@pytest.mark.parametrize("mode", ["-... | 36 | 1,135 |
numpy | numpy/fft/_helper.py | .py | """
Discrete Fourier Transforms - _helper.py
"""
from numpy._core import arange, asarray, empty, integer, roll
from numpy._core.overrides import array_function_dispatch, set_module
# Created by Pearu Peterson, September 2002
__all__ = ['fftshift', 'ifftshift', 'fftfreq', 'rfftfreq']
integer_types = (int, integer)
... | 236 | 6,801 |
numpy | numpy/fft/__init__.py | .py | """
Discrete Fourier Transform
==========================
.. currentmodule:: numpy.fft
The SciPy module `scipy.fft` is a more comprehensive superset
of `numpy.fft`, which includes only a basic set of routines.
Standard FFTs
-------------
.. autosummary::
:toctree: generated/
fft Discrete Fourier transf... | 214 | 8,156 |
numpy | numpy/fft/_pocketfft.py | .py | """
Discrete Fourier Transforms
Routines in this module:
fft(a, n=None, axis=-1, norm="backward")
ifft(a, n=None, axis=-1, norm="backward")
rfft(a, n=None, axis=-1, norm="backward")
irfft(a, n=None, axis=-1, norm="backward")
hfft(a, n=None, axis=-1, norm="backward")
ihfft(a, n=None, axis=-1, norm="backward")
fftn(a, ... | 1,694 | 62,612 |
numpy | numpy/fft/tests/test_helper.py | .py | """Test functions for fftpack.helper module
Copied from fftpack.helper by Pearu Peterson, October 2005
"""
import numpy as np
from numpy import fft, pi
from numpy.testing import assert_array_almost_equal
class TestFFTShift:
def test_definition(self):
x = [0, 1, 2, 3, 4, -4, -3, -2, -1]
y = [-4,... | 168 | 6,154 |
numpy | numpy/fft/tests/test_pocketfft.py | .py | import queue
import threading
import pytest
import numpy as np
from numpy.random import random
from numpy.testing import IS_WASM, assert_allclose, assert_array_equal, assert_raises
def fft1(x):
L = len(x)
phase = -2j * np.pi * (np.arange(L) / L)
phase = np.arange(L).reshape(-1, 1) * phase
return np.... | 610 | 25,161 |
numpy | numpy/random/_pickle.py | .py | from ._generator import Generator
from ._mt19937 import MT19937
from ._pcg64 import PCG64, PCG64DXSM
from ._philox import Philox
from ._sfc64 import SFC64
from .bit_generator import BitGenerator
from .mtrand import RandomState
BitGenerators = {'MT19937': MT19937,
'PCG64': PCG64,
'PCG6... | 89 | 2,742 |
numpy | numpy/random/__init__.py | .py | """
========================
Random Number Generation
========================
Use ``default_rng()`` to create a `Generator` and call its methods.
=============== =========================================================
Generator
--------------- ---------------------------------------------------------
Generator ... | 214 | 7,480 |
numpy | numpy/random/tests/test_randomstate.py | .py | import hashlib
import pickle
import sys
import warnings
import pytest
import numpy as np
from numpy import random
from numpy.random import MT19937, PCG64
from numpy.testing import (
IS_WASM,
assert_,
assert_array_almost_equal,
assert_array_equal,
assert_equal,
assert_no_warnings,
assert_ra... | 2,108 | 88,050 |
numpy | numpy/random/tests/test_regression.py | .py | import inspect
import sys
import pytest
import numpy as np
from numpy import random
from numpy.testing import assert_, assert_array_equal, assert_raises
class TestRegression:
def test_VonMises_range(self):
# Make sure generated random variables are in [-pi, pi].
# Regression test for ticket #98... | 175 | 6,244 |
numpy | numpy/random/tests/test_generator_mt19937_regressions.py | .py | import pytest
import numpy as np
from numpy.random import MT19937, PCG64, Generator
from numpy.testing import assert_, assert_array_equal
class TestRegression:
def _create_generator(self):
return Generator(MT19937(121263137472525314065))
def test_vonmises_range(self):
# Make sure generated r... | 241 | 9,328 |
numpy | numpy/random/tests/test_smoke.py | .py | import pickle
from dataclasses import dataclass
from functools import partial
import pytest
import numpy as np
from numpy.random import MT19937, PCG64, PCG64DXSM, SFC64, Generator, Philox
from numpy.testing import assert_, assert_array_equal, assert_equal
DTYPES_BOOL_INT_UINT = (np.bool, np.int8, np.int16, np.int32,... | 883 | 29,939 |
numpy | numpy/random/tests/test_random.py | .py | import sys
import warnings
import pytest
import numpy as np
from numpy import random
from numpy.testing import (
IS_WASM,
assert_,
assert_array_almost_equal,
assert_array_equal,
assert_equal,
assert_no_warnings,
assert_raises,
)
class TestSeed:
def test_scalar(self):
s = np.r... | 1,724 | 71,231 |
numpy | numpy/random/tests/test_seed_sequence.py | .py | import numpy as np
from numpy.random import SeedSequence
from numpy.testing import (
assert_array_compare,
assert_array_equal,
assert_raises,
assert_raises_regex,
)
def test_reference_data():
""" Check that SeedSequence generates data the same as the C++ reference.
https://gist.github.com/imn... | 104 | 3,972 |
numpy | numpy/random/tests/test_extending.py | .py | import os
import shutil
import sys
import sysconfig
import warnings
from importlib.util import module_from_spec, spec_from_file_location
import pytest
import numpy as np
from numpy.testing import HAS_SUBPROCESSES, IS_EDITABLE
from numpy.testing._private.utils import run_subprocess
try:
import cffi
except ImportE... | 130 | 4,623 |
numpy | numpy/random/tests/test_randomstate_regression.py | .py | import sys
import pytest
import numpy as np
from numpy import random
from numpy.testing import assert_, assert_array_equal, assert_raises
class TestRegression:
def test_VonMises_range(self):
# Make sure generated random variables are in [-pi, pi].
# Regression test for ticket #986.
for ... | 250 | 9,319 |
numpy | numpy/random/tests/test_direct.py | .py | import os
import sys
from os.path import join
import pytest
import numpy as np
from numpy.random import (
MT19937,
PCG64,
PCG64DXSM,
SFC64,
Generator,
Philox,
RandomState,
SeedSequence,
default_rng,
)
from numpy.random._common import interface
from numpy.testing import (
assert... | 621 | 20,852 |
numpy | numpy/random/tests/test_generator_mt19937.py | .py | import hashlib
import os.path
import sys
import warnings
import pytest
import numpy as np
from numpy.exceptions import AxisError
from numpy.linalg import LinAlgError
from numpy.random import MT19937, Generator, RandomState, SeedSequence
from numpy.testing import (
IS_64BIT,
IS_WASM,
assert_,
assert_al... | 2,830 | 118,963 |
numpy | numpy/random/_examples/numba/extending.py | .py | from timeit import timeit
import numba as nb
import numpy as np
from numpy.random import PCG64
bit_gen = PCG64()
next_d = bit_gen.cffi.next_double
state_addr = bit_gen.cffi.state_address
def normals(n, state):
out = np.empty(n)
for i in range((n + 1) // 2):
x1 = 2.0 * next_d(state) - 1.0
x2 ... | 87 | 1,959 |
numpy | numpy/random/_examples/numba/extending_distributions.py | .py | r"""
Building the required library in this example requires a source distribution
of NumPy or clone of the NumPy git repository since distributions.c is not
included in binary distributions.
On *nix, execute in numpy/random/src/distributions
export ${PYTHON_VERSION}=3.8 # Python version
export PYTHON_INCLUDE=#path to... | 68 | 2,036 |
numpy | numpy/random/_examples/cffi/extending.py | .py | """
Use cffi to access any of the underlying C functions from distributions.h
"""
import os
import cffi
import numpy as np
from .parse import parse_distributions_h
ffi = cffi.FFI()
inc_dir = os.path.join(np.get_include(), 'numpy')
# Basic numpy types
ffi.cdef('''
typedef intptr_t npy_intp;
typedef unsigne... | 45 | 882 |
numpy | numpy/random/_examples/cffi/parse.py | .py | import os
def parse_distributions_h(ffi, inc_dir):
"""
Parse distributions.h located in inc_dir for CFFI, filling in the ffi.cdef
Read the function declarations without the "#define ..." macros that will
be filled in when loading the library.
"""
with open(os.path.join(inc_dir, 'random', 'bi... | 54 | 1,750 |
numpy | numpy/polynomial/legendre.py | .py | """
==================================================
Legendre Series (:mod:`numpy.polynomial.legendre`)
==================================================
This module provides a number of objects (mostly functions) useful for
dealing with Legendre series, including a `Legendre` class that
encapsulates the usual arit... | 1,656 | 53,023 |
numpy | numpy/polynomial/chebyshev.py | .py | """
====================================================
Chebyshev Series (:mod:`numpy.polynomial.chebyshev`)
====================================================
This module provides a number of objects (mostly functions) useful for
dealing with Chebyshev series, including a `Chebyshev` class that
encapsulates the us... | 2,054 | 64,229 |
numpy | numpy/polynomial/laguerre.py | .py | """
==================================================
Laguerre Series (:mod:`numpy.polynomial.laguerre`)
==================================================
This module provides a number of objects (mostly functions) useful for
dealing with Laguerre series, including a `Laguerre` class that
encapsulates the usual arit... | 1,730 | 54,515 |
numpy | numpy/polynomial/polyutils.py | .py | """
Utility classes and functions for the polynomial modules.
This module provides: error and warning objects; a polynomial base class;
and some routines used in both the `polynomial` and `chebyshev` modules.
Functions
---------
.. autosummary::
:toctree: generated/
as_series convert list of array_likes in... | 760 | 22,635 |
numpy | numpy/polynomial/polynomial.py | .py | """
=================================================
Power Series (:mod:`numpy.polynomial.polynomial`)
=================================================
This module provides a number of objects (mostly functions) useful for
dealing with polynomials, including a `Polynomial` class that
encapsulates the usual arithmeti... | 1,684 | 54,834 |
numpy | numpy/polynomial/__init__.py | .py | """
A sub-package for efficiently dealing with polynomials.
Within the documentation for this sub-package, a "finite power series,"
i.e., a polynomial (also referred to simply as a "series") is represented
by a 1-D numpy array of the polynomial's coefficients, ordered from lowest
order term to highest. For example, a... | 188 | 6,726 |
numpy | numpy/polynomial/_polybase.py | .py | """
Abstract base class for the various polynomial Classes.
The ABCPolyBase class provides the methods needed to implement the common API
for the various polynomial classes. It operates as a mixin, but uses the
abc module from the stdlib, hence it is only available for Python >= 2.6.
"""
import abc
import numbers
imp... | 1,192 | 39,358 |
numpy | numpy/polynomial/hermite_e.py | .py | """
===================================================================
HermiteE Series, "Probabilists" (:mod:`numpy.polynomial.hermite_e`)
===================================================================
This module provides a number of objects (mostly functions) useful for
dealing with Hermite_e series, including... | 1,693 | 54,210 |
numpy | numpy/polynomial/hermite.py | .py | """
==============================================================
Hermite Series, "Physicists" (:mod:`numpy.polynomial.hermite`)
==============================================================
This module provides a number of objects (mostly functions) useful for
dealing with Hermite series, including a `Hermite` clas... | 1,795 | 56,647 |
numpy | numpy/polynomial/tests/test_legendre.py | .py | """Tests for legendre module.
"""
from functools import reduce
import numpy as np
import numpy.polynomial.legendre as leg
from numpy.polynomial.polynomial import polyval
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
L0 = np.array([1])
L1 = np.array([0, 1])
L2 = np.array([-1, 0, ... | 588 | 19,356 |
numpy | numpy/polynomial/tests/test_hermite.py | .py | """Tests for hermite module.
"""
from functools import reduce
import numpy as np
import numpy.polynomial.hermite as herm
from numpy.polynomial.polynomial import polyval
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
H0 = np.array([1])
H1 = np.array([0, 2])
H2 = np.array([-2, 0, 4... | 575 | 19,247 |
numpy | numpy/polynomial/tests/test_laguerre.py | .py | """Tests for laguerre module.
"""
from functools import reduce
import numpy as np
import numpy.polynomial.laguerre as lag
from numpy.polynomial.polynomial import polyval
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
L0 = np.array([1]) / 1
L1 = np.array([1, -1]) / 1
L2 = np.array... | 557 | 18,188 |
numpy | numpy/polynomial/tests/test_chebyshev.py | .py | """Tests for chebyshev module.
"""
from functools import reduce
import numpy as np
import numpy.polynomial.chebyshev as cheb
from numpy.polynomial.polynomial import polyval
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
def trim(x):
return cheb.chebtrim(x, tol=1e-6)
T0 = [... | 640 | 21,210 |
numpy | numpy/polynomial/tests/test_classes.py | .py | """Test inter-conversion of different polynomial classes.
This tests the convert and cast methods of all the polynomial classes.
"""
import operator as op
from numbers import Number
import pytest
import numpy as np
from numpy.exceptions import RankWarning
from numpy.polynomial import (
Chebyshev,
Hermite,
... | 626 | 18,933 |
numpy | numpy/polynomial/tests/test_symbol.py | .py | """
Tests related to the ``symbol`` attribute of the ABCPolyBase class.
"""
import pytest
import numpy.polynomial as poly
from numpy._core import array
from numpy.testing import assert_, assert_equal, assert_raises
class TestInit:
"""
Test polynomial creation with symbol kwarg.
"""
c = [1, 2, 3]
... | 218 | 5,375 |
numpy | numpy/polynomial/tests/test_polyutils.py | .py | """Tests for polyutils module.
"""
import numpy as np
import numpy.polynomial.polyutils as pu
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
class TestMisc:
def test_trimseq(self):
tgt = [1]
for num_trailing_zeros in range(5):
res = pu.trimseq([1]... | 124 | 3,759 |
numpy | numpy/polynomial/tests/test_printing.py | .py | from decimal import Decimal
# For testing polynomial printing with object arrays
from fractions import Fraction
from math import inf, nan
import pytest
import numpy.polynomial as poly
from numpy._core import arange, array, printoptions
from numpy.testing import assert_, assert_equal
class TestStrUnicodeSuperSubscr... | 563 | 21,617 |
numpy | numpy/polynomial/tests/test_polynomial.py | .py | """Tests for polynomial module.
"""
import pickle
from copy import deepcopy
from fractions import Fraction
from functools import reduce
import pytest
import numpy as np
import numpy.polynomial.polynomial as poly
from numpy.testing import (
assert_,
assert_almost_equal,
assert_array_equal,
assert_equa... | 714 | 24,195 |
numpy | numpy/polynomial/tests/test_hermite_e.py | .py | """Tests for hermite_e module.
"""
from functools import reduce
import numpy as np
import numpy.polynomial.hermite_e as herme
from numpy.polynomial.polynomial import polyval
from numpy.testing import assert_, assert_almost_equal, assert_equal, assert_raises
He0 = np.array([1])
He1 = np.array([0, 1])
He2 = np.array([... | 576 | 19,595 |
numpy | numpy/char/__init__.py | .py | from numpy._core.defchararray import __all__, __doc__
__DEPRECATED = frozenset({"chararray", "array", "asarray"})
def __getattr__(name: str):
if name in __DEPRECATED:
# Deprecated in NumPy 2.5, 2026-01-07
import warnings
warnings.warn(
(
"The chararray class i... | 32 | 828 |
numpy | numpy/typing/__init__.py | .py | """
============================
Typing (:mod:`numpy.typing`)
============================
.. versionadded:: 1.20
Large parts of the NumPy API have :pep:`484`-style type annotations. In
addition a number of type aliases are available to users, most prominently
the two below:
- `ArrayLike`: objects that can be conver... | 217 | 6,692 |
numpy | numpy/typing/tests/test_runtime.py | .py | """Test the runtime usage of `numpy.typing`."""
from typing import (
Any,
NamedTuple,
Self,
TypeAliasType,
get_args,
get_origin,
get_type_hints,
)
import pytest
import numpy as np
import numpy._typing as _npt
import numpy.typing as npt
class TypeTup(NamedTuple):
typ: type # type ex... | 104 | 3,114 |
numpy | numpy/typing/tests/test_isfile.py | .py | import os
from pathlib import Path
import pytest
import numpy as np
from numpy.testing import assert_
ROOT = Path(np.__file__).parents[0]
FILES = [
ROOT / "py.typed",
ROOT / "__init__.pyi",
ROOT / "ctypeslib" / "__init__.pyi",
ROOT / "_core" / "__init__.pyi",
ROOT / "f2py" / "__init__.pyi",
R... | 36 | 954 |
numpy | numpy/typing/tests/test_typing.py | .py | import importlib.util
import os
import re
import shutil
import textwrap
from collections import defaultdict
from typing import TYPE_CHECKING
import pytest
# Only trigger a full `mypy` run if this environment variable is set
# Note that these tests tend to take over a minute even on a macOS M1 CPU,
# and more than tha... | 208 | 6,420 |
numpy | numpy/typing/tests/data/pass/bitwise_ops.py | .py | import numpy as np
i8 = np.int64(1)
u8 = np.uint64(1)
i4 = np.int32(1)
u4 = np.uint32(1)
b_ = np.bool(1)
b = bool(1)
i = 1
AR = np.array([0, 1, 2], dtype=np.int32)
AR.setflags(write=False)
i8 << i8
i8 >> i8
i8 | i8
i8 ^ i8
i8 & i8
i << AR
i >> AR
i | AR
i ^ AR
i & AR
i8 << AR
i8 >> AR
i8 | AR
i8 ^ AR
i8 & AR
... | 132 | 959 |
numpy | numpy/typing/tests/data/pass/simple.py | .py | """Simple expression that should pass with mypy."""
import operator
from collections.abc import Iterable
import numpy as np
import numpy.typing as npt
# Basic checks
array = np.array([1, 2])
def ndarray_func(x: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]:
return x
ndarray_func(np.array([1, 2], dtype=n... | 171 | 2,755 |
numpy | numpy/typing/tests/data/pass/comparisons.py | .py | from __future__ import annotations
from typing import Any, cast
import numpy as np
c16 = np.complex128()
f8 = np.float64()
i8 = np.int64()
u8 = np.uint64()
c8 = np.complex64()
f4 = np.float32()
i4 = np.int32()
u4 = np.uint32()
dt = np.datetime64(0, "D")
td = np.timedelta64(0, "D")
b_ = np.bool()
b = False
c = 0j... | 317 | 3,405 |
numpy | numpy/typing/tests/data/pass/flatiter.py | .py | import numpy as np
a = np.empty((2, 2)).flat
a.base
a.copy()
a.coords
a.index
iter(a)
next(a)
a[0]
a[...]
a[:]
a.__array__()
b = np.array([1]).flat
a[b]
a[0] = "1"
a[:] = "2"
a[...] = "3"
a[[]] = "4"
a[[0]] = "5"
a[[[0]]] = "6"
a[[[[[0]]]]] = "7"
a[b] = "8"
| 27 | 262 |
numpy | numpy/typing/tests/data/pass/ndarray_misc.py | .py | """
Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods.
More extensive tests are performed for the methods'
function-based counterpart in `../from_numeric.py`.
"""
from __future__ import annotations
import operator
from collections.abc import Hashable
from typing import Any, cast
import nump... | 200 | 3,408 |
numpy | numpy/typing/tests/data/pass/einsumfunc.py | .py | from __future__ import annotations
from typing import Any
import numpy as np
AR_LIKE_b = [True, True, True]
AR_LIKE_u = [np.uint32(1), np.uint32(2), np.uint32(3)]
AR_LIKE_i = [1, 2, 3]
AR_LIKE_f = [1.0, 2.0, 3.0]
AR_LIKE_c = [1j, 2j, 3j]
AR_LIKE_U = ["1", "2", "3"]
OUT_f: np.ndarray[Any, np.dtype[np.float64]] = np.... | 37 | 1,370 |
numpy | numpy/typing/tests/data/pass/lib_utils.py | .py | from __future__ import annotations
from io import StringIO
import numpy as np
import numpy.lib.array_utils as array_utils
FILE = StringIO()
AR = np.arange(10, dtype=np.float64)
def func(a: int) -> bool:
return True
array_utils.byte_bounds(AR)
array_utils.byte_bounds(np.float64())
np.info(1, output=FILE)
| 20 | 317 |
numpy | numpy/typing/tests/data/pass/recfunctions.py | .py | """These tests are based on the doctests from `numpy/lib/recfunctions.py`."""
from typing import Any, assert_type
import numpy as np
import numpy.typing as npt
from numpy.lib import recfunctions as rfn
def test_recursive_fill_fields() -> None:
a: npt.NDArray[np.void] = np.array(
[(1, 10.0), (2, 20.0)],
... | 165 | 4,974 |
numpy | numpy/typing/tests/data/pass/numeric.py | .py | """
Tests for :mod:`numpy._core.numeric`.
Does not include tests which fall under ``array_constructors``.
"""
from typing import Any
import numpy as np
class SubClass(np.ndarray[tuple[Any, ...], np.dtype[np.float64]]): ...
i8 = np.int64(1)
A = np.arange(27).reshape(3, 3, 3)
B = A.tolist()
C = np.empty((27, 27))... | 91 | 1,492 |
numpy | numpy/typing/tests/data/pass/arrayterator.py | .py |
from __future__ import annotations
from typing import Any
import numpy as np
AR_i8: np.ndarray[Any, np.dtype[np.int_]] = np.arange(10)
ar_iter = np.lib.Arrayterator(AR_i8)
ar_iter.var
ar_iter.buf_size
ar_iter.start
ar_iter.stop
ar_iter.step
ar_iter.shape
ar_iter.flat
ar_iter.__array__()
for i in ar_iter:
pas... | 29 | 394 |
numpy | numpy/typing/tests/data/pass/random.py | .py | from __future__ import annotations
from typing import Any
import numpy as np
SEED_NONE = None
SEED_INT = 4579435749574957634658964293569
SEED_ARR: np.ndarray[Any, np.dtype[np.int64]] = np.array([1, 2, 3, 4], dtype=np.int64)
SEED_ARRLIKE: list[int] = [1, 2, 3, 4]
SEED_SEED_SEQ: np.random.SeedSequence = np.random.Seed... | 1,499 | 61,825 |
numpy | numpy/typing/tests/data/pass/scalars.py | .py | import datetime as dt
import pytest
import numpy as np
b = np.bool()
b_ = np.bool_()
u8 = np.uint64()
i8 = np.int64()
f8 = np.float64()
c16 = np.complex128()
U = np.str_()
S = np.bytes_()
# Construction
class D:
def __index__(self) -> int:
return 0
class C:
def __complex__(self) -> complex:
... | 263 | 4,147 |
numpy | numpy/typing/tests/data/pass/ndarray_conversion.py | .py | import os
import tempfile
import numpy as np
nd = np.array([[1, 2], [3, 4]])
scalar_array = np.array(1)
# item
scalar_array.item()
nd.item(1)
nd.item(0, 1)
nd.item((0, 1))
# tobytes
nd.tobytes()
nd.tobytes("C")
nd.tobytes(None)
# tofile
if os.name != "nt":
with tempfile.NamedTemporaryFile(suffix=".txt") as tmp... | 82 | 1,449 |
numpy | numpy/typing/tests/data/pass/array_constructors.py | .py | from typing import Any
import numpy as np
class Index:
def __index__(self) -> int:
return 0
class SubClass(np.ndarray[tuple[Any, ...], np.dtype[np.float64]]):
pass
def func(i: int, j: int, **kwargs: Any) -> SubClass:
return B
i8 = np.int64(1)
A = np.array([1])
B = A.view(SubClass).copy()
B... | 138 | 2,447 |
numpy | numpy/typing/tests/data/pass/ufuncs.py | .py | import numpy as np
np.sin(1)
np.sin([1, 2, 3])
np.sin(1, out=np.empty(1))
np.matmul(np.ones((2, 2, 2)), np.ones((2, 2, 2)), axes=[(0, 1), (0, 1), (0, 1)])
np.sin(1, signature="D->D")
# NOTE: `np.generic` subclasses are not guaranteed to support addition;
# re-enable this we can infer the exact return type of `np.sin(.... | 17 | 422 |
numpy | numpy/typing/tests/data/pass/modules.py | .py | import numpy as np
from numpy import f2py
np.char
np.ctypeslib
np.emath
np.fft
np.lib
np.linalg
np.ma
np.matrixlib
np.polynomial
np.random
np.rec
np.strings
np.testing
np.version
np.lib.format
np.lib.mixins
np.lib.scimath
np.lib.stride_tricks
np.lib.array_utils
np.ma.extras
np.polynomial.chebyshev
np.polynomial.hermi... | 46 | 625 |
numpy | numpy/typing/tests/data/pass/ufunc_config.py | .py | """Typing tests for `numpy._core._ufunc_config`."""
import numpy as np
def func1(a: str, b: int) -> None:
return None
def func2(a: str, b: int, c: float = 1.0) -> None:
return None
def func3(a: str, b: int) -> int:
return 0
class Write1:
def write(self, a: str) -> None:
return None
cl... | 65 | 1,205 |
numpy | numpy/typing/tests/data/pass/ma.py | .py | import datetime as dt
from typing import Any, cast
import numpy as np
import numpy.typing as npt
from numpy._typing import _Shape
type MaskedArray[ScalarT: np.generic] = np.ma.MaskedArray[_Shape, np.dtype[ScalarT]]
MAR_b: MaskedArray[np.bool] = np.ma.MaskedArray([True])
MAR_u: MaskedArray[np.uint32] = np.ma.MaskedAr... | 200 | 3,894 |
numpy | numpy/typing/tests/data/pass/lib_version.py | .py | from numpy.lib import NumpyVersion
version = NumpyVersion("1.8.0")
version.vstring
version.version
version.major
version.minor
version.bugfix
version.pre_release
version.is_devversion
version == version
version != version
version < "1.8.0"
version <= version
version > version
version >= "1.8.0"
| 19 | 299 |
numpy | numpy/typing/tests/data/pass/arrayprint.py | .py | import numpy as np
AR = np.arange(10)
AR.setflags(write=False)
with np.printoptions():
np.set_printoptions(
precision=1,
threshold=2,
edgeitems=3,
linewidth=4,
suppress=False,
nanstr="Bob",
infstr="Bill",
formatter={},
sign="+",
float... | 38 | 766 |
numpy | numpy/typing/tests/data/pass/ufunclike.py | .py | from __future__ import annotations
from typing import Any
import numpy as np
class Object:
def __ceil__(self) -> Object:
return self
def __floor__(self) -> Object:
return self
def __trunc__(self) -> Object:
return self
def __ge__(self, value: object) -> bool:
retur... | 53 | 1,351 |
numpy | numpy/typing/tests/data/pass/array_like.py | .py | import numpy as np
from numpy._typing import ArrayLike, NDArray, _SupportsArray
x1: ArrayLike = True
x2: ArrayLike = 5
x3: ArrayLike = 1.0
x4: ArrayLike = 1 + 1j
x5: ArrayLike = np.int8(1)
x6: ArrayLike = np.float64(1)
x7: ArrayLike = np.complex128(1)
x8: ArrayLike = np.array([1, 2, 3])
x9: ArrayLike = [1, 2, 3]
x10: ... | 38 | 939 |
numpy | numpy/typing/tests/data/pass/ndarray_shape_manipulation.py | .py | import numpy as np
nd1 = np.array([[1, 2], [3, 4]])
# reshape
nd1.reshape(4)
nd1.reshape(2, 2)
nd1.reshape((2, 2))
nd1.reshape((2, 2), order="C")
nd1.reshape(4, order="C")
# resize
nd1.resize() # type: ignore[deprecated]
nd1.resize(4) # type: ignore[deprecated]
nd1.resize(2, 2) # type: ignore[deprecated]
nd1.res... | 48 | 808 |
numpy | numpy/typing/tests/data/pass/lib_user_array.py | .py | """Based on the `if __name__ == "__main__"` test code in `lib/_user_array_impl.py`."""
from __future__ import annotations
import numpy as np
from numpy.lib.user_array import container # type: ignore[deprecated]
N = 10_000
W = H = int(N**0.5)
a: np.ndarray[tuple[int, int], np.dtype[np.int32]]
ua: container[tuple[in... | 23 | 618 |
numpy | numpy/typing/tests/data/pass/numerictypes.py | .py | import numpy as np
np.isdtype(np.float64, (np.int64, np.float64))
np.isdtype(np.int64, "signed integer")
np.issubdtype("S1", np.bytes_)
np.issubdtype(np.float64, np.float32)
np.ScalarType
np.ScalarType[0]
np.ScalarType[3]
np.ScalarType[8]
np.ScalarType[10]
np.typecodes["Character"]
np.typecodes["Complex"]
np.typeco... | 18 | 331 |
numpy | numpy/typing/tests/data/pass/literal.py | .py | from __future__ import annotations
from functools import partial
from typing import TYPE_CHECKING, Any
import pytest
import numpy as np
if TYPE_CHECKING:
from collections.abc import Callable
AR = np.array(0)
AR.setflags(write=False)
KACF = frozenset({None, "K", "A", "C", "F"})
ACF = frozenset({None, "A", "C",... | 53 | 1,473 |
numpy | numpy/typing/tests/data/pass/arithmetic.py | .py | from __future__ import annotations
from typing import Any, cast
import pytest
import numpy as np
import numpy.typing as npt
c16 = np.complex128(1)
f8 = np.float64(1)
i8 = np.int64(1)
u8 = np.uint64(1)
c8 = np.complex64(1)
f4 = np.float32(1)
i4 = np.int32(1)
u4 = np.uint32(1)
dt = np.datetime64(1, "D")
td = np.tim... | 615 | 7,934 |
numpy | numpy/typing/tests/data/pass/warnings_and_errors.py | .py | import numpy.exceptions as ex
ex.AxisError("test")
ex.AxisError(1, ndim=2)
ex.AxisError(1, ndim=2, msg_prefix="error")
ex.AxisError(1, ndim=2, msg_prefix=None)
| 7 | 161 |
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