sentence1 stringlengths 52 3.87M | sentence2 stringlengths 1 47.2k | label stringclasses 1
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def _find_parameter(self, name_list, create_missing=False, quiet=False):
"""
Tries to find and return the parameter of the specified name. The name
should be of the form
['branch1','branch2', 'parametername']
Setting create_missing=True means if it doesn't find a branch it
... | Tries to find and return the parameter of the specified name. The name
should be of the form
['branch1','branch2', 'parametername']
Setting create_missing=True means if it doesn't find a branch it
will create one.
Setting quiet=True will suppress error messages (for checking) | entailment |
def _clean_up_name(self, name):
"""
Cleans up the name according to the rules specified in this exact
function. Uses self.naughty, a list of naughty characters.
"""
for n in self.naughty: name = name.replace(n, '_')
return name | Cleans up the name according to the rules specified in this exact
function. Uses self.naughty, a list of naughty characters. | entailment |
def add_button(self, name, checkable=False, checked=False):
"""
Adds (and returns) a button at the specified location.
"""
# first clean up the name
name = self._clean_up_name(name)
# split into (presumably existing) branches and parameter
s = name.split('/')
... | Adds (and returns) a button at the specified location. | entailment |
def add_parameter(self, name='test', value=42.0, **kwargs):
"""
Adds a parameter "leaf" to the tree.
Parameters
----------
name='test'
The name of the leaf. It should be a string of the form
"branch1/branch2/parametername" and will be nested as i... | Adds a parameter "leaf" to the tree.
Parameters
----------
name='test'
The name of the leaf. It should be a string of the form
"branch1/branch2/parametername" and will be nested as indicated.
value=42.0
Value of the leaf.
Com... | entailment |
def _get_parameter_dictionary(self, base_name, dictionary, sorted_keys, parameter):
"""
Recursively loops over the parameter's children, adding
keys (starting with base_name) and values to the supplied dictionary
(provided they do not have a value of None).
"""
# assembl... | Recursively loops over the parameter's children, adding
keys (starting with base_name) and values to the supplied dictionary
(provided they do not have a value of None). | entailment |
def send_to_databox_header(self, destination_databox):
"""
Sends all the information currently in the tree to the supplied
databox's header, in alphabetical order. If the entries already
exists, just updates them.
"""
k, d = self.get_dictionary()
destination_datab... | Sends all the information currently in the tree to the supplied
databox's header, in alphabetical order. If the entries already
exists, just updates them. | entailment |
def get_dictionary(self):
"""
Returns the list of parameters and a dictionary of values
(good for writing to a databox header!)
Return format is sorted_keys, dictionary
"""
# output
k = list()
d = dict()
# loop over the root items
for i ... | Returns the list of parameters and a dictionary of values
(good for writing to a databox header!)
Return format is sorted_keys, dictionary | entailment |
def get_value(self, name):
"""
Returns the value of the parameter with the specified name.
"""
# first clean up the name
name = self._clean_up_name(name)
# now get the parameter object
x = self._find_parameter(name.split('/'))
# quit if it pooped.
... | Returns the value of the parameter with the specified name. | entailment |
def get_list_values(self, name):
"""
Returns the values for a list item of the specified name.
"""
# Make sure it's a list
if not self.get_type(name) in ['list']:
self.print_message('ERROR: "'+name+'" is not a list.')
return
# Return a co... | Returns the values for a list item of the specified name. | entailment |
def set_value(self, name, value, ignore_error=False, block_user_signals=False):
"""
Sets the variable of the supplied name to the supplied value.
Setting block_user_signals=True will temporarily block the widget from
sending any signals when setting the value.
"""
# firs... | Sets the variable of the supplied name to the supplied value.
Setting block_user_signals=True will temporarily block the widget from
sending any signals when setting the value. | entailment |
def save(self, path=None):
"""
Saves all the parameters to a text file using the databox
functionality. If path=None, saves to self._autosettings_path. If
self._autosettings_path=None, does not save.
"""
if path==None:
if self._autosettings_path ... | Saves all the parameters to a text file using the databox
functionality. If path=None, saves to self._autosettings_path. If
self._autosettings_path=None, does not save. | entailment |
def load(self, path=None, ignore_errors=True, block_user_signals=False):
"""
Loads all the parameters from a databox text file. If path=None,
loads from self._autosettings_path (provided this is not None).
Parameters
----------
path=None
Path to load ... | Loads all the parameters from a databox text file. If path=None,
loads from self._autosettings_path (provided this is not None).
Parameters
----------
path=None
Path to load the settings from. If None, will load from the
specified autosettings_path.
... | entailment |
def update(self, d, ignore_errors=True, block_user_signals=False):
"""
Supply a dictionary or databox with a header of the same format
and see what happens! (Hint: it updates the existing values.)
This will store non-existent key-value pairs in the dictionary
self._lazy... | Supply a dictionary or databox with a header of the same format
and see what happens! (Hint: it updates the existing values.)
This will store non-existent key-value pairs in the dictionary
self._lazy_load. When you add settings in the future,
these will be checked for the defau... | entailment |
def _set_value_safe(self, k, v, ignore_errors=False, block_user_signals=False):
"""
Actually sets the value, first by trying it directly, then by
"""
# for safety: by default assume it's a repr() with python code
try:
self.set_value(k, v, ignore_error = ignore_... | Actually sets the value, first by trying it directly, then by | entailment |
def _button_autosave_clicked(self, checked):
"""
Called whenever the button is clicked.
"""
if checked:
# get the path from the user
path = _spinmob.dialogs.save(filters=self.file_type)
# abort if necessary
if not path:
sel... | Called whenever the button is clicked. | entailment |
def save_file(self, path=None, force_overwrite=False, just_settings=False, **kwargs):
"""
Saves the data in the databox to a file.
Parameters
----------
path=None
Path for output. If set to None, use a save dialog.
force_overwrite=False
Do not que... | Saves the data in the databox to a file.
Parameters
----------
path=None
Path for output. If set to None, use a save dialog.
force_overwrite=False
Do not question the overwrite if the file already exists.
just_settings=False
Set to True to sa... | entailment |
def load_file(self, path=None, just_settings=False):
"""
Loads a data file. After the file is loaded, calls self.after_load_file(self),
which you can overwrite if you like!
just_settings=True will only load the configuration of the controls,
and will not plot anything or run aft... | Loads a data file. After the file is loaded, calls self.after_load_file(self),
which you can overwrite if you like!
just_settings=True will only load the configuration of the controls,
and will not plot anything or run after_load_file | entailment |
def _autoscript(self):
"""
Automatically generates a python script for plotting.
"""
# This should never happen unless I screwed up.
if self.combo_autoscript.get_index() == 0: return "ERROR: Ask Jack."
# if there is no data, leave it blank
if len(self)... | Automatically generates a python script for plotting. | entailment |
def plot(self):
"""
Sets the internal databox to the supplied value and plots it.
If databox=None, this will plot the internal databox.
"""
# if we're disabled or have no data columns, clear everything!
if not self.button_enabled.is_checked() or len(self) == 0:
... | Sets the internal databox to the supplied value and plots it.
If databox=None, this will plot the internal databox. | entailment |
def autosave(self):
"""
Autosaves the currently stored data, but only if autosave is checked!
"""
# make sure we're suppoed to
if self.button_autosave.is_checked():
# save the file
self.save_file(_os.path.join(self._autosave_directory, "%04d " % (self.num... | Autosaves the currently stored data, but only if autosave is checked! | entailment |
def autozoom(self, n=None):
"""
Auto-scales the axes to fit all the data in plot index n. If n == None,
auto-scale everyone.
"""
if n==None:
for p in self.plot_widgets: p.autoRange()
else: self.plot_widgets[n].autoRange()
return self | Auto-scales the axes to fit all the data in plot index n. If n == None,
auto-scale everyone. | entailment |
def _synchronize_controls(self):
"""
Updates the gui based on button configs.
"""
# whether the script is visible
self.grid_script._widget.setVisible(self.button_script.get_value())
# whether we should be able to edit it.
if not self.combo_autoscript.get_index()... | Updates the gui based on button configs. | entailment |
def _set_number_of_plots(self, n):
"""
Adjusts number of plots & curves to the desired value the gui.
"""
# multi plot, right number of plots and curves = great!
if self.button_multi.is_checked() \
and len(self._curves) == len(self.plot_widgets) \
a... | Adjusts number of plots & curves to the desired value the gui. | entailment |
def _update_linked_axes(self):
"""
Loops over the axes and links / unlinks them.
"""
# no axes to link!
if len(self.plot_widgets) <= 1: return
# get the first plotItem
a = self.plot_widgets[0].plotItem.getViewBox()
# now loop through all the axes... | Loops over the axes and links / unlinks them. | entailment |
def resolve_const_spec(self, name, lineno):
"""Finds and links the ConstSpec with the given name."""
if name in self.const_specs:
return self.const_specs[name].link(self)
if '.' in name:
include_name, component = name.split('.', 1)
if include_name in self.in... | Finds and links the ConstSpec with the given name. | entailment |
def resolve_type_spec(self, name, lineno):
"""Finds and links the TypeSpec with the given name."""
if name in self.type_specs:
return self.type_specs[name].link(self)
if '.' in name:
include_name, component = name.split('.', 1)
if include_name in self.includ... | Finds and links the TypeSpec with the given name. | entailment |
def resolve_service_spec(self, name, lineno):
"""Finds and links the ServiceSpec with the given name."""
if name in self.service_specs:
return self.service_specs[name].link(self)
if '.' in name:
include_name, component = name.split('.', 2)
if include_name in... | Finds and links the ServiceSpec with the given name. | entailment |
def add_include(self, name, included_scope, module):
"""Register an imported module into this scope.
Raises ``ThriftCompilerError`` if the name has already been used.
"""
# The compiler already ensures this. If we still get here with a
# conflict, that's a bug.
assert na... | Register an imported module into this scope.
Raises ``ThriftCompilerError`` if the name has already been used. | entailment |
def add_service_spec(self, service_spec):
"""Registers the given ``ServiceSpec`` into the scope.
Raises ``ThriftCompilerError`` if the name has already been used.
"""
assert service_spec is not None
if service_spec.name in self.service_specs:
raise ThriftCompilerErr... | Registers the given ``ServiceSpec`` into the scope.
Raises ``ThriftCompilerError`` if the name has already been used. | entailment |
def add_const_spec(self, const_spec):
"""Adds a ConstSpec to the compliation scope.
If the ConstSpec's ``save`` attribute is True, the constant will be
added to the module at the top-level.
"""
if const_spec.name in self.const_specs:
raise ThriftCompilerError(
... | Adds a ConstSpec to the compliation scope.
If the ConstSpec's ``save`` attribute is True, the constant will be
added to the module at the top-level. | entailment |
def add_surface(self, name, surface):
"""Adds a top-level attribute with the given name to the module."""
assert surface is not None
if hasattr(self.module, name):
raise ThriftCompilerError(
'Cannot define "%s". The name has already been used.' % name
)
... | Adds a top-level attribute with the given name to the module. | entailment |
def add_type_spec(self, name, spec, lineno):
"""Adds the given type to the scope.
:param str name:
Name of the new type
:param spec:
``TypeSpec`` object containing information on the type, or a
``TypeReference`` if this is meant to be resolved during the
... | Adds the given type to the scope.
:param str name:
Name of the new type
:param spec:
``TypeSpec`` object containing information on the type, or a
``TypeReference`` if this is meant to be resolved during the
``link`` stage.
:param lineno:
... | entailment |
def coarsen_array(a, level=2, method='mean'):
"""
Returns a coarsened (binned) version of the data. Currently supports
any of the numpy array operations, e.g. min, max, mean, std, ...
level=2 means every two data points will be binned.
level=0 or 1 just returns a copy of the array
"""
i... | Returns a coarsened (binned) version of the data. Currently supports
any of the numpy array operations, e.g. min, max, mean, std, ...
level=2 means every two data points will be binned.
level=0 or 1 just returns a copy of the array | entailment |
def coarsen_data(x, y, ey=None, ex=None, level=2, exponential=False):
"""
Coarsens the supplied data set. Returns coarsened arrays of x, y, along with
quadrature-coarsened arrays of ey and ex if specified.
Parameters
----------
x, y
Data arrays. Can be lists (will convert to numpy a... | Coarsens the supplied data set. Returns coarsened arrays of x, y, along with
quadrature-coarsened arrays of ey and ex if specified.
Parameters
----------
x, y
Data arrays. Can be lists (will convert to numpy arrays).
These are coarsened by taking an average.
ey=None, ex=None
... | entailment |
def coarsen_matrix(Z, xlevel=0, ylevel=0, method='average'):
"""
This returns a coarsened numpy matrix.
method can be 'average', 'maximum', or 'minimum'
"""
# coarsen x
if not ylevel:
Z_coarsened = Z
else:
temp = []
for z in Z: temp.append(coarsen_array(z, ylevel, m... | This returns a coarsened numpy matrix.
method can be 'average', 'maximum', or 'minimum' | entailment |
def erange(start, end, steps):
"""
Returns a numpy array over the specified range taking geometric steps.
See also numpy.logspace()
"""
if start == 0:
print("Nothing you multiply zero by gives you anything but zero. Try picking something small.")
return None
if end == 0:
... | Returns a numpy array over the specified range taking geometric steps.
See also numpy.logspace() | entailment |
def is_a_number(s):
"""
This takes an object and determines whether it's a number or a string
representing a number.
"""
if _s.fun.is_iterable(s) and not type(s) == str: return False
try:
float(s)
return 1
except:
try:
complex(s)
return 2
... | This takes an object and determines whether it's a number or a string
representing a number. | entailment |
def array_shift(a, n, fill="average"):
"""
This will return an array with all the elements shifted forward in index by n.
a is the array
n is the amount by which to shift (can be positive or negative)
fill="average" fill the new empty elements with the average of the array
fill="wrap" ... | This will return an array with all the elements shifted forward in index by n.
a is the array
n is the amount by which to shift (can be positive or negative)
fill="average" fill the new empty elements with the average of the array
fill="wrap" fill the new empty elements with the lopped-of... | entailment |
def assemble_covariance(error, correlation):
"""
This takes an error vector and a correlation matrix and assembles the covariance
"""
covariance = []
for n in range(0, len(error)):
covariance.append([])
for m in range(0, len(error)):
covariance[n].append(correlation[n][m... | This takes an error vector and a correlation matrix and assembles the covariance | entailment |
def combine_dictionaries(a, b):
"""
returns the combined dictionary. a's values preferentially chosen
"""
c = {}
for key in list(b.keys()): c[key]=b[key]
for key in list(a.keys()): c[key]=a[key]
return c | returns the combined dictionary. a's values preferentially chosen | entailment |
def decompose_covariance(c):
"""
This decomposes a covariance matrix into an error vector and a correlation matrix
"""
# make it a kickass copy of the original
c = _n.array(c)
# first get the error vector
e = []
for n in range(0, len(c[0])): e.append(_n.sqrt(c[n][n]))
# now cycle ... | This decomposes a covariance matrix into an error vector and a correlation matrix | entailment |
def derivative(xdata, ydata):
"""
performs d(ydata)/d(xdata) with nearest-neighbor slopes
must be well-ordered, returns new arrays [xdata, dydx_data]
neighbors:
"""
D_ydata = []
D_xdata = []
for n in range(1, len(xdata)-1):
D_xdata.append(xdata[n])
D_ydata.append((ydata[... | performs d(ydata)/d(xdata) with nearest-neighbor slopes
must be well-ordered, returns new arrays [xdata, dydx_data]
neighbors: | entailment |
def derivative_fit(xdata, ydata, neighbors=1):
"""
loops over the data points, performing a least-squares linear fit of the
nearest neighbors at each point. Returns an array of x-values and slopes.
xdata should probably be well-ordered.
neighbors How many data point on the left and right to incl... | loops over the data points, performing a least-squares linear fit of the
nearest neighbors at each point. Returns an array of x-values and slopes.
xdata should probably be well-ordered.
neighbors How many data point on the left and right to include. | entailment |
def distort_matrix_X(Z, X, f, new_xmin, new_xmax, subsample=3):
"""
Applies a distortion (remapping) to the matrix Z (and x-values X) using function f.
returns new_Z, new_X
f is an INVERSE function old_x(new_x)
Z is a matrix. X is an array where X[n] is the x-value associated with the array Z[n].
... | Applies a distortion (remapping) to the matrix Z (and x-values X) using function f.
returns new_Z, new_X
f is an INVERSE function old_x(new_x)
Z is a matrix. X is an array where X[n] is the x-value associated with the array Z[n].
new_xmin, new_xmax is the possible range of the distorted x-variable fo... | entailment |
def distort_matrix_Y(Z, Y, f, new_ymin, new_ymax, subsample=3):
"""
Applies a distortion (remapping) to the matrix Z (and y-values Y) using function f.
returns new_Z, new_Y
f is a function old_y(new_y)
Z is a matrix. Y is an array where Y[n] is the y-value associated with the array Z[:,n].
ne... | Applies a distortion (remapping) to the matrix Z (and y-values Y) using function f.
returns new_Z, new_Y
f is a function old_y(new_y)
Z is a matrix. Y is an array where Y[n] is the y-value associated with the array Z[:,n].
new_ymin, new_ymax is the range of the distorted x-variable for generating Z
... | entailment |
def dumbguy_minimize(f, xmin, xmax, xstep):
"""
This just steps x and looks for a peak
returns x, f(x)
"""
prev = f(xmin)
this = f(xmin+xstep)
for x in frange(xmin+xstep,xmax,xstep):
next = f(x+xstep)
# see if we're on top
if this < prev and this < next: return x, ... | This just steps x and looks for a peak
returns x, f(x) | entailment |
def elements_are_numbers(array):
"""
Tests whether the elements of the supplied array are numbers.
"""
# empty case
if len(array) == 0: return 0
output_value = 1
for x in array:
# test it and die if it's not a number
test = is_a_number(x)
if not test: return False
... | Tests whether the elements of the supplied array are numbers. | entailment |
def equalize_list_lengths(a,b):
"""
Modifies the length of list a to match b. Returns a.
a can also not be a list (will convert it to one).
a will not be modified.
"""
if not _s.fun.is_iterable(a): a = [a]
a = list(a)
while len(a)>len(b): a.pop(-1)
while len(a)<len(b): a.append(a[-1... | Modifies the length of list a to match b. Returns a.
a can also not be a list (will convert it to one).
a will not be modified. | entailment |
def find_N_peaks(array, N=4, max_iterations=100, rec_max_iterations=3, recursion=1):
"""
This will run the find_peaks algorythm, adjusting the baseline until exactly N peaks are found.
"""
if recursion<0: return None
# get an initial guess as to the baseline
ymin = min(array)
ymax = max(ar... | This will run the find_peaks algorythm, adjusting the baseline until exactly N peaks are found. | entailment |
def find_peaks(array, baseline=0.1, return_subarrays=False):
"""
This will try to identify the indices of the peaks in array, returning a list of indices in ascending order.
Runs along the data set until it jumps above baseline. Then it considers all the subsequent data above the baseline
as part of th... | This will try to identify the indices of the peaks in array, returning a list of indices in ascending order.
Runs along the data set until it jumps above baseline. Then it considers all the subsequent data above the baseline
as part of the peak, and records the maximum of this data as one peak value. | entailment |
def find_zero_bisect(f, xmin, xmax, xprecision):
"""
This will bisect the range and zero in on zero.
"""
if f(xmax)*f(xmin) > 0:
print("find_zero_bisect(): no zero on the range",xmin,"to",xmax)
return None
temp = min(xmin,xmax)
xmax = max(xmin,xmax)
xmin = temp
xmid = (... | This will bisect the range and zero in on zero. | entailment |
def fit_linear(xdata, ydata):
"""
Returns slope and intercept of line of best fit:
y = a*x + b
through the supplied data.
Parameters
----------
xdata, ydata:
Arrays of x data and y data (having matching lengths).
"""
x = _n.array(xdata)
y = _n.arra... | Returns slope and intercept of line of best fit:
y = a*x + b
through the supplied data.
Parameters
----------
xdata, ydata:
Arrays of x data and y data (having matching lengths). | entailment |
def frange(start, end, inc=1.0):
"""
A range function, that accepts float increments and reversed direction.
See also numpy.linspace()
"""
start = 1.0*start
end = 1.0*end
inc = 1.0*inc
# if we got a dumb increment
if not inc: return _n.array([start,end])
# if the incremen... | A range function, that accepts float increments and reversed direction.
See also numpy.linspace() | entailment |
def generate_fake_data(f='2*x-5', x=_n.linspace(-5,5,11), ey=1, ex=0, include_errors=False, **kwargs):
"""
Generates a set of fake data from the underlying "reality" (or mean
behavior) function f.
Parameters
----------
f:
Underlying "reality" function or mean behavior. This can be a... | Generates a set of fake data from the underlying "reality" (or mean
behavior) function f.
Parameters
----------
f:
Underlying "reality" function or mean behavior. This can be any
python-evaluable string, and will have access to all the numpy
functions (e.g., cos), scipy's sp... | entailment |
def get_shell_history():
"""
This only works with some shells.
"""
# try for ipython
if 'get_ipython' in globals():
a = list(get_ipython().history_manager.input_hist_raw)
a.reverse()
return a
elif 'SPYDER_SHELL_ID' in _os.environ:
try:
p = _os.path.jo... | This only works with some shells. | entailment |
def index(value, array):
"""
Array search that behaves like I want it to. Totally dumb, I know.
"""
i = array.searchsorted(value)
if i == len(array): return -1
else: return i | Array search that behaves like I want it to. Totally dumb, I know. | entailment |
def index_nearest(value, array):
"""
expects a _n.array
returns the global minimum of (value-array)^2
"""
a = (array-value)**2
return index(a.min(), a) | expects a _n.array
returns the global minimum of (value-array)^2 | entailment |
def index_next_crossing(value, array, starting_index=0, direction=1):
"""
starts at starting_index, and walks through the array until
it finds a crossing point with value
set direction=-1 for down crossing
"""
for n in range(starting_index, len(array)-1):
if (value-array[n] )*directi... | starts at starting_index, and walks through the array until
it finds a crossing point with value
set direction=-1 for down crossing | entailment |
def insert_ordered(value, array):
"""
This will insert the value into the array, keeping it sorted, and returning the
index where it was inserted
"""
index = 0
# search for the last array item that value is larger than
for n in range(0,len(array)):
if value >= array[n]: index = n+1... | This will insert the value into the array, keeping it sorted, and returning the
index where it was inserted | entailment |
def integrate_data(xdata, ydata, xmin=None, xmax=None, autozero=0):
"""
Numerically integrates up the ydata using the trapezoid approximation.
estimate the bin width (scaled by the specified amount).
Returns (xdata, integrated ydata).
autozero is the number of data points to use as an estimate of t... | Numerically integrates up the ydata using the trapezoid approximation.
estimate the bin width (scaled by the specified amount).
Returns (xdata, integrated ydata).
autozero is the number of data points to use as an estimate of the background
(then subtracted before integrating). | entailment |
def invert_increasing_function(f, f0, xmin, xmax, tolerance, max_iterations=100):
"""
This will try try to qickly find a point on the f(x) curve between xmin and xmax that is
equal to f0 within tolerance.
"""
for n in range(max_iterations):
# start at the middle
x = 0.5*(xmin+xmax)
... | This will try try to qickly find a point on the f(x) curve between xmin and xmax that is
equal to f0 within tolerance. | entailment |
def fft(t, y, pow2=False, window=None, rescale=False):
"""
FFT of y, assuming complex or real-valued inputs. This goes through the
numpy fourier transform process, assembling and returning (frequencies,
complex fft) given time and signal data y.
Parameters
----------
t,y
Time (t) ... | FFT of y, assuming complex or real-valued inputs. This goes through the
numpy fourier transform process, assembling and returning (frequencies,
complex fft) given time and signal data y.
Parameters
----------
t,y
Time (t) and signal (y) arrays with which to perform the fft. Note the t
... | entailment |
def psd(t, y, pow2=False, window=None, rescale=False):
"""
Single-sided power spectral density, assuming real valued inputs. This goes
through the numpy fourier transform process, assembling and returning
(frequencies, psd) given time and signal data y.
Note it is defined such that sum(psd)*d... | Single-sided power spectral density, assuming real valued inputs. This goes
through the numpy fourier transform process, assembling and returning
(frequencies, psd) given time and signal data y.
Note it is defined such that sum(psd)*df, where df is the frequency
spacing, is the variance of the or... | entailment |
def replace_in_files(search, replace, depth=0, paths=None, confirm=True):
"""
Does a line-by-line search and replace, but only up to the "depth" line.
"""
# have the user select some files
if paths==None:
paths = _s.dialogs.MultipleFiles('DIS AND DAT|*.*')
if paths == []: return
fo... | Does a line-by-line search and replace, but only up to the "depth" line. | entailment |
def replace_lines_in_files(search_string, replacement_line):
"""
Finds lines containing the search string and replaces the whole line with
the specified replacement string.
"""
# have the user select some files
paths = _s.dialogs.MultipleFiles('DIS AND DAT|*.*')
if paths == []: return
... | Finds lines containing the search string and replaces the whole line with
the specified replacement string. | entailment |
def reverse(array):
"""
returns a reversed numpy array
"""
l = list(array)
l.reverse()
return _n.array(l) | returns a reversed numpy array | entailment |
def round_sigfigs(x, n=2):
"""
Rounds the number to the specified significant figures. x can also be
a list or array of numbers (in these cases, a numpy array is returned).
"""
iterable = is_iterable(x)
if not iterable: x = [x]
# make a copy to be safe
x = _n.array(x)
# loop o... | Rounds the number to the specified significant figures. x can also be
a list or array of numbers (in these cases, a numpy array is returned). | entailment |
def shift_feature_to_x0(xdata, ydata, x0=0, feature=imax):
"""
Finds a feature in the the ydata and shifts xdata so the feature is centered
at x0. Returns shifted xdata, ydata. Try me with plot.tweaks.manipulate_shown_data()!
xdata,ydata data set
x0=0 where to shift the peak
feat... | Finds a feature in the the ydata and shifts xdata so the feature is centered
at x0. Returns shifted xdata, ydata. Try me with plot.tweaks.manipulate_shown_data()!
xdata,ydata data set
x0=0 where to shift the peak
feature=imax function taking an array/list and returning the index of sa... | entailment |
def smooth_data(xdata, ydata, yerror, amount=1):
"""
Returns smoothed [xdata, ydata, yerror]. Does not destroy the input arrays.
"""
new_xdata = smooth_array(_n.array(xdata), amount)
new_ydata = smooth_array(_n.array(ydata), amount)
if yerror is None: new_yerror = None
else: ... | Returns smoothed [xdata, ydata, yerror]. Does not destroy the input arrays. | entailment |
def sort_matrix(a,n=0):
"""
This will rearrange the array a[n] from lowest to highest, and
rearrange the rest of a[i]'s in the same way. It is dumb and slow.
Returns a numpy array.
"""
a = _n.array(a)
return a[:,a[n,:].argsort()] | This will rearrange the array a[n] from lowest to highest, and
rearrange the rest of a[i]'s in the same way. It is dumb and slow.
Returns a numpy array. | entailment |
def submatrix(matrix,i1,i2,j1,j2):
"""
returns the submatrix defined by the index bounds i1-i2 and j1-j2
Endpoints included!
"""
new = []
for i in range(i1,i2+1):
new.append(matrix[i][j1:j2+1])
return _n.array(new) | returns the submatrix defined by the index bounds i1-i2 and j1-j2
Endpoints included! | entailment |
def trim_data(xmin, xmax, xdata, *args):
"""
Removes all the data except that in which xdata is between xmin and xmax.
This does not mutilate the input arrays, and additional arrays
can be supplied via args (provided they match xdata in shape)
xmin and xmax can be None
"""
# make sure it'... | Removes all the data except that in which xdata is between xmin and xmax.
This does not mutilate the input arrays, and additional arrays
can be supplied via args (provided they match xdata in shape)
xmin and xmax can be None | entailment |
def trim_data_uber(arrays, conditions):
"""
Non-destructively selects data from the supplied list of arrays based on
the supplied list of conditions. Importantly, if any of the conditions are
not met for the n'th data point, the n'th data point is rejected for
all supplied arrays.
Example
... | Non-destructively selects data from the supplied list of arrays based on
the supplied list of conditions. Importantly, if any of the conditions are
not met for the n'th data point, the n'th data point is rejected for
all supplied arrays.
Example
-------
x = numpy.linspace(0,10,20)
y = num... | entailment |
def _fetch(self, searchtype, fields, **kwargs):
'''Fetch a response from the Geocoding API.'''
fields['vintage'] = self.vintage
fields['benchmark'] = self.benchmark
fields['format'] = 'json'
if 'layers' in kwargs:
fields['layers'] = kwargs['layers']
returnty... | Fetch a response from the Geocoding API. | entailment |
def coordinates(self, x, y, **kwargs):
'''Geocode a (lon, lat) coordinate.'''
kwargs['returntype'] = 'geographies'
fields = {
'x': x,
'y': y
}
return self._fetch('coordinates', fields, **kwargs) | Geocode a (lon, lat) coordinate. | entailment |
def address(self, street, city=None, state=None, zipcode=None, **kwargs):
'''Geocode an address.'''
fields = {
'street': street,
'city': city,
'state': state,
'zip': zipcode,
}
return self._fetch('address', fields, **kwargs) | Geocode an address. | entailment |
def onelineaddress(self, address, **kwargs):
'''Geocode an an address passed as one string.
e.g. "4600 Silver Hill Rd, Suitland, MD 20746"
'''
fields = {
'address': address,
}
return self._fetch('onelineaddress', fields, **kwargs) | Geocode an an address passed as one string.
e.g. "4600 Silver Hill Rd, Suitland, MD 20746" | entailment |
def addressbatch(self, data, **kwargs):
'''
Send either a CSV file or data to the addressbatch API.
According to the Census, "there is currently an upper limit of 1000 records per batch file."
If a file, must have no header and fields id,street,city,state,zip
If data, should be a... | Send either a CSV file or data to the addressbatch API.
According to the Census, "there is currently an upper limit of 1000 records per batch file."
If a file, must have no header and fields id,street,city,state,zip
If data, should be a list of dicts with the above fields (although ID is optiona... | entailment |
def load_colormap(self, name=None):
"""
Loads a colormap of the supplied name. None means used the internal
name. (See self.get_name())
"""
if name == None: name = self.get_name()
if name == "" or not type(name)==str: return "Error: Bad name."
# assemble the pat... | Loads a colormap of the supplied name. None means used the internal
name. (See self.get_name()) | entailment |
def save_colormap(self, name=None):
"""
Saves the colormap with the specified name. None means use internal
name. (See get_name())
"""
if name == None: name = self.get_name()
if name == "" or not type(name)==str: return "Error: invalid name."
# get the colormaps ... | Saves the colormap with the specified name. None means use internal
name. (See get_name()) | entailment |
def delete_colormap(self, name=None):
"""
Deletes the colormap with the specified name. None means use the internal
name (see get_name())
"""
if name == None: name = self.get_name()
if name == "" or not type(name)==str: return "Error: invalid name."
# assemble th... | Deletes the colormap with the specified name. None means use the internal
name (see get_name()) | entailment |
def set_name(self, name="My Colormap"):
"""
Sets the name.
Make sure the name is something your OS could name a file.
"""
if not type(name)==str:
print("set_name(): Name must be a string.")
return
self._name = name
return self | Sets the name.
Make sure the name is something your OS could name a file. | entailment |
def set_image(self, image='auto'):
"""
Set which pylab image to tweak.
"""
if image=="auto": image = _pylab.gca().images[0]
self._image=image
self.update_image() | Set which pylab image to tweak. | entailment |
def update_image(self):
"""
Set's the image's cmap.
"""
if self._image:
self._image.set_cmap(self.get_cmap())
_pylab.draw() | Set's the image's cmap. | entailment |
def pop_colorpoint(self, n=0):
"""
Removes and returns the specified colorpoint. Will always leave two behind.
"""
# make sure we have more than 2; otherwise don't pop it, just return it
if len(self._colorpoint_list) > 2:
# do the popping
x = self._color... | Removes and returns the specified colorpoint. Will always leave two behind. | entailment |
def insert_colorpoint(self, position=0.5, color1=[1.0,1.0,0.0], color2=[1.0,1.0,0.0]):
"""
Inserts the specified color into the list.
"""
L = self._colorpoint_list
# if position = 0 or 1, push the end points inward
if position <= 0.0:
L.insert(0,[0.0,color1... | Inserts the specified color into the list. | entailment |
def modify_colorpoint(self, n, position=0.5, color1=[1.0,1.0,1.0], color2=[1.0,1.0,1.0]):
"""
Changes the values of an existing colorpoint, then updates the colormap.
"""
if n==0.0 : position = 0.0
elif n==len(self._colorpoint_list)-1: position = 1.0
... | Changes the values of an existing colorpoint, then updates the colormap. | entailment |
def get_cmap(self):
"""
Generates a pylab cmap object from the colorpoint data.
"""
# now generate the colormap from the ordered list
r = []
g = []
b = []
for p in self._colorpoint_list:
r.append((p[0], p[1][0]*1.0, p[2][0]*1.0))
g... | Generates a pylab cmap object from the colorpoint data. | entailment |
def _build_gui(self):
"""
Removes all existing sliders and rebuilds them based on the colormap.
"""
# remove all widgets (should destroy all children too)
self._central_widget.deleteLater()
# remove all references to other controls
self._sliders = [... | Removes all existing sliders and rebuilds them based on the colormap. | entailment |
def _signal_load(self):
"""
Load the selected cmap.
"""
# set our name
self.set_name(str(self._combobox_cmaps.currentText()))
# load the colormap
self.load_colormap()
# rebuild the interface
self._build_gui()
self._button_save.setEnable... | Load the selected cmap. | entailment |
def _button_save_clicked(self):
"""
Save the selected cmap.
"""
self.set_name(str(self._combobox_cmaps.currentText()))
self.save_colormap()
self._button_save.setEnabled(False)
self._load_cmap_list() | Save the selected cmap. | entailment |
def _button_delete_clicked(self):
"""
Save the selected cmap.
"""
name = str(self._combobox_cmaps.currentText())
self.delete_colormap(name)
self._combobox_cmaps.setEditText("")
self._load_cmap_list() | Save the selected cmap. | entailment |
def _color_dialog_changed(self, n, top, c):
"""
Updates the color of the slider.
"""
self._button_save.setEnabled(True)
cp = self._colorpoint_list[n]
# if they're linked, set both
if self._checkboxes[n].isChecked():
self.modify_colorpoint(n, cp[0], [... | Updates the color of the slider. | entailment |
def _button_plus_clicked(self, n):
"""
Create a new colorpoint.
"""
self._button_save.setEnabled(True)
self.insert_colorpoint(self._colorpoint_list[n][0],
self._colorpoint_list[n][1],
self._colorpoint_list[n][2])
... | Create a new colorpoint. | entailment |
def _button_minus_clicked(self, n):
"""
Remove a new colorpoint.
"""
self._button_save.setEnabled(True)
self.pop_colorpoint(n)
self._build_gui() | Remove a new colorpoint. | entailment |
def _slider_changed(self, n):
"""
updates the colormap / plot
"""
self._button_save.setEnabled(True)
self.modify_colorpoint(n, self._sliders[n].value()*0.001, self._colorpoint_list[n][1], self._colorpoint_list[n][2]) | updates the colormap / plot | entailment |
def _color_button_clicked(self, n,top):
"""
Opens the dialog.
"""
self._button_save.setEnabled(True)
if top: self._color_dialogs_top[n].open()
else: self._color_dialogs_bottom[n].open() | Opens the dialog. | entailment |
def _load_cmap_list(self):
"""
Searches the colormaps directory for all files, populates the list.
"""
# store the current name
name = self.get_name()
# clear the list
self._combobox_cmaps.blockSignals(True)
self._combobox_cmaps.clear()
# list th... | Searches the colormaps directory for all files, populates the list. | entailment |
def save(filters='*.*', text='Save THIS, facehead!', default_directory='default_directory', force_extension=None):
"""
Pops up a save dialog and returns the string path of the selected file.
Parameters
----------
filters='*.*'
Which file types should appear in the dialog.
text='Save... | Pops up a save dialog and returns the string path of the selected file.
Parameters
----------
filters='*.*'
Which file types should appear in the dialog.
text='Save THIS, facehead!'
Title text for the dialog.
default_directory='default_directory'
Key for the spinmob.sett... | entailment |
def load(filters="*.*", text='Select a file, FACEFACE!', default_directory='default_directory'):
"""
Pops up a dialog for opening a single file. Returns a string path or None.
"""
# make sure the filters contains "*.*" as an option!
if not '*' in filters.split(';'): filters = filters + ";;All files ... | Pops up a dialog for opening a single file. Returns a string path or None. | entailment |
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