neulab/docprompting-conala huggingface dataset:
set_fillstyle(fillstyle)[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
set_marker(marker)[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
matplotlib.mathtext.get_unicode_index(symbol, math=True)[source]
 
Return the integer index (from the Unicode table) of symbol.  Parameters 
 
symbolstr


A single unicode character, a TeX command (e.g. r'pi') or a Type1 symbol name (e.g. 'phi').  
mathbool, default: True


If False, always treat as a single unicode character.
matplotlib.mathtext.math_to_image(s, filename_or_obj, prop=None, dpi=None, format=None)[source]
 
Given a math expression, renders it in a closely-clipped bounding box to an image file.  Parameters 
 
sstr


A math expression. The math portion must be enclosed in dollar signs.  
filename_or_objstr or path-like or file-like


Where to write the image data.  
propFontProperties, optional


The size and style of the text.  
dpifloat, optional


The output dpi. If not set, the dpi is determined as for Figure.savefig.  
formatstr, optional


The output format, e.g., 'svg', 'pdf', 'ps' or 'png'. If not set, the format is determined as for Figure.savefig.
classmatplotlib.mathtext.MathtextBackend[source]
 
Bases: object The base class for the mathtext backend-specific code. MathtextBackend subclasses interface between mathtext and specific Matplotlib graphics backends. Subclasses need to override the following:  render_glyph() render_rect_filled() get_results()  And optionally, if you need to use a FreeType hinting style:  get_hinting_type()    get_hinting_type()[source]
 
Get the FreeType hinting type to use with this particular backend. 
   get_results(box)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2). 
   set_canvas_size(w, h, d)[source]
 
Set the dimension of the drawing canvas.
get_hinting_type()[source]
 
Get the FreeType hinting type to use with this particular backend.
get_results(box)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done.
render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy).
render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
set_canvas_size(w, h, d)[source]
 
Set the dimension of the drawing canvas.
classmatplotlib.mathtext.MathtextBackendAgg[source]
 
Bases: matplotlib.mathtext.MathtextBackend Render glyphs and rectangles to an FTImage buffer, which is later transferred to the Agg image by the Agg backend.   get_hinting_type()[source]
 
Get the FreeType hinting type to use with this particular backend. 
   get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2). 
   set_canvas_size(w, h, d)[source]
 
Set the dimension of the drawing canvas.
get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done.
classmatplotlib.mathtext.MathtextBackendBitmap[source]
 
Bases: matplotlib.mathtext.MathtextBackendAgg [Deprecated] Notes  Deprecated since version 3.4:     get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done.
classmatplotlib.mathtext.MathtextBackendCairo[source]
 
Bases: matplotlib.mathtext.MathtextBackend [Deprecated] Store information to write a mathtext rendering to the Cairo backend. Notes  Deprecated since version 3.4.    get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
classmatplotlib.mathtext.MathtextBackendPath[source]
 
Bases: matplotlib.mathtext.MathtextBackend Store information to write a mathtext rendering to the text path machinery.   get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
classmatplotlib.mathtext.MathtextBackendPdf[source]
 
Bases: matplotlib.mathtext.MathtextBackend [Deprecated] Store information to write a mathtext rendering to the PDF backend. Notes  Deprecated since version 3.4.    get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
classmatplotlib.mathtext.MathtextBackendPs[source]
 
Bases: matplotlib.mathtext.MathtextBackend [Deprecated] Store information to write a mathtext rendering to the PostScript backend. Notes  Deprecated since version 3.4.    get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
classmatplotlib.mathtext.MathtextBackendSvg[source]
 
Bases: matplotlib.mathtext.MathtextBackend [Deprecated] Store information to write a mathtext rendering to the SVG backend. Notes  Deprecated since version 3.4.    get_results(box, used_characters)[source]
 
Return a backend-specific tuple to return to the backend after all processing is done. 
   render_glyph(ox, oy, info)[source]
 
Draw a glyph described by info to the reference point (ox, oy). 
   render_rect_filled(x1, y1, x2, y2)[source]
 
Draw a filled black rectangle from (x1, y1) to (x2, y2).
classmatplotlib.mathtext.MathTextParser(output)[source]
 
Bases: object Create a MathTextParser for the given backend output.   get_depth(texstr, dpi=120, fontsize=14)[source]
 
[Deprecated] Get the depth of a mathtext string.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
dpifloat


The dots-per-inch setting used to render the text.    Returns 
 int

Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.  
   parse(s, dpi=72, prop=None, *, _force_standard_ps_fonts=False)[source]
 
Parse the given math expression s at the given dpi. If prop is provided, it is a FontProperties object specifying the "default" font to use in the math expression, used for all non-math text. The results are cached, so multiple calls to parse with the same expression should be fast. 
   to_mask(texstr, dpi=120, fontsize=14)[source]
 
[Deprecated] Convert a mathtext string to a grayscale array and depth.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points    Returns 
 
array2D uint8 alpha


Mask array of rasterized tex.  
depthint


Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.  
   to_png(filename, texstr, color='black', dpi=120, fontsize=14)[source]
 
[Deprecated] Render a tex expression to a PNG file.  Parameters 
 filename

A writable filename or fileobject.  
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
colorcolor


The text color.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points.    Returns 
 int

Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.  
   to_rgba(texstr, color='black', dpi=120, fontsize=14)[source]
 
[Deprecated] Convert a mathtext string to an RGBA array and depth.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
colorcolor


The text color.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points.    Returns 
 
array(M, N, 4) array


RGBA color values of rasterized tex, colorized with color.  
depthint


Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.
get_depth(texstr, dpi=120, fontsize=14)[source]
 
[Deprecated] Get the depth of a mathtext string.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
dpifloat


The dots-per-inch setting used to render the text.    Returns 
 int

Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.
parse(s, dpi=72, prop=None, *, _force_standard_ps_fonts=False)[source]
 
Parse the given math expression s at the given dpi. If prop is provided, it is a FontProperties object specifying the "default" font to use in the math expression, used for all non-math text. The results are cached, so multiple calls to parse with the same expression should be fast.
to_mask(texstr, dpi=120, fontsize=14)[source]
 
[Deprecated] Convert a mathtext string to a grayscale array and depth.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points    Returns 
 
array2D uint8 alpha


Mask array of rasterized tex.  
depthint


Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.
to_png(filename, texstr, color='black', dpi=120, fontsize=14)[source]
 
[Deprecated] Render a tex expression to a PNG file.  Parameters 
 filename

A writable filename or fileobject.  
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
colorcolor


The text color.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points.    Returns 
 int

Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.
to_rgba(texstr, color='black', dpi=120, fontsize=14)[source]
 
[Deprecated] Convert a mathtext string to an RGBA array and depth.  Parameters 
 
texstrstr


A valid mathtext string, e.g., r'IQ: $sigma_i=15$'.  
colorcolor


The text color.  
dpifloat


The dots-per-inch setting used to render the text.  
fontsizeint


The font size in points.    Returns 
 
array(M, N, 4) array


RGBA color values of rasterized tex, colorized with color.  
depthint


Offset of the baseline from the bottom of the image, in pixels.     Notes  Deprecated since version 3.4.
exceptionmatplotlib.mathtext.MathTextWarning[source]
 
Bases: Warning
matplotlib.mathtext.ship(ox, oy, box)[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
matplotlib.matplotlib_fname()[source]
 
Get the location of the config file. The file location is determined in the following order  $PWD/matplotlibrc 
$MATPLOTLIBRC if it is not a directory $MATPLOTLIBRC/matplotlibrc $MPLCONFIGDIR/matplotlibrc 
 On Linux,

 
$XDG_CONFIG_HOME/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is defined) or $HOME/.config/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is not defined)     On other platforms, - $HOME/.matplotlib/matplotlibrc if $HOME is defined Lastly, it looks in $MATPLOTLIBDATA/matplotlibrc, which should always exist.
matplotlib.mlab.angle_spectrum(x, Fs=None, window=None, pad_to=None, sides=None)
 
Compute the angle of the frequency spectrum (wrapped phase spectrum) of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.  Parameters 
 
x1-D array or sequence


Array or sequence containing the data  
Fsfloat, default: 2


The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit.  
windowcallable or ndarray, default: window_hanning


A function or a vector of length NFFT. To create window vectors see window_hanning, window_none, numpy.blackman, numpy.hamming, numpy.bartlett, scipy.signal, scipy.signal.get_window, etc. If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment.  
sides{'default', 'onesided', 'twosided'}, optional


Which sides of the spectrum to return. 'default' is one-sided for real data and two-sided for complex data. 'onesided' forces the return of a one-sided spectrum, while 'twosided' forces two-sided.  
pad_toint, optional


The number of points to which the data segment is padded when performing the FFT. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to the length of the input signal (i.e. no padding).    Returns 
 
spectrum1-D array


The angle of the frequency spectrum (wrapped phase spectrum).  
freqs1-D array


The frequencies corresponding to the elements in spectrum.      See also  psd

Returns the power spectral density.  complex_spectrum

Returns the complex-valued frequency spectrum.  magnitude_spectrum

Returns the absolute value of the complex_spectrum.  angle_spectrum

Returns the angle of the complex_spectrum.  phase_spectrum

Returns the phase (unwrapped angle) of the complex_spectrum.  specgram

Can return the complex spectrum of segments within the signal.
matplotlib.mlab.cohere(x, y, NFFT=256, Fs=2, detrend=<function detrend_none>, window=<function window_hanning>, noverlap=0, pad_to=None, sides='default', scale_by_freq=None)[source]
 
The coherence between x and y. Coherence is the normalized cross spectral density:  \[C_{xy} = \frac{|P_{xy}|^2}{P_{xx}P_{yy}}\]  Parameters 
 x, y

Array or sequence containing the data  
Fsfloat, default: 2


The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit.  
windowcallable or ndarray, default: window_hanning


A function or a vector of length NFFT. To create window vectors see window_hanning, window_none, numpy.blackman, numpy.hamming, numpy.bartlett, scipy.signal, scipy.signal.get_window, etc. If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment.  
sides{'default', 'onesided', 'twosided'}, optional


Which sides of the spectrum to return. 'default' is one-sided for real data and two-sided for complex data. 'onesided' forces the return of a one-sided spectrum, while 'twosided' forces two-sided.  
pad_toint, optional


The number of points to which the data segment is padded when performing the FFT. This can be different from NFFT, which specifies the number of data points used. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to NFFT  
NFFTint, default: 256


The number of data points used in each block for the FFT. A power 2 is most efficient. This should NOT be used to get zero padding, or the scaling of the result will be incorrect; use pad_to for this instead.  
detrend{'none', 'mean', 'linear'} or callable, default: 'none'


The function applied to each segment before fft-ing, designed to remove the mean or linear trend. Unlike in MATLAB, where the detrend parameter is a vector, in Matplotlib it is a function. The mlab module defines detrend_none, detrend_mean, and detrend_linear, but you can use a custom function as well. You can also use a string to choose one of the functions: 'none' calls detrend_none. 'mean' calls detrend_mean. 'linear' calls detrend_linear.  
scale_by_freqbool, default: True


Whether the resulting density values should be scaled by the scaling frequency, which gives density in units of Hz^-1. This allows for integration over the returned frequency values. The default is True for MATLAB compatibility.  
noverlapint, default: 0 (no overlap)


The number of points of overlap between segments.    Returns 
 
Cxy1-D array


The coherence vector.  
freqs1-D array


The frequencies for the elements in Cxy.      See also  
psd(), csd()


For information about the methods used to compute \(P_{xy}\), \(P_{xx}\) and \(P_{yy}\).
matplotlib.mlab.complex_spectrum(x, Fs=None, window=None, pad_to=None, sides=None)
 
Compute the complex-valued frequency spectrum of x. Data is padded to a length of pad_to and the windowing function window is applied to the signal.  Parameters 
 
x1-D array or sequence


Array or sequence containing the data  
Fsfloat, default: 2


The sampling frequency (samples per time unit). It is used to calculate the Fourier frequencies, freqs, in cycles per time unit.  
windowcallable or ndarray, default: window_hanning


A function or a vector of length NFFT. To create window vectors see window_hanning, window_none, numpy.blackman, numpy.hamming, numpy.bartlett, scipy.signal, scipy.signal.get_window, etc. If a function is passed as the argument, it must take a data segment as an argument and return the windowed version of the segment.  
sides{'default', 'onesided', 'twosided'}, optional


Which sides of the spectrum to return. 'default' is one-sided for real data and two-sided for complex data. 'onesided' forces the return of a one-sided spectrum, while 'twosided' forces two-sided.  
pad_toint, optional


The number of points to which the data segment is padded when performing the FFT. While not increasing the actual resolution of the spectrum (the minimum distance between resolvable peaks), this can give more points in the plot, allowing for more detail. This corresponds to the n parameter in the call to fft(). The default is None, which sets pad_to equal to the length of the input signal (i.e. no padding).    Returns 
 
spectrum1-D array


The complex-valued frequency spectrum.  
freqs1-D array


The frequencies corresponding to the elements in spectrum.      See also  psd

Returns the power spectral density.  complex_spectrum

Returns the complex-valued frequency spectrum.  magnitude_spectrum

Returns the absolute value of the complex_spectrum.  angle_spectrum

Returns the angle of the complex_spectrum.  phase_spectrum

Returns the phase (unwrapped angle) of the complex_spectrum.  specgram

Can return the complex spectrum of segments within the signal.
matplotlib.mlab.detrend(x, key=None, axis=None)[source]
 
Return x with its trend removed.  Parameters 
 
xarray or sequence


Array or sequence containing the data.  
key{'default', 'constant', 'mean', 'linear', 'none'} or function


The detrending algorithm to use. 'default', 'mean', and 'constant' are the same as detrend_mean. 'linear' is the same as detrend_linear. 'none' is the same as detrend_none. The default is 'mean'. See the corresponding functions for more details regarding the algorithms. Can also be a function that carries out the detrend operation.  
axisint


The axis along which to do the detrending.      See also  detrend_mean

Implementation of the 'mean' algorithm.  detrend_linear

Implementation of the 'linear' algorithm.  detrend_none

Implementation of the 'none' algorithm.
matplotlib.mlab.detrend_linear(y)[source]
 
Return x minus best fit line; 'linear' detrending.  Parameters 
 
y0-D or 1-D array or sequence


Array or sequence containing the data      See also  detrend_mean

Another detrend algorithm.  detrend_none

Another detrend algorithm.  detrend

A wrapper around all the detrend algorithms.
matplotlib.mlab.detrend_mean(x, axis=None)[source]
 
Return x minus the mean(x).  Parameters 
 
xarray or sequence


Array or sequence containing the data Can have any dimensionality  
axisint


The axis along which to take the mean. See numpy.mean for a description of this argument.      See also  detrend_linear

Another detrend algorithm.  detrend_none

Another detrend algorithm.  detrend

A wrapper around all the detrend algorithms.
matplotlib.mlab.detrend_none(x, axis=None)[source]
 
Return x: no detrending.  Parameters 
 
xany object


An object containing the data  
axisint


This parameter is ignored. It is included for compatibility with detrend_mean      See also  detrend_mean

Another detrend algorithm.  detrend_linear

Another detrend algorithm.  detrend

A wrapper around all the detrend algorithms.
classmatplotlib.mlab.GaussianKDE(dataset, bw_method=None)[source]
 
Bases: object Representation of a kernel-density estimate using Gaussian kernels.  Parameters 
 
datasetarray-like


Datapoints to estimate from. In case of univariate data this is a 1-D array, otherwise a 2D array with shape (# of dims, # of data).  
bw_methodstr, scalar or callable, optional


The method used to calculate the estimator bandwidth. This can be 'scott', 'silverman', a scalar constant or a callable. If a scalar, this will be used directly as kde.factor. If a callable, it should take a GaussianKDE instance as only parameter and return a scalar. If None (default), 'scott' is used.    Attributes 
 
datasetndarray


The dataset with which gaussian_kde was initialized.  
dimint


Number of dimensions.  
num_dpint


Number of datapoints.  
factorfloat


The bandwidth factor, obtained from kde.covariance_factor, with which the covariance matrix is multiplied.  
covariancendarray


The covariance matrix of dataset, scaled by the calculated bandwidth (kde.factor).  
inv_covndarray


The inverse of covariance.     Methods  
kde.evaluate(points) (ndarray) Evaluate the estimated pdf on a provided set of points.  
kde(points) (ndarray) Same as kde.evaluate(points)     covariance_factor()[source]

   evaluate(points)[source]
 
Evaluate the estimated pdf on a set of points.  Parameters 
 
points(# of dimensions, # of points)-array


Alternatively, a (# of dimensions,) vector can be passed in and treated as a single point.    Returns 
 (# of points,)-array

The values at each point.    Raises 
 
ValueErrorif the dimensionality of the input points is different


than the dimensionality of the KDE.     
   scotts_factor()[source]

   silverman_factor()[source]
evaluate(points)[source]
 
Evaluate the estimated pdf on a set of points.  Parameters 
 
points(# of dimensions, # of points)-array


Alternatively, a (# of dimensions,) vector can be passed in and treated as a single point.    Returns 
 (# of points,)-array

The values at each point.    Raises 
 
ValueErrorif the dimensionality of the input points is different


than the dimensionality of the KDE.