neulab/docprompting-conala huggingface dataset:
classInvertedLambertTransform(center_longitude, center_latitude, resolution)[source]
 
Bases: matplotlib.projections.geo._GeoTransform Create a new geographical transform. Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.   has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   transform_non_affine(xy)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
classLambertTransform(center_longitude, center_latitude, resolution)[source]
 
Bases: matplotlib.projections.geo._GeoTransform The base Lambert transform. Create a new Lambert transform. Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved Lambert space.   has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   transform_non_affine(ll)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
classInvertedMollweideTransform(resolution)[source]
 
Bases: matplotlib.projections.geo._GeoTransform Create a new geographical transform. Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.   has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   transform_non_affine(xy)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
classMollweideTransform(resolution)[source]
 
Bases: matplotlib.projections.geo._GeoTransform The base Mollweide transform. Create a new geographical transform. Resolution is the number of steps to interpolate between each input line segment to approximate its path in curved space.   has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   transform_non_affine(ll)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
matplotlib.projections.get_projection_class(projection=None)[source]
 
Get a projection class from its name. If projection is None, a standard rectilinear projection is returned.
matplotlib.projections.get_projection_names()[source]
 
Return the names of all projections currently registered.
classmatplotlib.projections.polar.InvertedPolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)[source]
 
Bases: matplotlib.transforms.Transform The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.  Parameters 
 
shorthand_namestr


A string representing the "name" of the transform. The name carries no significance other than to improve the readability of str(transform) when DEBUG=True.       has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   input_dims=2
 
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   output_dims=2
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(xy)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
input_dims=2
 
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass.
output_dims=2
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass.
classmatplotlib.projections.polar.PolarAffine(scale_transform, limits)[source]
 
Bases: matplotlib.transforms.Affine2DBase The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle. limits is the view limit of the data. The only part of its bounds that is used is the y limits (for the radius limits). The theta range is handled by the non-affine transform.   get_matrix()[source]
 
Get the matrix for the affine part of this transform.
get_matrix()[source]
 
Get the matrix for the affine part of this transform.
can_pan()[source]
 
Return whether this axes supports the pan/zoom button functionality. For polar axes, this is slightly misleading. Both panning and zooming are performed by the same button. Panning is performed in azimuth while zooming is done along the radial.
can_zoom()[source]
 
Return whether this axes supports the zoom box button functionality. Polar axes do not support zoom boxes.
format_coord(theta, r)[source]
 
Return a format string formatting the x, y coordinates.
get_data_ratio()[source]
 
Return the aspect ratio of the data itself. For a polar plot, this should always be 1.0
get_rlabel_position()[source]
 
 Returns 
 float

The theta position of the radius labels in degrees.
get_rmax()[source]
 
 Returns 
 float

Outer radial limit.
get_rmin()[source]
 
 Returns 
 float

The inner radial limit.
get_theta_direction()[source]
 
Get the direction in which theta increases.  -1:

Theta increases in the clockwise direction  1:

Theta increases in the counterclockwise direction
get_theta_offset()[source]
 
Get the offset for the location of 0 in radians.
classInvertedPolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)[source]
 
Bases: matplotlib.transforms.Transform The inverse of the polar transform, mapping Cartesian coordinate space x and y back to theta and r.  Parameters 
 
shorthand_namestr


A string representing the "name" of the transform. The name carries no significance other than to improve the readability of str(transform) when DEBUG=True.       has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   input_dims=2
 
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   output_dims=2
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(xy)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
classPolarAffine(scale_transform, limits)[source]
 
Bases: matplotlib.transforms.Affine2DBase The affine part of the polar projection. Scales the output so that maximum radius rests on the edge of the axes circle. limits is the view limit of the data. The only part of its bounds that is used is the y limits (for the radius limits). The theta range is handled by the non-affine transform.   get_matrix()[source]
 
Get the matrix for the affine part of this transform.
classPolarTransform(axis=None, use_rmin=True, _apply_theta_transforms=True)[source]
 
Bases: matplotlib.transforms.Transform The base polar transform. This handles projection theta and r into Cartesian coordinate space x and y, but does not perform the ultimate affine transformation into the correct position.  Parameters 
 
shorthand_namestr


A string representing the "name" of the transform. The name carries no significance other than to improve the readability of str(transform) when DEBUG=True.       has_inverse=True
 
True if this transform has a corresponding inverse transform. 
   input_dims=2
 
The number of input dimensions of this transform. Must be overridden (with integers) in the subclass. 
   inverted()[source]
 
Return the corresponding inverse transformation. It holds x == self.inverted().transform(self.transform(x)). The return value of this method should be treated as temporary. An update to self does not cause a corresponding update to its inverted copy. 
   output_dims=2
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(tr)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.     
   transform_path_non_affine(path)[source]
 
Apply the non-affine part of this transform to Path path, returning a new Path. transform_path(path) is equivalent to transform_path_affine(transform_path_non_affine(values)).
transform_non_affine(tr)[source]
 
Apply only the non-affine part of this transformation. transform(values) is always equivalent to transform_affine(transform_non_affine(values)). In non-affine transformations, this is generally equivalent to transform(values). In affine transformations, this is always a no-op.  Parameters 
 
valuesarray


The input values as NumPy array of length input_dims or shape (N x input_dims).    Returns 
 array

The output values as NumPy array of length input_dims or shape (N x output_dims), depending on the input.
transform_path_non_affine(path)[source]
 
Apply the non-affine part of this transform to Path path, returning a new Path. transform_path(path) is equivalent to transform_path_affine(transform_path_non_affine(values)).
classRadialLocator(base, axes=None)[source]
 
Bases: matplotlib.ticker.Locator Used to locate radius ticks. Ensures that all ticks are strictly positive. For all other tasks, it delegates to the base Locator (which may be different depending on the scale of the r-axis).   nonsingular(vmin, vmax)[source]
 
Adjust a range as needed to avoid singularities. This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not.  If v0 == v1 (possibly up to some floating point slop), this method returns an expanded interval around this value. If (v0, v1) == (-inf, +inf), this method returns appropriate default view limits. Otherwise, (v0, v1) is returned without modification.  
   set_axis(axis)[source]

   view_limits(vmin, vmax)[source]
 
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.
nonsingular(vmin, vmax)[source]
 
Adjust a range as needed to avoid singularities. This method gets called during autoscaling, with (v0, v1) set to the data limits on the axes if the axes contains any data, or (-inf, +inf) if not.  If v0 == v1 (possibly up to some floating point slop), this method returns an expanded interval around this value. If (v0, v1) == (-inf, +inf), this method returns appropriate default view limits. Otherwise, (v0, v1) is returned without modification.
view_limits(vmin, vmax)[source]
 
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.
set(*, adjustable=<UNSET>, agg_filter=<UNSET>, alpha=<UNSET>, anchor=<UNSET>, animated=<UNSET>, aspect=<UNSET>, autoscale_on=<UNSET>, autoscalex_on=<UNSET>, autoscaley_on=<UNSET>, axes_locator=<UNSET>, axisbelow=<UNSET>, box_aspect=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, facecolor=<UNSET>, frame_on=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, label=<UNSET>, navigate=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, prop_cycle=<UNSET>, rasterization_zorder=<UNSET>, rasterized=<UNSET>, rgrids=<UNSET>, rlabel_position=<UNSET>, rlim=<UNSET>, rmax=<UNSET>, rmin=<UNSET>, rorigin=<UNSET>, rscale=<UNSET>, rticks=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, theta_direction=<UNSET>, theta_offset=<UNSET>, theta_zero_location=<UNSET>, thetagrids=<UNSET>, thetalim=<UNSET>, thetamax=<UNSET>, thetamin=<UNSET>, title=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, xbound=<UNSET>, xlabel=<UNSET>, xlim=<UNSET>, xmargin=<UNSET>, xscale=<UNSET>, xticklabels=<UNSET>, xticks=<UNSET>, ybound=<UNSET>, ylabel=<UNSET>, ylim=<UNSET>, ymargin=<UNSET>, yscale=<UNSET>, yticklabels=<UNSET>, yticks=<UNSET>, zorder=<UNSET>)[source]
 
Set multiple properties at once. Supported properties are   
Property Description   
adjustable {'box', 'datalim'}  
agg_filter a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array  
alpha scalar or None  
anchor (float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', ...}  
animated bool  
aspect {'auto', 'equal'} or float  
autoscale_on bool  
autoscalex_on bool  
autoscaley_on bool  
axes_locator Callable[[Axes, Renderer], Bbox]  
axisbelow bool or 'line'  
box_aspect float or None  
clip_box Bbox  
clip_on bool  
clip_path Patch or (Path, Transform) or None  
facecolor or fc color  
figure Figure  
frame_on bool  
gid str  
in_layout bool  
label object  
navigate bool  
navigate_mode unknown  
path_effects AbstractPathEffect  
picker None or bool or float or callable  
position [left, bottom, width, height] or Bbox  
prop_cycle unknown  
rasterization_zorder float or None  
rasterized bool  
rgrids tuple with floats  
rlabel_position number  
rlim unknown  
rmax float  
rmin float  
rorigin float  
rscale unknown  
rticks unknown  
sketch_params (scale: float, length: float, randomness: float)  
snap bool or None  
theta_direction unknown  
theta_offset unknown  
theta_zero_location str  
thetagrids tuple with floats, degrees  
thetalim unknown  
thetamax unknown  
thetamin unknown  
title str  
transform Transform  
url str  
visible bool  
xbound unknown  
xlabel str  
xlim (bottom: float, top: float)  
xmargin float greater than -0.5  
xscale {"linear", "log", "symlog", "logit", ...} or ScaleBase  
xticklabels unknown  
xticks unknown  
ybound unknown  
ylabel str  
ylim float, optional  
ymargin float greater than -0.5  
yscale unknown  
yticklabels unknown  
yticks unknown  
zorder float
set_rgrids(radii, labels=None, angle=None, fmt=None, **kwargs)[source]
 
Set the radial gridlines on a polar plot.  Parameters 
 
radiituple with floats


The radii for the radial gridlines  
labelstuple with strings or None


The labels to use at each radial gridline. The matplotlib.ticker.ScalarFormatter will be used if None.  
anglefloat


The angular position of the radius labels in degrees.  
fmtstr or None


Format string used in matplotlib.ticker.FormatStrFormatter. For example '%f'.    Returns 
 
lineslist of lines.Line2D


The radial gridlines.  
labelslist of text.Text


The tick labels.    Other Parameters 
 **kwargs

kwargs are optional Text properties for the labels.      See also  PolarAxes.set_thetagrids
Axis.get_gridlines
Axis.get_ticklabels
set_rlabel_position(value)[source]
 
Update the theta position of the radius labels.  Parameters 
 
valuenumber


The angular position of the radius labels in degrees.
set_rlim(bottom=None, top=None, emit=True, auto=False, **kwargs)[source]
 
See set_ylim.
set_rmax(rmax)[source]
 
Set the outer radial limit.  Parameters 
 
rmaxfloat
set_rmin(rmin)[source]
 
Set the inner radial limit.  Parameters 
 
rminfloat
set_rorigin(rorigin)[source]
 
Update the radial origin.  Parameters 
 
roriginfloat
set_theta_direction(direction)[source]
 
Set the direction in which theta increases.  clockwise, -1:

Theta increases in the clockwise direction  counterclockwise, anticlockwise, 1:

Theta increases in the counterclockwise direction
set_theta_offset(offset)[source]
 
Set the offset for the location of 0 in radians.
set_theta_zero_location(loc, offset=0.0)[source]
 
Set the location of theta's zero. This simply calls set_theta_offset with the correct value in radians.  Parameters 
 
locstr


May be one of "N", "NW", "W", "SW", "S", "SE", "E", or "NE".  
offsetfloat, default: 0


An offset in degrees to apply from the specified loc. Note: this offset is always applied counter-clockwise regardless of the direction setting.
set_thetagrids(angles, labels=None, fmt=None, **kwargs)[source]
 
Set the theta gridlines in a polar plot.  Parameters 
 
anglestuple with floats, degrees


The angles of the theta gridlines.  
labelstuple with strings or None


The labels to use at each theta gridline. The projections.polar.ThetaFormatter will be used if None.  
fmtstr or None


Format string used in matplotlib.ticker.FormatStrFormatter. For example '%f'. Note that the angle that is used is in radians.    Returns 
 
lineslist of lines.Line2D


The theta gridlines.  
labelslist of text.Text


The tick labels.    Other Parameters 
 **kwargs

kwargs are optional Text properties for the labels.      See also  PolarAxes.set_rgrids
Axis.get_gridlines
Axis.get_ticklabels
set_thetalim(*args, **kwargs)[source]
 
Set the minimum and maximum theta values. Can take the following signatures:  
set_thetalim(minval, maxval): Set the limits in radians. 
set_thetalim(thetamin=minval, thetamax=maxval): Set the limits in degrees.  where minval and maxval are the minimum and maximum limits. Values are wrapped in to the range \([0, 2\pi]\) (in radians), so for example it is possible to do set_thetalim(-np.pi / 2, np.pi / 2) to have an axes symmetric around 0. A ValueError is raised if the absolute angle difference is larger than a full circle.
set_thetamax(thetamax)[source]
 
Set the maximum theta limit in degrees.
set_thetamin(thetamin)[source]
 
Set the minimum theta limit in degrees.
set_ylim(bottom=None, top=None, emit=True, auto=False, *, ymin=None, ymax=None)[source]
 
Set the data limits for the radial axis.  Parameters 
 
bottomfloat, optional


The bottom limit (default: None, which leaves the bottom limit unchanged). The bottom and top ylims may be passed as the tuple (bottom, top) as the first positional argument (or as the bottom keyword argument).  
topfloat, optional


The top limit (default: None, which leaves the top limit unchanged).  
emitbool, default: True


Whether to notify observers of limit change.  
autobool or None, default: False


Whether to turn on autoscaling of the y-axis. True turns on, False turns off, None leaves unchanged.  
ymin, ymaxfloat, optional


These arguments are deprecated and will be removed in a future version. They are equivalent to bottom and top respectively, and it is an error to pass both ymin and bottom or ymax and top.    Returns 
 
bottom, top(float, float)


The new y-axis limits in data coordinates.
classThetaFormatter[source]
 
Bases: matplotlib.ticker.Formatter Used to format the theta tick labels. Converts the native unit of radians into degrees and adds a degree symbol.
classThetaLocator(base)[source]
 
Bases: matplotlib.ticker.Locator Used to locate theta ticks. This will work the same as the base locator except in the case that the view spans the entire circle. In such cases, the previously used default locations of every 45 degrees are returned.   refresh()[source]

   set_axis(axis)[source]

   view_limits(vmin, vmax)[source]
 
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.