neulab/docprompting-conala huggingface dataset:
classmatplotlib.scale.LogitScale(axis, nonpositive='mask', *, one_half='\x0crac{1}{2}', use_overline=False)[source]
 
Bases: matplotlib.scale.ScaleBase Logit scale for data between zero and one, both excluded. This scale is similar to a log scale close to zero and to one, and almost linear around 0.5. It maps the interval ]0, 1[ onto ]-infty, +infty[.  Parameters 
 
axismatplotlib.axis.Axis


Currently unused.  
nonpositive{'mask', 'clip'}


Determines the behavior for values beyond the open interval ]0, 1[. They can either be masked as invalid, or clipped to a number very close to 0 or 1.  
use_overlinebool, default: False


Indicate the usage of survival notation (overline{x}) in place of standard notation (1-x) for probability close to one.  
one_halfstr, default: r"frac{1}{2}"


The string used for ticks formatter to represent 1/2.       get_transform()[source]
 
Return the LogitTransform associated with this scale. 
   limit_range_for_scale(vmin, vmax, minpos)[source]
 
Limit the domain to values between 0 and 1 (excluded). 
   name='logit'

   set_default_locators_and_formatters(axis)[source]
 
Set the locators and formatters of axis to instances suitable for this scale.
limit_range_for_scale(vmin, vmax, minpos)[source]
 
Limit the domain to values between 0 and 1 (excluded).
classmatplotlib.scale.LogitTransform(nonpositive='mask')[source]
 
Bases: matplotlib.transforms.Transform  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=1
 
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. 
   is_separable=True
 
True if this transform is separable in the x- and y- dimensions. 
   output_dims=1
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(a)[source]
 
logit transform (base 10), masked or clipped
transform_non_affine(a)[source]
 
logit transform (base 10), masked or clipped
classmatplotlib.scale.LogScale(axis, *, base=10, subs=None, nonpositive='clip')[source]
 
Bases: matplotlib.scale.ScaleBase A standard logarithmic scale. Care is taken to only plot positive values.  Parameters 
 
axisAxis


The axis for the scale.  
basefloat, default: 10


The base of the logarithm.  
nonpositive{'clip', 'mask'}, default: 'clip'


Determines the behavior for non-positive values. They can either be masked as invalid, or clipped to a very small positive number.  
subssequence of int, default: None


Where to place the subticks between each major tick. For example, in a log10 scale, [2, 3, 4, 5, 6, 7, 8, 9] will place 8 logarithmically spaced minor ticks between each major tick.       propertybase

   get_transform()[source]
 
Return the LogTransform associated with this scale. 
   limit_range_for_scale(vmin, vmax, minpos)[source]
 
Limit the domain to positive values. 
   name='log'

   set_default_locators_and_formatters(axis)[source]
 
Set the locators and formatters of axis to instances suitable for this scale.
limit_range_for_scale(vmin, vmax, minpos)[source]
 
Limit the domain to positive values.
classmatplotlib.scale.LogTransform(base, nonpositive='clip')[source]
 
Bases: matplotlib.transforms.Transform  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=1
 
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. 
   is_separable=True
 
True if this transform is separable in the x- and y- dimensions. 
   output_dims=1
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(a)[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.scale.register_scale(scale_class)[source]
 
Register a new kind of scale.  Parameters 
 
scale_classsubclass of ScaleBase


The scale to register.
matplotlib.scale.scale_factory(scale, axis, **kwargs)[source]
 
Return a scale class by name.  Parameters 
 
scale{'function', 'functionlog', 'linear', 'log', 'logit', 'symlog'}


axismatplotlib.axis.Axis
classmatplotlib.scale.ScaleBase(axis)[source]
 
Bases: object The base class for all scales. Scales are separable transformations, working on a single dimension. Subclasses should override  name

The scale's name.  get_transform()

A method returning a Transform, which converts data coordinates to scaled coordinates. This transform should be invertible, so that e.g. mouse positions can be converted back to data coordinates.  set_default_locators_and_formatters()

A method that sets default locators and formatters for an Axis that uses this scale.  limit_range_for_scale()

An optional method that "fixes" the axis range to acceptable values, e.g. restricting log-scaled axes to positive values.   Construct a new scale. Notes The following note is for scale implementors. For back-compatibility reasons, scales take an Axis object as first argument. However, this argument should not be used: a single scale object should be usable by multiple Axises at the same time.   get_transform()[source]
 
Return the Transform object associated with this scale. 
   limit_range_for_scale(vmin, vmax, minpos)[source]
 
Return the range vmin, vmax, restricted to the domain supported by this scale (if any). minpos should be the minimum positive value in the data. This is used by log scales to determine a minimum value. 
   set_default_locators_and_formatters(axis)[source]
 
Set the locators and formatters of axis to instances suitable for this scale.
limit_range_for_scale(vmin, vmax, minpos)[source]
 
Return the range vmin, vmax, restricted to the domain supported by this scale (if any). minpos should be the minimum positive value in the data. This is used by log scales to determine a minimum value.
classmatplotlib.scale.SymmetricalLogScale(axis, *, base=10, linthresh=2, subs=None, linscale=1)[source]
 
Bases: matplotlib.scale.ScaleBase The symmetrical logarithmic scale is logarithmic in both the positive and negative directions from the origin. Since the values close to zero tend toward infinity, there is a need to have a range around zero that is linear. The parameter linthresh allows the user to specify the size of this range (-linthresh, linthresh).  Parameters 
 
basefloat, default: 10


The base of the logarithm.  
linthreshfloat, default: 2


Defines the range (-x, x), within which the plot is linear. This avoids having the plot go to infinity around zero.  
subssequence of int


Where to place the subticks between each major tick. For example, in a log10 scale: [2, 3, 4, 5, 6, 7, 8, 9] will place 8 logarithmically spaced minor ticks between each major tick.  
linscalefloat, optional


This allows the linear range (-linthresh, linthresh) to be stretched relative to the logarithmic range. Its value is the number of decades to use for each half of the linear range. For example, when linscale == 1.0 (the default), the space used for the positive and negative halves of the linear range will be equal to one decade in the logarithmic range.     Construct a new scale. Notes The following note is for scale implementors. For back-compatibility reasons, scales take an Axis object as first argument. However, this argument should not be used: a single scale object should be usable by multiple Axises at the same time.   propertybase

   get_transform()[source]
 
Return the SymmetricalLogTransform associated with this scale. 
   propertylinscale

   propertylinthresh

   name='symlog'

   set_default_locators_and_formatters(axis)[source]
 
Set the locators and formatters of axis to instances suitable for this scale.
get_transform()[source]
 
Return the SymmetricalLogTransform associated with this scale.
classmatplotlib.scale.SymmetricalLogTransform(base, linthresh, linscale)[source]
 
Bases: matplotlib.transforms.Transform  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=1
 
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. 
   is_separable=True
 
True if this transform is separable in the x- and y- dimensions. 
   output_dims=1
 
The number of output dimensions of this transform. Must be overridden (with integers) in the subclass. 
   transform_non_affine(a)[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.set_loglevel(level)[source]
 
Set Matplotlib's root logger and root logger handler level, creating the handler if it does not exist yet. Typically, one should call set_loglevel("info") or set_loglevel("debug") to get additional debugging information.  Parameters 
 
level{"notset", "debug", "info", "warning", "error", "critical"}


The log level of the handler.     Notes The first time this function is called, an additional handler is attached to Matplotlib's root handler; this handler is reused every time and this function simply manipulates the logger and handler's level.
matplotlib.sphinxext.mathmpl  A role and directive to display mathtext in Sphinx  Warning In most cases, you will likely want to use one of Sphinx's builtin Math extensions instead of this one.  Mathtext may be included in two ways:  
Inline, using the role: This text uses inline math: :mathmpl:`\alpha > \beta`.
 which produces: This text uses inline math: .  
Standalone, using the directive: Here is some standalone math:

.. mathmpl::

    \alpha > \beta
 which produces: Here is some standalone math:     Options The mathmpl role and directive both support the following options:  fontsetstr, default: 'cm'


The font set to use when displaying math. See rcParams["mathtext.fontset"] (default: 'dejavusans').  fontsizefloat


The font size, in points. Defaults to the value from the extension configuration option defined below.     Configuration options The mathtext extension has the following configuration options:  mathmpl_fontsizefloat, default: 10.0


Default font size, in points.  mathmpl_srcsetlist of str, default: []


Additional image sizes to generate when embedding in HTML, to support responsive resolution images. The list should contain additional x-descriptors ('1.5x', '2x', etc.) to generate (1x is the default and always included.)     classmatplotlib.sphinxext.mathmpl.MathDirective(name, arguments, options, content, lineno, content_offset, block_text, state, state_machine)[source]
 
The .. mathmpl:: directive, as documented in the module's docstring.
classmatplotlib.sphinxext.mathmpl.MathDirective(name, arguments, options, content, lineno, content_offset, block_text, state, state_machine)[source]
 
The .. mathmpl:: directive, as documented in the module's docstring.
matplotlib.sphinxext.plot_directive.mark_plot_labels(app, document)[source]
 
To make plots referenceable, we need to move the reference from the "htmlonly" (or "latexonly") node to the actual figure node itself.
matplotlib.sphinxext.plot_directive.out_of_date(original, derived, includes=None)[source]
 
Return whether derived is out-of-date relative to original or any of the RST files included in it using the RST include directive (includes). derived and original are full paths, and includes is optionally a list of full paths which may have been included in the original.
classmatplotlib.sphinxext.plot_directive.PlotDirective(name, arguments, options, content, lineno, content_offset, block_text, state, state_machine)[source]
 
The .. plot:: directive, as documented in the module's docstring.   run()[source]
 
Run the plot directive.
matplotlib.sphinxext.plot_directive.render_figures(code, code_path, output_dir, output_base, context, function_name, config, context_reset=False, close_figs=False, code_includes=None)[source]
 
Run a pyplot script and save the images in output_dir. Save the images under output_dir with file names derived from output_base
matplotlib.sphinxext.plot_directive.run_code(code, code_path, ns=None, function_name=None)[source]
 
[Deprecated] Import a Python module from a path, and run the function given by name, if function_name is not None. Notes  Deprecated since version 3.5.
matplotlib.sphinxext.plot_directive.split_code_at_show(text)[source]
 
[Deprecated] Split code at plt.show(). Notes  Deprecated since version 3.5.
matplotlib.sphinxext.plot_directive.unescape_doctest(text)[source]
 
[Deprecated] Extract code from a piece of text, which contains either Python code or doctests. Notes  Deprecated since version 3.5.
classmethodarc_spine(axes, spine_type, center, radius, theta1, theta2, **kwargs)[source]
 
Create and return an arc Spine.
classmethodcircular_spine(axes, center, radius, **kwargs)[source]
 
Create and return a circular Spine.
get_window_extent(renderer=None)[source]
 
Return the window extent of the spines in display space, including padding for ticks (but not their labels)  See also  matplotlib.axes.Axes.get_tightbbox
matplotlib.axes.Axes.get_window_extent
classmethodlinear_spine(axes, spine_type, **kwargs)[source]
 
Create and return a linear Spine.
register_axis(axis)[source]
 
Register an axis. An axis should be registered with its corresponding spine from the Axes instance. This allows the spine to clear any axis properties when needed.
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, antialiased=<UNSET>, bounds=<UNSET>, capstyle=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, color=<UNSET>, edgecolor=<UNSET>, facecolor=<UNSET>, fill=<UNSET>, gid=<UNSET>, hatch=<UNSET>, in_layout=<UNSET>, joinstyle=<UNSET>, label=<UNSET>, linestyle=<UNSET>, linewidth=<UNSET>, patch_arc=<UNSET>, patch_circle=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, position=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, zorder=<UNSET>)[source]
 
Set multiple properties at once. Supported properties are   
Property Description   
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  
animated bool  
antialiased or aa bool or None  
bounds (low: float, high: float)  
capstyle CapStyle or {'butt', 'projecting', 'round'}  
clip_box Bbox  
clip_on bool  
clip_path Patch or (Path, Transform) or None  
color color  
edgecolor or ec color or None  
facecolor or fc color or None  
figure Figure  
fill bool  
gid str  
hatch {'/', '\', '|', '-', '+', 'x', 'o', 'O', '.', '*'}  
in_layout bool  
joinstyle JoinStyle or {'miter', 'round', 'bevel'}  
label object  
linestyle or ls {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}  
linewidth or lw float or None  
patch_arc unknown  
patch_circle unknown  
path_effects AbstractPathEffect  
picker None or bool or float or callable  
position unknown  
rasterized bool  
sketch_params (scale: float, length: float, randomness: float)  
snap bool or None  
transform Transform  
url str  
visible bool  
zorder float
set_bounds(low=None, high=None)[source]
 
Set the spine bounds.  Parameters 
 
lowfloat or None, optional


The lower spine bound. Passing None leaves the limit unchanged. The bounds may also be passed as the tuple (low, high) as the first positional argument.  
highfloat or None, optional


The higher spine bound. Passing None leaves the limit unchanged.
set_color(c)[source]
 
Set the edgecolor.  Parameters 
 
ccolor

   Notes This method does not modify the facecolor (which defaults to "none"), unlike the Patch.set_color method defined in the parent class. Use Patch.set_facecolor to set the facecolor.
set_patch_arc(center, radius, theta1, theta2)[source]
 
Set the spine to be arc-like.
set_patch_circle(center, radius)[source]
 
Set the spine to be circular.
set_position(position)[source]
 
Set the position of the spine. Spine position is specified by a 2 tuple of (position type, amount). The position types are:  'outward': place the spine out from the data area by the specified number of points. (Negative values place the spine inwards.) 'axes': place the spine at the specified Axes coordinate (0 to 1). 'data': place the spine at the specified data coordinate.  Additionally, shorthand notations define a special positions:  'center' -> ('axes', 0.5) 'zero' -> ('data', 0.0)
classmatplotlib.spines.Spines(**kwargs)[source]
 
Bases: collections.abc.MutableMapping The container of all Spines in an Axes. The interface is dict-like mapping names (e.g. 'left') to Spine objects. Additionally it implements some pandas.Series-like features like accessing elements by attribute: spines['top'].set_visible(False)
spines.top.set_visible(False)
 Multiple spines can be addressed simultaneously by passing a list: spines[['top', 'right']].set_visible(False)
 Use an open slice to address all spines: spines[:].set_visible(False)
 The latter two indexing methods will return a SpinesProxy that broadcasts all set_* calls to its members, but cannot be used for any other operation.   classmethodfrom_dict(d)[source]
classmatplotlib.spines.SpinesProxy(spine_dict)[source]
 
Bases: object A proxy to broadcast set_* method calls to all contained Spines. The proxy cannot be used for any other operations on its members. The supported methods are determined dynamically based on the contained spines. If not all spines support a given method, it's executed only on the subset of spines that support it.
matplotlib.style Styles are predefined sets of rcParams that define the visual appearance of a plot. Customizing Matplotlib with style sheets and rcParams describes the mechanism and usage of styles. The Style sheets reference gives an overview of the builtin styles.   matplotlib.style.context(style, after_reset=False)
 
Context manager for using style settings temporarily.  Parameters 
 
stylestr, dict, Path or list


A style specification. Valid options are:  
str The name of a style or a path/URL to a style file. For a list of available style names, see style.available.  
dict Dictionary with valid key/value pairs for matplotlib.rcParams.  
Path A path-like object which is a path to a style file.  
list A list of style specifiers (str, Path or dict) applied from first to last in the list.    
after_resetbool


If True, apply style after resetting settings to their defaults; otherwise, apply style on top of the current settings.     
   matplotlib.style.reload_library()[source]
 
Reload the style library. 
   matplotlib.style.use(style)[source]
 
Use Matplotlib style settings from a style specification. The style name of 'default' is reserved for reverting back to the default style settings.  Note This updates the rcParams with the settings from the style. rcParams not defined in the style are kept.   Parameters 
 
stylestr, dict, Path or list


A style specification. Valid options are:  
str The name of a style or a path/URL to a style file. For a list of available style names, see style.available.  
dict Dictionary with valid key/value pairs for matplotlib.rcParams.  
Path A path-like object which is a path to a style file.  
list A list of style specifiers (str, Path or dict) applied from first to last in the list.       Notes The following rcParams are not related to style and will be ignored if found in a style specification:  backend backend_fallback datapath date.epoch docstring.hardcopy figure.max_open_warning figure.raise_window interactive savefig.directory timezone tk.window_focus toolbar webagg.address webagg.open_in_browser webagg.port webagg.port_retries  
   matplotlib.style.library
 
A dict mapping from style name to RcParams defining that style. This is meant to be read-only. Use reload_library to update. 
   matplotlib.style.available
 
List of the names of the available styles. This is meant to be read-only. Use reload_library to update.
matplotlib.style.context(style, after_reset=False)
 
Context manager for using style settings temporarily.  Parameters 
 
stylestr, dict, Path or list


A style specification. Valid options are:  
str The name of a style or a path/URL to a style file. For a list of available style names, see style.available.  
dict Dictionary with valid key/value pairs for matplotlib.rcParams.  
Path A path-like object which is a path to a style file.  
list A list of style specifiers (str, Path or dict) applied from first to last in the list.    
after_resetbool


If True, apply style after resetting settings to their defaults; otherwise, apply style on top of the current settings.
matplotlib.style.available
 
List of the names of the available styles. This is meant to be read-only. Use reload_library to update.
matplotlib.style.library
 
A dict mapping from style name to RcParams defining that style. This is meant to be read-only. Use reload_library to update.
matplotlib.style.use(style)[source]
 
Use Matplotlib style settings from a style specification. The style name of 'default' is reserved for reverting back to the default style settings.  Note This updates the rcParams with the settings from the style. rcParams not defined in the style are kept.   Parameters 
 
stylestr, dict, Path or list


A style specification. Valid options are:  
str The name of a style or a path/URL to a style file. For a list of available style names, see style.available.  
dict Dictionary with valid key/value pairs for matplotlib.rcParams.  
Path A path-like object which is a path to a style file.  
list A list of style specifiers (str, Path or dict) applied from first to last in the list.       Notes The following rcParams are not related to style and will be ignored if found in a style specification:  backend backend_fallback datapath date.epoch docstring.hardcopy figure.max_open_warning figure.raise_window interactive savefig.directory timezone tk.window_focus toolbar webagg.address webagg.open_in_browser webagg.port webagg.port_retries
auto_set_font_size(renderer)[source]
 
Shrink font size until the text fits into the cell width.
get_required_width(renderer)[source]
 
Return the minimal required width for the cell.
get_text_bounds(renderer)[source]
 
Return the text bounds as (x, y, width, height) in table coordinates.