neulab/docprompting-conala huggingface dataset:
classmatplotlib.ticker.MaxNLocator(nbins=None, **kwargs)[source]
 
Bases: matplotlib.ticker.Locator Find nice tick locations with no more than N being within the view limits. Locations beyond the limits are added to support autoscaling.  Parameters 
 
nbinsint or 'auto', default: 10


Maximum number of intervals; one less than max number of ticks. If the string 'auto', the number of bins will be automatically determined based on the length of the axis.  
stepsarray-like, optional


Sequence of nice numbers starting with 1 and ending with 10; e.g., [1, 2, 4, 5, 10], where the values are acceptable tick multiples. i.e. for the example, 20, 40, 60 would be an acceptable set of ticks, as would 0.4, 0.6, 0.8, because they are multiples of 2. However, 30, 60, 90 would not be allowed because 3 does not appear in the list of steps.  
integerbool, default: False


If True, ticks will take only integer values, provided at least min_n_ticks integers are found within the view limits.  
symmetricbool, default: False


If True, autoscaling will result in a range symmetric about zero.  
prune{'lower', 'upper', 'both', None}, default: None


Remove edge ticks -- useful for stacked or ganged plots where the upper tick of one axes overlaps with the lower tick of the axes above it, primarily when rcParams["axes.autolimit_mode"] (default: 'data') is 'round_numbers'. If prune=='lower', the smallest tick will be removed. If prune == 'upper', the largest tick will be removed. If prune == 'both', the largest and smallest ticks will be removed. If prune is None, no ticks will be removed.  
min_n_ticksint, default: 2


Relax nbins and integer constraints if necessary to obtain this minimum number of ticks.       default_params={'integer': False, 'min_n_ticks': 2, 'nbins': 10, 'prune': None, 'steps': None, 'symmetric': False}

   set_params(**kwargs)[source]
 
Set parameters for this locator.  Parameters 
 
nbinsint or 'auto', optional


see MaxNLocator  
stepsarray-like, optional


see MaxNLocator  
integerbool, optional


see MaxNLocator  
symmetricbool, optional


see MaxNLocator  
prune{'lower', 'upper', 'both', None}, optional


see MaxNLocator  
min_n_ticksint, optional


see MaxNLocator     
   tick_values(vmin, vmax)[source]
 
Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
  
   view_limits(dmin, dmax)[source]
 
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.
default_params={'integer': False, 'min_n_ticks': 2, 'nbins': 10, 'prune': None, 'steps': None, 'symmetric': False}
set_params(**kwargs)[source]
 
Set parameters for this locator.  Parameters 
 
nbinsint or 'auto', optional


see MaxNLocator  
stepsarray-like, optional


see MaxNLocator  
integerbool, optional


see MaxNLocator  
symmetricbool, optional


see MaxNLocator  
prune{'lower', 'upper', 'both', None}, optional


see MaxNLocator  
min_n_ticksint, optional


see MaxNLocator
view_limits(dmin, dmax)[source]
 
Select a scale for the range from vmin to vmax. Subclasses should override this method to change locator behaviour.
classmatplotlib.ticker.MultipleLocator(base=1.0)[source]
 
Bases: matplotlib.ticker.Locator Set a tick on each integer multiple of a base within the view interval.   set_params(base)[source]
 
Set parameters within this locator. 
   tick_values(vmin, vmax)[source]
 
Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
  
   view_limits(dmin, dmax)[source]
 
Set the view limits to the nearest multiples of base that contain the data.
view_limits(dmin, dmax)[source]
 
Set the view limits to the nearest multiples of base that contain the data.
classmatplotlib.ticker.NullFormatter[source]
 
Bases: matplotlib.ticker.Formatter Always return the empty string.
classmatplotlib.ticker.NullLocator[source]
 
Bases: matplotlib.ticker.Locator No ticks   tick_values(vmin, vmax)[source]
 
Return the locations of the ticks.  Note Because the values are Null, vmin and vmax are not used in this method.
tick_values(vmin, vmax)[source]
 
Return the locations of the ticks.  Note Because the values are Null, vmin and vmax are not used in this method.
classmatplotlib.ticker.PercentFormatter(xmax=100, decimals=None, symbol='%', is_latex=False)[source]
 
Bases: matplotlib.ticker.Formatter Format numbers as a percentage.  Parameters 
 
xmaxfloat


Determines how the number is converted into a percentage. xmax is the data value that corresponds to 100%. Percentages are computed as x / xmax * 100. So if the data is already scaled to be percentages, xmax will be 100. Another common situation is where xmax is 1.0.  
decimalsNone or int


The number of decimal places to place after the point. If None (the default), the number will be computed automatically.  
symbolstr or None


A string that will be appended to the label. It may be None or empty to indicate that no symbol should be used. LaTeX special characters are escaped in symbol whenever latex mode is enabled, unless is_latex is True.  
is_latexbool


If False, reserved LaTeX characters in symbol will be escaped.       convert_to_pct(x)[source]

   format_pct(x, display_range)[source]
 
Format the number as a percentage number with the correct number of decimals and adds the percent symbol, if any. If self.decimals is None, the number of digits after the decimal point is set based on the display_range of the axis as follows:  
display_range decimals sample  
>50 0 x = 34.5 => 35%  
>5 1 x = 34.5 => 34.5%  
>0.5 2 x = 34.5 => 34.50%  
... ... ...   This method will not be very good for tiny axis ranges or extremely large ones. It assumes that the values on the chart are percentages displayed on a reasonable scale. 
   propertysymbol
 
The configured percent symbol as a string. If LaTeX is enabled via rcParams["text.usetex"] (default: False), the special characters {'#', '$', '%', '&', '~', '_', '^', '\', '{', '}'} are automatically escaped in the string.
format_pct(x, display_range)[source]
 
Format the number as a percentage number with the correct number of decimals and adds the percent symbol, if any. If self.decimals is None, the number of digits after the decimal point is set based on the display_range of the axis as follows:  
display_range decimals sample  
>50 0 x = 34.5 => 35%  
>5 1 x = 34.5 => 34.5%  
>0.5 2 x = 34.5 => 34.50%  
... ... ...   This method will not be very good for tiny axis ranges or extremely large ones. It assumes that the values on the chart are percentages displayed on a reasonable scale.
get_useLocale()[source]
 
Return whether locale settings are used for formatting.  See also  ScalarFormatter.set_useLocale
get_useMathText()[source]
 
Return whether to use fancy math formatting.  See also  ScalarFormatter.set_useMathText
get_useOffset()[source]
 
Return whether automatic mode for offset notation is active. This returns True if set_useOffset(True); it returns False if an explicit offset was set, e.g. set_useOffset(1000).  See also  ScalarFormatter.set_useOffset
set_powerlimits(lims)[source]
 
Set size thresholds for scientific notation.  Parameters 
 
lims(int, int)


A tuple (min_exp, max_exp) containing the powers of 10 that determine the switchover threshold. For a number representable as \(a \times 10^\mathrm{exp}\) with \(1 <= |a| < 10\), scientific notation will be used if exp <= min_exp or exp >= max_exp. The default limits are controlled by rcParams["axes.formatter.limits"] (default: [-5, 6]). In particular numbers with exp equal to the thresholds are written in scientific notation. Typically, min_exp will be negative and max_exp will be positive. For example, formatter.set_powerlimits((-3, 4)) will provide the following formatting: \(1 \times 10^{-3}, 9.9 \times 10^{-3}, 0.01,\) \(9999, 1 \times 10^4\).      See also  ScalarFormatter.set_scientific
set_scientific(b)[source]
 
Turn scientific notation on or off.  See also  ScalarFormatter.set_powerlimits
set_useLocale(val)[source]
 
Set whether to use locale settings for decimal sign and positive sign.  Parameters 
 
valbool or None


None resets to rcParams["axes.formatter.use_locale"] (default: False).
set_useMathText(val)[source]
 
Set whether to use fancy math formatting. If active, scientific notation is formatted as \(1.2 \times 10^3\).  Parameters 
 
valbool or None


None resets to rcParams["axes.formatter.use_mathtext"] (default: False).
set_useOffset(val)[source]
 
Set whether to use offset notation. When formatting a set numbers whose value is large compared to their range, the formatter can separate an additive constant. This can shorten the formatted numbers so that they are less likely to overlap when drawn on an axis.  Parameters 
 
valbool or float


 If False, do not use offset notation. If True (=automatic mode), use offset notation if it can make the residual numbers significantly shorter. The exact behavior is controlled by rcParams["axes.formatter.offset_threshold"] (default: 4). If a number, force an offset of the given value.      Examples With active offset notation, the values 100_000, 100_002, 100_004, 100_006, 100_008 will be formatted as 0, 2, 4, 6, 8 plus an offset +1e5, which is written to the edge of the axis.
classmatplotlib.ticker.StrMethodFormatter(fmt)[source]
 
Bases: matplotlib.ticker.Formatter Use a new-style format string (as used by str.format) to format the tick. The field used for the tick value must be labeled x and the field used for the tick position must be labeled pos.
classmatplotlib.ticker.SymmetricalLogLocator(transform=None, subs=None, linthresh=None, base=None)[source]
 
Bases: matplotlib.ticker.Locator Determine the tick locations for symmetric log axes.  Parameters 
 
transformSymmetricalLogTransform, optional


If set, defines the base and linthresh of the symlog transform.  
base, linthreshfloat, optional


The base and linthresh of the symlog transform, as documented for SymmetricalLogScale. These parameters are only used if transform is not set.  
subssequence of float, default: [1]


The multiples of integer powers of the base where ticks are placed, i.e., ticks are placed at [sub * base**i for i in ... for sub in subs].     Notes Either transform, or both base and linthresh, must be given.   set_params(subs=None, numticks=None)[source]
 
Set parameters within this locator. 
   tick_values(vmin, vmax)[source]
 
Return the values of the located ticks given vmin and vmax.  Note To get tick locations with the vmin and vmax values defined automatically for the associated axis simply call the Locator instance: >>> print(type(loc))
<type 'Locator'>
>>> print(loc())
[1, 2, 3, 4]
  
   view_limits(vmin, vmax)[source]
 
Try to choose the view limits intelligently.
set_params(subs=None, numticks=None)[source]
 
Set parameters within this locator.
classmatplotlib.ticker.TickHelper[source]
 
Bases: object   axis=None

   create_dummy_axis(**kwargs)[source]

   set_axis(axis)[source]

   set_bounds(vmin, vmax)[source]
 
[Deprecated] Notes  Deprecated since version 3.5:   
   set_data_interval(vmin, vmax)[source]
 
[Deprecated] Notes  Deprecated since version 3.5:   
   set_view_interval(vmin, vmax)[source]
 
[Deprecated] Notes  Deprecated since version 3.5:
set_bounds(vmin, vmax)[source]
 
[Deprecated] Notes  Deprecated since version 3.5:
matplotlib.tight_bbox Helper module for the bbox_inches parameter in Figure.savefig.   matplotlib.tight_bbox.adjust_bbox(fig, bbox_inches, fixed_dpi=None)[source]
 
Temporarily adjust the figure so that only the specified area (bbox_inches) is saved. It modifies fig.bbox, fig.bbox_inches, fig.transFigure._boxout, and fig.patch. While the figure size changes, the scale of the original figure is conserved. A function which restores the original values are returned. 
   matplotlib.tight_bbox.process_figure_for_rasterizing(fig, bbox_inches_restore, fixed_dpi=None)[source]
 
A function that needs to be called when figure dpi changes during the drawing (e.g., rasterizing). It recovers the bbox and re-adjust it with the new dpi.
matplotlib.tight_bbox.adjust_bbox(fig, bbox_inches, fixed_dpi=None)[source]
 
Temporarily adjust the figure so that only the specified area (bbox_inches) is saved. It modifies fig.bbox, fig.bbox_inches, fig.transFigure._boxout, and fig.patch. While the figure size changes, the scale of the original figure is conserved. A function which restores the original values are returned.
matplotlib.tight_bbox.process_figure_for_rasterizing(fig, bbox_inches_restore, fixed_dpi=None)[source]
 
A function that needs to be called when figure dpi changes during the drawing (e.g., rasterizing). It recovers the bbox and re-adjust it with the new dpi.
matplotlib.tight_layout Routines to adjust subplot params so that subplots are nicely fit in the figure. In doing so, only axis labels, tick labels, axes titles and offsetboxes that are anchored to axes are currently considered. Internally, this module assumes that the margins (left margin, etc.) which are differences between Axes.get_tightbbox and Axes.bbox are independent of Axes position. This may fail if Axes.adjustable is datalim as well as such cases as when left or right margin are affected by xlabel.   matplotlib.tight_layout.auto_adjust_subplotpars(fig, renderer, nrows_ncols, num1num2_list, subplot_list, ax_bbox_list=None, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
 
[Deprecated] Return a dict of subplot parameters to adjust spacing between subplots or None if resulting axes would have zero height or width. Note that this function ignores geometry information of subplot itself, but uses what is given by the nrows_ncols and num1num2_list parameters. Also, the results could be incorrect if some subplots have adjustable=datalim.  Parameters 
 
nrows_ncolstuple[int, int]


Number of rows and number of columns of the grid.  
num1num2_listlist[tuple[int, int]]


List of numbers specifying the area occupied by the subplot  
subplot_listlist of subplots


List of subplots that will be used to calculate optimal subplot_params.  
padfloat


Padding between the figure edge and the edges of subplots, as a fraction of the font size.  
h_pad, w_padfloat


Padding (height/width) between edges of adjacent subplots, as a fraction of the font size. Defaults to pad.  
recttuple[float, float, float, float]


[left, bottom, right, top] in normalized (0, 1) figure coordinates.     Notes  Deprecated since version 3.5.  
   matplotlib.tight_layout.get_renderer(fig)[source]

   matplotlib.tight_layout.get_subplotspec_list(axes_list, grid_spec=None)[source]
 
Return a list of subplotspec from the given list of axes. For an instance of axes that does not support subplotspec, None is inserted in the list. If grid_spec is given, None is inserted for those not from the given grid_spec. 
   matplotlib.tight_layout.get_tight_layout_figure(fig, axes_list, subplotspec_list, renderer, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
 
Return subplot parameters for tight-layouted-figure with specified padding.  Parameters 
 
figFigure


axes_listlist of Axes


subplotspec_listlist of SubplotSpec


The subplotspecs of each axes.  
rendererrenderer


padfloat


Padding between the figure edge and the edges of subplots, as a fraction of the font size.  
h_pad, w_padfloat


Padding (height/width) between edges of adjacent subplots. Defaults to pad.  
recttuple[float, float, float, float], optional


(left, bottom, right, top) rectangle in normalized figure coordinates that the whole subplots area (including labels) will fit into. Defaults to using the entire figure.    Returns 
 subplotspec or None

subplotspec kwargs to be passed to Figure.subplots_adjust or None if tight_layout could not be accomplished.
matplotlib.tight_layout.auto_adjust_subplotpars(fig, renderer, nrows_ncols, num1num2_list, subplot_list, ax_bbox_list=None, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
 
[Deprecated] Return a dict of subplot parameters to adjust spacing between subplots or None if resulting axes would have zero height or width. Note that this function ignores geometry information of subplot itself, but uses what is given by the nrows_ncols and num1num2_list parameters. Also, the results could be incorrect if some subplots have adjustable=datalim.  Parameters 
 
nrows_ncolstuple[int, int]


Number of rows and number of columns of the grid.  
num1num2_listlist[tuple[int, int]]


List of numbers specifying the area occupied by the subplot  
subplot_listlist of subplots


List of subplots that will be used to calculate optimal subplot_params.  
padfloat


Padding between the figure edge and the edges of subplots, as a fraction of the font size.  
h_pad, w_padfloat


Padding (height/width) between edges of adjacent subplots, as a fraction of the font size. Defaults to pad.  
recttuple[float, float, float, float]


[left, bottom, right, top] in normalized (0, 1) figure coordinates.     Notes  Deprecated since version 3.5.
matplotlib.tight_layout.get_subplotspec_list(axes_list, grid_spec=None)[source]
 
Return a list of subplotspec from the given list of axes. For an instance of axes that does not support subplotspec, None is inserted in the list. If grid_spec is given, None is inserted for those not from the given grid_spec.
matplotlib.tight_layout.get_tight_layout_figure(fig, axes_list, subplotspec_list, renderer, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
 
Return subplot parameters for tight-layouted-figure with specified padding.  Parameters 
 
figFigure


axes_listlist of Axes


subplotspec_listlist of SubplotSpec


The subplotspecs of each axes.  
rendererrenderer


padfloat


Padding between the figure edge and the edges of subplots, as a fraction of the font size.  
h_pad, w_padfloat


Padding (height/width) between edges of adjacent subplots. Defaults to pad.  
recttuple[float, float, float, float], optional


(left, bottom, right, top) rectangle in normalized figure coordinates that the whole subplots area (including labels) will fit into. Defaults to using the entire figure.    Returns 
 subplotspec or None

subplotspec kwargs to be passed to Figure.subplots_adjust or None if tight_layout could not be accomplished.
classmatplotlib.transforms.Affine2D(matrix=None, **kwargs)[source]
 
Bases: matplotlib.transforms.Affine2DBase A mutable 2D affine transformation. Initialize an Affine transform from a 3x3 numpy float array: a c e
b d f
0 0 1
 If matrix is None, initialize with the identity transform.   __init__(matrix=None, **kwargs)[source]
 
Initialize an Affine transform from a 3x3 numpy float array: a c e
b d f
0 0 1
 If matrix is None, initialize with the identity transform. 
   __module__='matplotlib.transforms'

   __str__()[source]
 
Return str(self). 
   clear()[source]
 
Reset the underlying matrix to the identity transform. 
   staticfrom_values(a, b, c, d, e, f)[source]
 
Create a new Affine2D instance from the given values: a c e
b d f
0 0 1
 . 
   get_matrix()[source]
 
Get the underlying transformation matrix as a 3x3 numpy array: a c e
b d f
0 0 1
 . 
   staticidentity()[source]
 
Return a new Affine2D object that is the identity transform. Unless this transform will be mutated later on, consider using the faster IdentityTransform class instead. 
   rotate(theta)[source]
 
Add a rotation (in radians) to this transform in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   rotate_around(x, y, theta)[source]
 
Add a rotation (in radians) around the point (x, y) in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   rotate_deg(degrees)[source]
 
Add a rotation (in degrees) to this transform in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   rotate_deg_around(x, y, degrees)[source]
 
Add a rotation (in degrees) around the point (x, y) in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   scale(sx, sy=None)[source]
 
Add a scale in place. If sy is None, the same scale is applied in both the x- and y-directions. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   set(other)[source]
 
Set this transformation from the frozen copy of another Affine2DBase object. 
   set_matrix(mtx)[source]
 
Set the underlying transformation matrix from a 3x3 numpy array: a c e
b d f
0 0 1
 . 
   skew(xShear, yShear)[source]
 
Add a skew in place. xShear and yShear are the shear angles along the x- and y-axes, respectively, in radians. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   skew_deg(xShear, yShear)[source]
 
Add a skew in place. xShear and yShear are the shear angles along the x- and y-axes, respectively, in degrees. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale(). 
   translate(tx, ty)[source]
 
Add a translation in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
__init__(matrix=None, **kwargs)[source]
 
Initialize an Affine transform from a 3x3 numpy float array: a c e
b d f
0 0 1
 If matrix is None, initialize with the identity transform.
staticfrom_values(a, b, c, d, e, f)[source]
 
Create a new Affine2D instance from the given values: a c e
b d f
0 0 1
 .
get_matrix()[source]
 
Get the underlying transformation matrix as a 3x3 numpy array: a c e
b d f
0 0 1
 .
staticidentity()[source]
 
Return a new Affine2D object that is the identity transform. Unless this transform will be mutated later on, consider using the faster IdentityTransform class instead.
rotate(theta)[source]
 
Add a rotation (in radians) to this transform in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
rotate_around(x, y, theta)[source]
 
Add a rotation (in radians) around the point (x, y) in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
rotate_deg(degrees)[source]
 
Add a rotation (in degrees) to this transform in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
rotate_deg_around(x, y, degrees)[source]
 
Add a rotation (in degrees) around the point (x, y) in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
scale(sx, sy=None)[source]
 
Add a scale in place. If sy is None, the same scale is applied in both the x- and y-directions. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
set(other)[source]
 
Set this transformation from the frozen copy of another Affine2DBase object.
set_matrix(mtx)[source]
 
Set the underlying transformation matrix from a 3x3 numpy array: a c e
b d f
0 0 1
 .
skew(xShear, yShear)[source]
 
Add a skew in place. xShear and yShear are the shear angles along the x- and y-axes, respectively, in radians. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
skew_deg(xShear, yShear)[source]
 
Add a skew in place. xShear and yShear are the shear angles along the x- and y-axes, respectively, in degrees. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().
translate(tx, ty)[source]
 
Add a translation in place. Returns self, so this method can easily be chained with more calls to rotate(), rotate_deg(), translate() and scale().