neulab/docprompting-conala huggingface dataset:
matplotlib.axes.Axes.violin   Axes.violin(vpstats, positions=None, vert=True, widths=0.5, showmeans=False, showextrema=True, showmedians=False)[source]
 
Drawing function for violin plots. Draw a violin plot for each column of vpstats. Each filled area extends to represent the entire data range, with optional lines at the mean, the median, the minimum, the maximum, and the quantiles values.  Parameters 
 
vpstatslist of dicts


A list of dictionaries containing stats for each violin plot. Required keys are:  
coords: A list of scalars containing the coordinates that the violin's kernel density estimate were evaluated at. 
vals: A list of scalars containing the values of the kernel density estimate at each of the coordinates given in coords. 
mean: The mean value for this violin's dataset. 
median: The median value for this violin's dataset. 
min: The minimum value for this violin's dataset. 
max: The maximum value for this violin's dataset.  Optional keys are:  
quantiles: A list of scalars containing the quantile values for this violin's dataset.   
positionsarray-like, default: [1, 2, ..., n]


The positions of the violins. The ticks and limits are automatically set to match the positions.  
vertbool, default: True.


If true, plots the violins vertically. Otherwise, plots the violins horizontally.  
widthsarray-like, default: 0.5


Either a scalar or a vector that sets the maximal width of each violin. The default is 0.5, which uses about half of the available horizontal space.  
showmeansbool, default: False


If true, will toggle rendering of the means.  
showextremabool, default: True


If true, will toggle rendering of the extrema.  
showmediansbool, default: False


If true, will toggle rendering of the medians.    Returns 
 dict

A dictionary mapping each component of the violinplot to a list of the corresponding collection instances created. The dictionary has the following keys:  
bodies: A list of the PolyCollection instances containing the filled area of each violin. 
cmeans: A LineCollection instance that marks the mean values of each of the violin's distribution. 
cmins: A LineCollection instance that marks the bottom of each violin's distribution. 
cmaxes: A LineCollection instance that marks the top of each violin's distribution. 
cbars: A LineCollection instance that marks the centers of each violin's distribution. 
cmedians: A LineCollection instance that marks the median values of each of the violin's distribution. 
cquantiles: A LineCollection instance created to identify the quantiles values of each of the violin's distribution.
matplotlib.axes.Axes.violinplot   Axes.violinplot(dataset, positions=None, vert=True, widths=0.5, showmeans=False, showextrema=True, showmedians=False, quantiles=None, points=100, bw_method=None, *, data=None)[source]
 
Make a violin plot. Make a violin plot for each column of dataset or each vector in sequence dataset. Each filled area extends to represent the entire data range, with optional lines at the mean, the median, the minimum, the maximum, and user-specified quantiles.  Parameters 
 
datasetArray or a sequence of vectors.


The input data.  
positionsarray-like, default: [1, 2, ..., n]


The positions of the violins. The ticks and limits are automatically set to match the positions.  
vertbool, default: True.


If true, creates a vertical violin plot. Otherwise, creates a horizontal violin plot.  
widthsarray-like, default: 0.5


Either a scalar or a vector that sets the maximal width of each violin. The default is 0.5, which uses about half of the available horizontal space.  
showmeansbool, default: False


If True, will toggle rendering of the means.  
showextremabool, default: True


If True, will toggle rendering of the extrema.  
showmediansbool, default: False


If True, will toggle rendering of the medians.  
quantilesarray-like, default: None


If not None, set a list of floats in interval [0, 1] for each violin, which stands for the quantiles that will be rendered for that violin.  
pointsint, default: 100


Defines the number of points to evaluate each of the gaussian kernel density estimations at.  
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 its only parameter and return a scalar. If None (default), 'scott' is used.  
dataindexable object, optional


If given, the following parameters also accept a string s, which is interpreted as data[s] (unless this raises an exception): dataset    Returns 
 dict

A dictionary mapping each component of the violinplot to a list of the corresponding collection instances created. The dictionary has the following keys:  
bodies: A list of the PolyCollection instances containing the filled area of each violin. 
cmeans: A LineCollection instance that marks the mean values of each of the violin's distribution. 
cmins: A LineCollection instance that marks the bottom of each violin's distribution. 
cmaxes: A LineCollection instance that marks the top of each violin's distribution. 
cbars: A LineCollection instance that marks the centers of each violin's distribution. 
cmedians: A LineCollection instance that marks the median values of each of the violin's distribution. 
cquantiles: A LineCollection instance created to identify the quantile values of each of the violin's distribution.      
  Examples using matplotlib.axes.Axes.violinplot
 
   Violin plot customization   

   violinplot(D)
matplotlib.axes.Axes.vlines   Axes.vlines(x, ymin, ymax, colors=None, linestyles='solid', label='', *, data=None, **kwargs)[source]
 
Plot vertical lines at each x from ymin to ymax.  Parameters 
 
xfloat or array-like


x-indexes where to plot the lines.  
ymin, ymaxfloat or array-like


Respective beginning and end of each line. If scalars are provided, all lines will have same length.  
colorslist of colors, default: rcParams["lines.color"] (default: 'C0')


linestyles{'solid', 'dashed', 'dashdot', 'dotted'}, optional


labelstr, default: ''

  Returns 
 LineCollection
  Other Parameters 
 
dataindexable object, optional


If given, the following parameters also accept a string s, which is interpreted as data[s] (unless this raises an exception): x, ymin, ymax, colors  
**kwargsLineCollection properties.

    See also  hlines

horizontal lines  axvline

vertical line across the Axes    
  Examples using matplotlib.axes.Axes.vlines
 
   Creating a timeline with lines, dates, and text   

   hlines and vlines   

   Violin plot customization
matplotlib.axes.Axes.xaxis_date   Axes.xaxis_date(tz=None)[source]
 
Set up axis ticks and labels to treat data along the xaxis as dates.  Parameters 
 
tzstr or datetime.tzinfo, default: rcParams["timezone"] (default: 'UTC')


The timezone used to create date labels.
matplotlib.axes.Axes.xaxis_inverted   Axes.xaxis_inverted()[source]
 
Return whether the xaxis is oriented in the "inverse" direction. The "normal" direction is increasing to the right for the x-axis and to the top for the y-axis; the "inverse" direction is increasing to the left for the x-axis and to the bottom for the y-axis.
matplotlib.axes.Axes.xcorr   Axes.xcorr(x, y, normed=True, detrend=<function detrend_none>, usevlines=True, maxlags=10, *, data=None, **kwargs)[source]
 
Plot the cross correlation between x and y. The correlation with lag k is defined as \(\sum_n x[n+k] \cdot y^*[n]\), where \(y^*\) is the complex conjugate of \(y\).  Parameters 
 
x, yarray-like of length n


detrendcallable, default: mlab.detrend_none (no detrending)


A detrending function applied to x and y. It must have the signature detrend(x: np.ndarray) -> np.ndarray
  
normedbool, default: True


If True, input vectors are normalised to unit length.  
usevlinesbool, default: True


Determines the plot style. If True, vertical lines are plotted from 0 to the xcorr value using Axes.vlines. Additionally, a horizontal line is plotted at y=0 using Axes.axhline. If False, markers are plotted at the xcorr values using Axes.plot.  
maxlagsint, default: 10


Number of lags to show. If None, will return all 2 * len(x) - 1 lags.    Returns 
 
lagsarray (length 2*maxlags+1)


The lag vector.  
carray (length 2*maxlags+1)


The auto correlation vector.  
lineLineCollection or Line2D


Artist added to the Axes of the correlation:  
LineCollection if usevlines is True. 
Line2D if usevlines is False.   
bLine2D or None


Horizontal line at 0 if usevlines is True None usevlines is False.    Other Parameters 
 
linestyleLine2D property, optional


The linestyle for plotting the data points. Only used if usevlines is False.  
markerstr, default: 'o'


The marker for plotting the data points. Only used if usevlines is False.  
dataindexable object, optional


If given, the following parameters also accept a string s, which is interpreted as data[s] (unless this raises an exception): x, y  **kwargs

Additional parameters are passed to Axes.vlines and Axes.axhline if usevlines is True; otherwise they are passed to Axes.plot.     Notes The cross correlation is performed with numpy.correlate with mode = "full". 
  Examples using matplotlib.axes.Axes.xcorr
 
   Cross- and Auto-Correlation Demo
matplotlib.axes.Axes.yaxis_date   Axes.yaxis_date(tz=None)[source]
 
Set up axis ticks and labels to treat data along the yaxis as dates.  Parameters 
 
tzstr or datetime.tzinfo, default: rcParams["timezone"] (default: 'UTC')


The timezone used to create date labels.
matplotlib.axes.Axes.yaxis_inverted   Axes.yaxis_inverted()[source]
 
Return whether the yaxis is oriented in the "inverse" direction. The "normal" direction is increasing to the right for the x-axis and to the top for the y-axis; the "inverse" direction is increasing to the left for the x-axis and to the bottom for the y-axis.
matplotlib.axes.subplot_class_factory   matplotlib.axes.subplot_class_factory(axes_class)[source]
matplotlib.axes.SubplotBase   classmatplotlib.axes.SubplotBase(fig, *args, **kwargs)[source]
 
Bases: object Base class for subplots, which are Axes instances with additional methods to facilitate generating and manipulating a set of Axes within a figure.  Parameters 
 
figmatplotlib.figure.Figure


*argstuple (nrows, ncols, index) or int


The array of subplots in the figure has dimensions (nrows,
ncols), and index is the index of the subplot being created. index starts at 1 in the upper left corner and increases to the right. If nrows, ncols, and index are all single digit numbers, then args can be passed as a single 3-digit number (e.g. 234 for (2, 3, 4)).  **kwargs

Keyword arguments are passed to the Axes (sub)class constructor.       change_geometry(numrows, numcols, num)[source]
 
[Deprecated] Change subplot geometry, e.g., from (1, 1, 1) to (2, 2, 3). Notes  Deprecated since version 3.4.  
   propertyfigbox[source]

   get_geometry()[source]
 
[Deprecated] Get the subplot geometry, e.g., (2, 2, 3). Notes  Deprecated since version 3.4.  
   get_gridspec()[source]
 
Return the GridSpec instance associated with the subplot. 
   get_subplotspec()[source]
 
Return the SubplotSpec instance associated with the subplot. 
   is_first_col()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:   
   is_first_row()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:   
   is_last_col()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:   
   is_last_row()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:   
   label_outer()[source]
 
Only show "outer" labels and tick labels. x-labels are only kept for subplots on the last row (or first row, if labels are on the top side); y-labels only for subplots on the first column (or last column, if labels are on the right side). 
   propertynumCols[source]

   propertynumRows[source]

   set_subplotspec(subplotspec)[source]
 
Set the SubplotSpec. instance associated with the subplot. 
   update_params()[source]
 
[Deprecated] Update the subplot position from self.figure.subplotpars. Notes  Deprecated since version 3.4.
change_geometry(numrows, numcols, num)[source]
 
[Deprecated] Change subplot geometry, e.g., from (1, 1, 1) to (2, 2, 3). Notes  Deprecated since version 3.4.
get_geometry()[source]
 
[Deprecated] Get the subplot geometry, e.g., (2, 2, 3). Notes  Deprecated since version 3.4.
get_subplotspec()[source]
 
Return the SubplotSpec instance associated with the subplot.
is_first_col()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
is_first_row()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
is_last_col()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
is_last_row()[source]
 
[Deprecated] Notes  Deprecated since version 3.4:
label_outer()[source]
 
Only show "outer" labels and tick labels. x-labels are only kept for subplots on the last row (or first row, if labels are on the top side); y-labels only for subplots on the first column (or last column, if labels are on the right side).
set_subplotspec(subplotspec)[source]
 
Set the SubplotSpec. instance associated with the subplot.
update_params()[source]
 
[Deprecated] Update the subplot position from self.figure.subplotpars. Notes  Deprecated since version 3.4.
mpl_toolkits.axes_grid  Note AxesGrid has been a part of matplotlib since v 0.99. Originally, the toolkit used the axes_grid namespace. In more recent versions, the toolkit has been split into axes_grid1 and axisartist. While axes_grid is maintained for the backward compatibility, use of axes_grid1 and axisartist is recommended. For the documentation on axes_grid, see the previous version of the docs.   mpl_toolkits.axes_grid1 mpl_toolkits.axisartist
mpl_toolkits.axes_grid1 mpl_toolkits.axes_grid1 provides a framework of helper classes to adjust the positioning of multiple fixed-aspect Axes (e.g., displaying images). It can be contrasted with the aspect property of Matplotlib Axes, which adjusts the position of a single Axes. See Overview of mpl_toolkits.axes_grid1 for a guide on the usage of axes_grid1.    The submodules of the axes_grid1 API are:  
axes_grid1.anchored_artists   
axes_grid1.axes_divider Helper classes to adjust the positions of multiple axes at drawing time.  
axes_grid1.axes_grid   
axes_grid1.axes_rgb   
axes_grid1.axes_size Provides classes of simple units that will be used with AxesDivider class (or others) to determine the size of each axes.  
axes_grid1.inset_locator A collection of functions and objects for creating or placing inset axes.  
axes_grid1.mpl_axes   
axes_grid1.parasite_axes
mpl_toolkits.axes_grid1.anchored_artists  Classes  
AnchoredAuxTransformBox(transform, loc[, ...]) An anchored container with transformed coordinates.  
AnchoredDirectionArrows(transform, label_x, ...) Draw two perpendicular arrows to indicate directions.  
AnchoredDrawingArea(width, height, xdescent, ...) An anchored container with a fixed size and fillable DrawingArea.  
AnchoredEllipse(transform, width, height, ...) Draw an anchored ellipse of a given size.  
AnchoredSizeBar(transform, size, label, loc) Draw a horizontal scale bar with a center-aligned label underneath.
mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox   classmpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox(transform, loc, pad=0.4, borderpad=0.5, prop=None, frameon=True, **kwargs)[source]
 
Bases: matplotlib.offsetbox.AnchoredOffsetbox An anchored container with transformed coordinates. Artists added to the drawing_area are scaled according to the coordinates of the transformation used. The dimensions of this artist will scale to contain the artists added.  Parameters 
 
transformmatplotlib.transforms.Transform


The transformation object for the coordinate system in use, i.e., matplotlib.axes.Axes.transData.  
locstr


Location of this artist. Valid locations are 'upper left', 'upper center', 'upper right', 'center left', 'center', 'center right', 'lower left', 'lower center, 'lower right'. For backward compatibility, numeric values are accepted as well. See the parameter loc of Legend for details.  
padfloat, default: 0.4


Padding around the child objects, in fraction of the font size.  
borderpadfloat, default: 0.5


Border padding, in fraction of the font size.  
propmatplotlib.font_manager.FontProperties, optional


Font property used as a reference for paddings.  
frameonbool, default: True


If True, draw a box around this artists.  **kwargs

Keyword arguments forwarded to AnchoredOffsetbox.     Examples To display an ellipse in the upper left, with a width of 0.1 and height of 0.4 in data coordinates: >>> box = AnchoredAuxTransformBox(ax.transData, loc='upper left')
>>> el = Ellipse((0, 0), width=0.1, height=0.4, angle=30)
>>> box.drawing_area.add_artist(el)
>>> ax.add_artist(box)
  Attributes 
 
drawing_areamatplotlib.offsetbox.AuxTransformBox


A container for artists to display.       set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, bbox_to_anchor=<UNSET>, child=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, gid=<UNSET>, height=<UNSET>, in_layout=<UNSET>, label=<UNSET>, offset=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, width=<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  
bbox_to_anchor unknown  
child unknown  
clip_box Bbox  
clip_on bool  
clip_path Patch or (Path, Transform) or None  
figure Figure  
gid str  
height float  
in_layout bool  
label object  
offset (float, float) or callable  
path_effects AbstractPathEffect  
picker None or bool or float or callable  
rasterized bool  
sketch_params (scale: float, length: float, randomness: float)  
snap bool or None  
transform Transform  
url str  
visible bool  
width float  
zorder float   
 
  Examples using mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox
 
   Annotations
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, bbox_to_anchor=<UNSET>, child=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, gid=<UNSET>, height=<UNSET>, in_layout=<UNSET>, label=<UNSET>, offset=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, width=<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  
bbox_to_anchor unknown  
child unknown  
clip_box Bbox  
clip_on bool  
clip_path Patch or (Path, Transform) or None  
figure Figure  
gid str  
height float  
in_layout bool  
label object  
offset (float, float) or callable  
path_effects AbstractPathEffect  
picker None or bool or float or callable  
rasterized bool  
sketch_params (scale: float, length: float, randomness: float)  
snap bool or None  
transform Transform  
url str  
visible bool  
width float  
zorder float
mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea   classmpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea(width, height, xdescent, ydescent, loc, pad=0.4, borderpad=0.5, prop=None, frameon=True, **kwargs)[source]
 
Bases: matplotlib.offsetbox.AnchoredOffsetbox An anchored container with a fixed size and fillable DrawingArea. Artists added to the drawing_area will have their coordinates interpreted as pixels. Any transformations set on the artists will be overridden.  Parameters 
 
width, heightfloat


width and height of the container, in pixels.  
xdescent, ydescentfloat


descent of the container in the x- and y- direction, in pixels.  
locstr


Location of this artist. Valid locations are 'upper left', 'upper center', 'upper right', 'center left', 'center', 'center right', 'lower left', 'lower center, 'lower right'. For backward compatibility, numeric values are accepted as well. See the parameter loc of Legend for details.  
padfloat, default: 0.4


Padding around the child objects, in fraction of the font size.  
borderpadfloat, default: 0.5


Border padding, in fraction of the font size.  
propmatplotlib.font_manager.FontProperties, optional


Font property used as a reference for paddings.  
frameonbool, default: True


If True, draw a box around this artists.  **kwargs

Keyword arguments forwarded to AnchoredOffsetbox.     Examples To display blue and red circles of different sizes in the upper right of an axes ax: >>> ada = AnchoredDrawingArea(20, 20, 0, 0,
...                           loc='upper right', frameon=False)
>>> ada.drawing_area.add_artist(Circle((10, 10), 10, fc="b"))
>>> ada.drawing_area.add_artist(Circle((30, 10), 5, fc="r"))
>>> ax.add_artist(ada)
  Attributes 
 
drawing_areamatplotlib.offsetbox.DrawingArea


A container for artists to display.       set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, bbox_to_anchor=<UNSET>, child=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, gid=<UNSET>, height=<UNSET>, in_layout=<UNSET>, label=<UNSET>, offset=<UNSET>, path_effects=<UNSET>, picker=<UNSET>, rasterized=<UNSET>, sketch_params=<UNSET>, snap=<UNSET>, transform=<UNSET>, url=<UNSET>, visible=<UNSET>, width=<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  
bbox_to_anchor unknown  
child unknown  
clip_box Bbox  
clip_on bool  
clip_path Patch or (Path, Transform) or None  
figure Figure  
gid str  
height float  
in_layout bool  
label object  
offset (float, float) or callable  
path_effects AbstractPathEffect  
picker None or bool or float or callable  
rasterized bool  
sketch_params (scale: float, length: float, randomness: float)  
snap bool or None  
transform Transform  
url str  
visible bool  
width float  
zorder float   
 
  Examples using mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea
 
   Simple Anchored Artists   

   Annotations