neulab/docprompting-conala huggingface dataset:
matplotlib.pyplot.tight_layout   matplotlib.pyplot.tight_layout(*, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
 
Adjust the padding between and around subplots. To exclude an artist on the Axes from the bounding box calculation that determines the subplot parameters (i.e. legend, or annotation), set a.set_in_layout(False) for that artist.  Parameters 
 
padfloat, default: 1.08


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


Padding (height/width) between edges of adjacent subplots, as a fraction of the font size.  
recttuple (left, bottom, right, top), default: (0, 0, 1, 1)


A rectangle in normalized figure coordinates into which the whole subplots area (including labels) will fit.      See also  Figure.set_tight_layout
pyplot.tight_layout
  
  Examples using matplotlib.pyplot.tight_layout
 
   Linestyles   

   Marker examples   

   Creating annotated heatmaps   

   Interpolations for imshow   

   Streamplot   

   Resizing axes with tight layout   

   Labeling ticks using engineering notation   

   Figure legend demo   

   Reference for Matplotlib artists   

   Zorder Demo   

   3D wireframe plots in one direction   

   MRI With EEG   

   Tick locators   

   Tight Layout guide
matplotlib.pyplot.title   matplotlib.pyplot.title(label, fontdict=None, loc=None, pad=None, *, y=None, **kwargs)[source]
 
Set a title for the Axes. Set one of the three available Axes titles. The available titles are positioned above the Axes in the center, flush with the left edge, and flush with the right edge.  Parameters 
 
labelstr


Text to use for the title  
fontdictdict


A dictionary controlling the appearance of the title text, the default fontdict is: {'fontsize': rcParams['axes.titlesize'],
 'fontweight': rcParams['axes.titleweight'],
 'color': rcParams['axes.titlecolor'],
 'verticalalignment': 'baseline',
 'horizontalalignment': loc}
  
loc{'center', 'left', 'right'}, default: rcParams["axes.titlelocation"] (default: 'center')


Which title to set.  
yfloat, default: rcParams["axes.titley"] (default: None)


Vertical Axes loation for the title (1.0 is the top). If None (the default), y is determined automatically to avoid decorators on the Axes.  
padfloat, default: rcParams["axes.titlepad"] (default: 6.0)


The offset of the title from the top of the Axes, in points.    Returns 
 Text

The matplotlib text instance representing the title    Other Parameters 
 
**kwargsText properties


Other keyword arguments are text properties, see Text for a list of valid text properties.     
  Examples using matplotlib.pyplot.title
 
   prop_cycle property markevery in rcParams   

   Plotting masked and NaN values   

   Stairs Demo   

   Step Demo   

   Geographic Projections   

   Multiple subplots   

   Controlling style of text and labels using a dictionary   

   Title positioning   

   Pyplot Mathtext   

   Pyplot Text   

   Solarized Light stylesheet   

   Interactive functions   

   Findobj Demo   

   Multipage PDF   

   Set and get properties   

   Table Demo   

   Zorder Demo   

   Custom scale   

   The Sankey class   

   SVG Histogram   

   Basic Usage   

   Pyplot tutorial
matplotlib.pyplot.tripcolor   matplotlib.pyplot.tripcolor(*args, alpha=1.0, norm=None, cmap=None, vmin=None, vmax=None, shading='flat', facecolors=None, **kwargs)[source]
 
Create a pseudocolor plot of an unstructured triangular grid. The triangulation can be specified in one of two ways; either: tripcolor(triangulation, ...)
 where triangulation is a Triangulation object, or tripcolor(x, y, ...)
tripcolor(x, y, triangles, ...)
tripcolor(x, y, triangles=triangles, ...)
tripcolor(x, y, mask=mask, ...)
tripcolor(x, y, triangles, mask=mask, ...)
 in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities. The next argument must be C, the array of color values, either one per point in the triangulation if color values are defined at points, or one per triangle in the triangulation if color values are defined at triangles. If there are the same number of points and triangles in the triangulation it is assumed that color values are defined at points; to force the use of color values at triangles use the kwarg facecolors=C instead of just C. shading may be 'flat' (the default) or 'gouraud'. If shading is 'flat' and C values are defined at points, the color values used for each triangle are from the mean C of the triangle's three points. If shading is 'gouraud' then color values must be defined at points. The remaining kwargs are the same as for pcolor.
matplotlib.pyplot.triplot   matplotlib.pyplot.triplot(*args, **kwargs)[source]
 
Draw a unstructured triangular grid as lines and/or markers. The triangulation to plot can be specified in one of two ways; either: triplot(triangulation, ...)
 where triangulation is a Triangulation object, or triplot(x, y, ...)
triplot(x, y, triangles, ...)
triplot(x, y, triangles=triangles, ...)
triplot(x, y, mask=mask, ...)
triplot(x, y, triangles, mask=mask, ...)
 in which case a Triangulation object will be created. See Triangulation for a explanation of these possibilities. The remaining args and kwargs are the same as for plot.  Returns 
 
linesLine2D


The drawn triangles edges.  
markersLine2D


The drawn marker nodes.
matplotlib.pyplot.twinx   matplotlib.pyplot.twinx(ax=None)[source]
 
Make and return a second axes that shares the x-axis. The new axes will overlay ax (or the current axes if ax is None), and its ticks will be on the right. Examples Plots with different scales
matplotlib.pyplot.twiny   matplotlib.pyplot.twiny(ax=None)[source]
 
Make and return a second axes that shares the y-axis. The new axes will overlay ax (or the current axes if ax is None), and its ticks will be on the top. Examples Plots with different scales
matplotlib.pyplot.uninstall_repl_displayhook   matplotlib.pyplot.uninstall_repl_displayhook()[source]
 
Uninstall the Matplotlib display hook.  Warning Need IPython >= 2 for this to work. For IPython < 2 will raise a NotImplementedError   Warning If you are using vanilla python and have installed another display hook, this will reset sys.displayhook to what ever function was there when Matplotlib installed its displayhook, possibly discarding your changes.
matplotlib.pyplot.violinplot   matplotlib.pyplot.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.
matplotlib.pyplot.viridis   matplotlib.pyplot.viridis()[source]
 
Set the colormap to 'viridis'. This changes the default colormap as well as the colormap of the current image if there is one. See help(colormaps) for more information.
matplotlib.pyplot.vlines   matplotlib.pyplot.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
matplotlib.pyplot.waitforbuttonpress   matplotlib.pyplot.waitforbuttonpress(timeout=- 1)[source]
 
Blocking call to interact with the figure. Wait for user input and return True if a key was pressed, False if a mouse button was pressed and None if no input was given within timeout seconds. Negative values deactivate timeout. 
  Examples using matplotlib.pyplot.waitforbuttonpress
 
   Interactive functions
matplotlib.pyplot.winter   matplotlib.pyplot.winter()[source]
 
Set the colormap to 'winter'. This changes the default colormap as well as the colormap of the current image if there is one. See help(colormaps) for more information.
matplotlib.pyplot.xcorr   matplotlib.pyplot.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".
matplotlib.pyplot.xkcd   matplotlib.pyplot.xkcd(scale=1, length=100, randomness=2)[source]
 
Turn on xkcd sketch-style drawing mode. This will only have effect on things drawn after this function is called. For best results, the "Humor Sans" font should be installed: it is not included with Matplotlib.  Parameters 
 
scalefloat, optional


The amplitude of the wiggle perpendicular to the source line.  
lengthfloat, optional


The length of the wiggle along the line.  
randomnessfloat, optional


The scale factor by which the length is shrunken or expanded.     Notes This function works by a number of rcParams, so it will probably override others you have set before. If you want the effects of this function to be temporary, it can be used as a context manager, for example: with plt.xkcd():
    # This figure will be in XKCD-style
    fig1 = plt.figure()
    # ...

# This figure will be in regular style
fig2 = plt.figure()
 
  Examples using matplotlib.pyplot.xkcd
 
   XKCD
matplotlib.pyplot.xlabel   matplotlib.pyplot.xlabel(xlabel, fontdict=None, labelpad=None, *, loc=None, **kwargs)[source]
 
Set the label for the x-axis.  Parameters 
 
xlabelstr


The label text.  
labelpadfloat, default: rcParams["axes.labelpad"] (default: 4.0)


Spacing in points from the Axes bounding box including ticks and tick labels. If None, the previous value is left as is.  
loc{'left', 'center', 'right'}, default: rcParams["xaxis.labellocation"] (default: 'center')


The label position. This is a high-level alternative for passing parameters x and horizontalalignment.    Other Parameters 
 
**kwargsText properties


Text properties control the appearance of the label.      See also  text

Documents the properties supported by Text.    
  Examples using matplotlib.pyplot.xlabel
 
   Scatter Symbol   

   Multiple subplots   

   Controlling style of text and labels using a dictionary   

   Infinite lines   

   Pyplot Mathtext   

   Pyplot Text   

   Solarized Light stylesheet   

   Findobj Demo   

   Custom scale   

   Basic Usage   

   Pyplot tutorial
matplotlib.pyplot.xlim   matplotlib.pyplot.xlim(*args, **kwargs)[source]
 
Get or set the x limits of the current axes. Call signatures: left, right = xlim()  # return the current xlim
xlim((left, right))   # set the xlim to left, right
xlim(left, right)     # set the xlim to left, right
 If you do not specify args, you can pass left or right as kwargs, i.e.: xlim(right=3)  # adjust the right leaving left unchanged
xlim(left=1)  # adjust the left leaving right unchanged
 Setting limits turns autoscaling off for the x-axis.  Returns 
 left, right

A tuple of the new x-axis limits.     Notes Calling this function with no arguments (e.g. xlim()) is the pyplot equivalent of calling get_xlim on the current axes. Calling this function with arguments is the pyplot equivalent of calling set_xlim on the current axes. All arguments are passed though. 
  Examples using matplotlib.pyplot.xlim
 
   Shared Axis   

   Infinite lines   

   Pyplot Text   

   Frame grabbing   

   Interactive functions
matplotlib.pyplot.xscale   matplotlib.pyplot.xscale(value, **kwargs)[source]
 
Set the x-axis scale.  Parameters 
 
value{"linear", "log", "symlog", "logit", ...} or ScaleBase


The axis scale type to apply.  **kwargs

Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments:  matplotlib.scale.LinearScale matplotlib.scale.LogScale matplotlib.scale.SymmetricalLogScale matplotlib.scale.LogitScale matplotlib.scale.FuncScale      Notes By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here.
matplotlib.pyplot.xticks   matplotlib.pyplot.xticks(ticks=None, labels=None, **kwargs)[source]
 
Get or set the current tick locations and labels of the x-axis. Pass no arguments to return the current values without modifying them.  Parameters 
 
ticksarray-like, optional


The list of xtick locations. Passing an empty list removes all xticks.  
labelsarray-like, optional


The labels to place at the given ticks locations. This argument can only be passed if ticks is passed as well.  **kwargs

Text properties can be used to control the appearance of the labels.    Returns 
 locs

The list of xtick locations.  labels

The list of xlabel Text objects.     Notes Calling this function with no arguments (e.g. xticks()) is the pyplot equivalent of calling get_xticks and get_xticklabels on the current axes. Calling this function with arguments is the pyplot equivalent of calling set_xticks and set_xticklabels on the current axes. Examples >>> locs, labels = xticks()  # Get the current locations and labels.
>>> xticks(np.arange(0, 1, step=0.2))  # Set label locations.
>>> xticks(np.arange(3), ['Tom', 'Dick', 'Sue'])  # Set text labels.
>>> xticks([0, 1, 2], ['January', 'February', 'March'],
...        rotation=20)  # Set text labels and properties.
>>> xticks([])  # Disable xticks.
 
  Examples using matplotlib.pyplot.xticks
 
   Secondary Axis   

   Table Demo   

   Rotating custom tick labels
matplotlib.pyplot.ylabel   matplotlib.pyplot.ylabel(ylabel, fontdict=None, labelpad=None, *, loc=None, **kwargs)[source]
 
Set the label for the y-axis.  Parameters 
 
ylabelstr


The label text.  
labelpadfloat, default: rcParams["axes.labelpad"] (default: 4.0)


Spacing in points from the Axes bounding box including ticks and tick labels. If None, the previous value is left as is.  
loc{'bottom', 'center', 'top'}, default: rcParams["yaxis.labellocation"] (default: 'center')


The label position. This is a high-level alternative for passing parameters y and horizontalalignment.    Other Parameters 
 
**kwargsText properties


Text properties control the appearance of the label.      See also  text

Documents the properties supported by Text.    
  Examples using matplotlib.pyplot.ylabel
 
   Scatter Symbol   

   Multiple subplots   

   Controlling style of text and labels using a dictionary   

   Pyplot Mathtext   

   Pyplot Simple   

   Pyplot Text   

   Solarized Light stylesheet   

   Findobj Demo   

   Table Demo   

   Custom scale   

   Basic Usage   

   Pyplot tutorial
matplotlib.pyplot.ylim   matplotlib.pyplot.ylim(*args, **kwargs)[source]
 
Get or set the y-limits of the current axes. Call signatures: bottom, top = ylim()  # return the current ylim
ylim((bottom, top))   # set the ylim to bottom, top
ylim(bottom, top)     # set the ylim to bottom, top
 If you do not specify args, you can alternatively pass bottom or top as kwargs, i.e.: ylim(top=3)  # adjust the top leaving bottom unchanged
ylim(bottom=1)  # adjust the bottom leaving top unchanged
 Setting limits turns autoscaling off for the y-axis.  Returns 
 bottom, top

A tuple of the new y-axis limits.     Notes Calling this function with no arguments (e.g. ylim()) is the pyplot equivalent of calling get_ylim on the current axes. Calling this function with arguments is the pyplot equivalent of calling set_ylim on the current axes. All arguments are passed though. 
  Examples using matplotlib.pyplot.ylim
 
   Infinite lines   

   Pyplot Text   

   Frame grabbing   

   Interactive functions   

   Findobj Demo   

   Pyplot tutorial
matplotlib.pyplot.yscale   matplotlib.pyplot.yscale(value, **kwargs)[source]
 
Set the y-axis scale.  Parameters 
 
value{"linear", "log", "symlog", "logit", ...} or ScaleBase


The axis scale type to apply.  **kwargs

Different keyword arguments are accepted, depending on the scale. See the respective class keyword arguments:  matplotlib.scale.LinearScale matplotlib.scale.LogScale matplotlib.scale.SymmetricalLogScale matplotlib.scale.LogitScale matplotlib.scale.FuncScale      Notes By default, Matplotlib supports the above mentioned scales. Additionally, custom scales may be registered using matplotlib.scale.register_scale. These scales can then also be used here. 
  Examples using matplotlib.pyplot.yscale
 
   Custom scale   

   Pyplot tutorial
matplotlib.pyplot.yticks   matplotlib.pyplot.yticks(ticks=None, labels=None, **kwargs)[source]
 
Get or set the current tick locations and labels of the y-axis. Pass no arguments to return the current values without modifying them.  Parameters 
 
ticksarray-like, optional


The list of ytick locations. Passing an empty list removes all yticks.  
labelsarray-like, optional


The labels to place at the given ticks locations. This argument can only be passed if ticks is passed as well.  **kwargs

Text properties can be used to control the appearance of the labels.    Returns 
 locs

The list of ytick locations.  labels

The list of ylabel Text objects.     Notes Calling this function with no arguments (e.g. yticks()) is the pyplot equivalent of calling get_yticks and get_yticklabels on the current axes. Calling this function with arguments is the pyplot equivalent of calling set_yticks and set_yticklabels on the current axes. Examples >>> locs, labels = yticks()  # Get the current locations and labels.
>>> yticks(np.arange(0, 1, step=0.2))  # Set label locations.
>>> yticks(np.arange(3), ['Tom', 'Dick', 'Sue'])  # Set text labels.
>>> yticks([0, 1, 2], ['January', 'February', 'March'],
...        rotation=45)  # Set text labels and properties.
>>> yticks([])  # Disable yticks.
 
  Examples using matplotlib.pyplot.yticks
 
   Table Demo
matplotlib.quiver Support for plotting vector fields. Presently this contains Quiver and Barb. Quiver plots an arrow in the direction of the vector, with the size of the arrow related to the magnitude of the vector. Barbs are like quiver in that they point along a vector, but the magnitude of the vector is given schematically by the presence of barbs or flags on the barb. This will also become a home for things such as standard deviation ellipses, which can and will be derived very easily from the Quiver code.  Classes  
Quiver(ax, *args[, scale, headwidth, ...]) Specialized PolyCollection for arrows.  
QuiverKey(Q, X, Y, U, label, *[, angle, ...]) Labelled arrow for use as a quiver plot scale key.  
Barbs(ax, *args[, pivot, length, barbcolor, ...]) Specialized PolyCollection for barbs.