neulab/docprompting-conala huggingface dataset:
matplotlib.axes.Axes.indicate_inset   Axes.indicate_inset(bounds, inset_ax=None, *, transform=None, facecolor='none', edgecolor='0.5', alpha=0.5, zorder=4.99, **kwargs)[source]
 
Add an inset indicator to the Axes. This is a rectangle on the plot at the position indicated by bounds that optionally has lines that connect the rectangle to an inset Axes (Axes.inset_axes).  Parameters 
 
bounds[x0, y0, width, height]


Lower-left corner of rectangle to be marked, and its width and height.  
inset_axAxes


An optional inset Axes to draw connecting lines to. Two lines are drawn connecting the indicator box to the inset Axes on corners chosen so as to not overlap with the indicator box.  
transformTransform


Transform for the rectangle coordinates. Defaults to ax.transAxes, i.e. the units of rect are in Axes-relative coordinates.  
facecolorcolor, default: 'none'


Facecolor of the rectangle.  
edgecolorcolor, default: '0.5'


Color of the rectangle and color of the connecting lines.  
alphafloat, default: 0.5


Transparency of the rectangle and connector lines.  
zorderfloat, default: 4.99


Drawing order of the rectangle and connector lines. The default, 4.99, is just below the default level of inset Axes.  **kwargs

Other keyword arguments are passed on to the Rectangle patch:   
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  
angle unknown  
animated bool  
antialiased or aa bool or None  
bounds (left, bottom, width, height)  
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', '.', '*'}  
height unknown  
in_layout bool  
joinstyle JoinStyle or {'miter', 'round', 'bevel'}  
label object  
linestyle or ls {'-', '--', '-.', ':', '', (offset, on-off-seq), ...}  
linewidth or lw float or None  
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 unknown  
x unknown  
xy (float, float)  
y unknown  
zorder float      Returns 
 
rectangle_patchpatches.Rectangle


The indicator frame.  
connector_lines4-tuple of patches.ConnectionPatch


The four connector lines connecting to (lower_left, upper_left, lower_right upper_right) corners of inset_ax. Two lines are set with visibility to False, but the user can set the visibility to True if the automatic choice is not deemed correct.      Warning This method is experimental as of 3.0, and the API may change.
matplotlib.axes.Axes.indicate_inset_zoom   Axes.indicate_inset_zoom(inset_ax, **kwargs)[source]
 
Add an inset indicator rectangle to the Axes based on the axis limits for an inset_ax and draw connectors between inset_ax and the rectangle.  Parameters 
 
inset_axAxes


Inset Axes to draw connecting lines to. Two lines are drawn connecting the indicator box to the inset Axes on corners chosen so as to not overlap with the indicator box.  **kwargs

Other keyword arguments are passed on to Axes.indicate_inset    Returns 
 
rectangle_patchpatches.Rectangle


Rectangle artist.  
connector_lines4-tuple of patches.ConnectionPatch


Each of four connector lines coming from the rectangle drawn on this axis, in the order lower left, upper left, lower right, upper right. Two are set with visibility to False, but the user can set the visibility to True if the automatic choice is not deemed correct.      Warning This method is experimental as of 3.0, and the API may change.  
  Examples using matplotlib.axes.Axes.indicate_inset_zoom
 
   Zoom region inset axes
matplotlib.axes.Axes.inset_axes   Axes.inset_axes(bounds, *, transform=None, zorder=5, **kwargs)[source]
 
Add a child inset Axes to this existing Axes.  Parameters 
 
bounds[x0, y0, width, height]


Lower-left corner of inset Axes, and its width and height.  
transformTransform


Defaults to ax.transAxes, i.e. the units of rect are in Axes-relative coordinates.  
zordernumber


Defaults to 5 (same as Axes.legend). Adjust higher or lower to change whether it is above or below data plotted on the parent Axes.  **kwargs

Other keyword arguments are passed on to the child Axes.    Returns 
 ax

The created Axes instance.      Warning This method is experimental as of 3.0, and the API may change.  Examples This example makes two inset Axes, the first is in Axes-relative coordinates, and the second in data-coordinates: fig, ax = plt.subplots()
ax.plot(range(10))
axin1 = ax.inset_axes([0.8, 0.1, 0.15, 0.15])
axin2 = ax.inset_axes(
        [5, 7, 2.3, 2.3], transform=ax.transData)
 
  Examples using matplotlib.axes.Axes.inset_axes
 
   Placing Colorbars   

   Zoom region inset axes
matplotlib.axes.Axes.invert_xaxis   Axes.invert_xaxis()[source]
 
Invert the x-axis.  See also  xaxis_inverted

get_xlim, set_xlim


get_xbound, set_xbound
matplotlib.axes.Axes.invert_yaxis   Axes.invert_yaxis()[source]
 
Invert the y-axis.  See also  yaxis_inverted

get_ylim, set_ylim


get_ybound, set_ybound

  
  Examples using matplotlib.axes.Axes.invert_yaxis
 
   Bar Label Demo   

   Horizontal bar chart   

   Marker reference
matplotlib.axes.Axes.locator_params   Axes.locator_params(axis='both', tight=None, **kwargs)[source]
 
Control behavior of major tick locators. Because the locator is involved in autoscaling, autoscale_view is called automatically after the parameters are changed.  Parameters 
 
axis{'both', 'x', 'y'}, default: 'both'


The axis on which to operate.  
tightbool or None, optional


Parameter passed to autoscale_view. Default is None, for no change.    Other Parameters 
 **kwargs

Remaining keyword arguments are passed to directly to the set_params() method of the locator. Supported keywords depend on the type of the locator. See for example set_params for the ticker.MaxNLocator used by default for linear axes.     Examples When plotting small subplots, one might want to reduce the maximum number of ticks and use tight bounds, for example: ax.locator_params(tight=True, nbins=4)
 
  Examples using matplotlib.axes.Axes.locator_params
 
   Contourf Demo   

   Constrained Layout Guide   

   Tight Layout guide
matplotlib.axes.Axes.loglog   Axes.loglog(*args, **kwargs)[source]
 
Make a plot with log scaling on both the x and y axis. Call signatures: loglog([x], y, [fmt], data=None, **kwargs)
loglog([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
 This is just a thin wrapper around plot which additionally changes both the x-axis and the y-axis to log scaling. All of the concepts and parameters of plot can be used here as well. The additional parameters base, subs and nonpositive control the x/y-axis properties. They are just forwarded to Axes.set_xscale and Axes.set_yscale. To use different properties on the x-axis and the y-axis, use e.g. ax.set_xscale("log", base=10); ax.set_yscale("log", base=2).  Parameters 
 
basefloat, default: 10


Base of the logarithm.  
subssequence, optional


The location of the minor ticks. If None, reasonable locations are automatically chosen depending on the number of decades in the plot. See Axes.set_xscale/Axes.set_yscale for details.  
nonpositive{'mask', 'clip'}, default: 'mask'


Non-positive values can be masked as invalid, or clipped to a very small positive number.  **kwargs

All parameters supported by plot.    Returns 
 list of Line2D


Objects representing the plotted data.     
  Examples using matplotlib.axes.Axes.loglog
 
   Secondary Axis   

   Log Demo
matplotlib.axes.Axes.margins   Axes.margins(*margins, x=None, y=None, tight=True)[source]
 
Set or retrieve autoscaling margins. The padding added to each limit of the Axes is the margin times the data interval. All input parameters must be floats within the range [0, 1]. Passing both positional and keyword arguments is invalid and will raise a TypeError. If no arguments (positional or otherwise) are provided, the current margins will remain in place and simply be returned. Specifying any margin changes only the autoscaling; for example, if xmargin is not None, then xmargin times the X data interval will be added to each end of that interval before it is used in autoscaling.  Parameters 
 
*marginsfloat, optional


If a single positional argument is provided, it specifies both margins of the x-axis and y-axis limits. If two positional arguments are provided, they will be interpreted as xmargin, ymargin. If setting the margin on a single axis is desired, use the keyword arguments described below.  
x, yfloat, optional


Specific margin values for the x-axis and y-axis, respectively. These cannot be used with positional arguments, but can be used individually to alter on e.g., only the y-axis.  
tightbool or None, default: True


The tight parameter is passed to autoscale_view(), which is executed after a margin is changed; the default here is True, on the assumption that when margins are specified, no additional padding to match tick marks is usually desired. Set tight to None will preserve the previous setting.    Returns 
 
xmargin, ymarginfloat

   Notes If a previously used Axes method such as pcolor() has set use_sticky_edges to True, only the limits not set by the "sticky artists" will be modified. To force all of the margins to be set, set use_sticky_edges to False before calling margins(). 
  Examples using matplotlib.axes.Axes.margins
 
   Marker reference   

   Creating a timeline with lines, dates, and text   

   Trigradient Demo   

   Controlling view limits using margins and sticky_edges   

   Scale invariant angle label   

   ggplot style sheet   

   Autoscaling
matplotlib.axes.Axes.matshow   Axes.matshow(Z, **kwargs)[source]
 
Plot the values of a 2D matrix or array as color-coded image. The matrix will be shown the way it would be printed, with the first row at the top. Row and column numbering is zero-based.  Parameters 
 
Z(M, N) array-like


The matrix to be displayed.    Returns 
 AxesImage
  Other Parameters 
 
**kwargsimshow arguments

    See also  imshow

More general function to plot data on a 2D regular raster.    Notes This is just a convenience function wrapping imshow to set useful defaults for displaying a matrix. In particular:  Set origin='upper'. Set interpolation='nearest'. Set aspect='equal'. Ticks are placed to the left and above. Ticks are formatted to show integer indices.
matplotlib.axes.Axes.minorticks_off   Axes.minorticks_off()[source]
 
Remove minor ticks from the Axes.
matplotlib.axes.Axes.minorticks_on   Axes.minorticks_on()[source]
 
Display minor ticks on the Axes. Displaying minor ticks may reduce performance; you may turn them off using minorticks_off() if drawing speed is a problem. 
  Examples using matplotlib.axes.Axes.minorticks_on
 
   MRI With EEG
matplotlib.axes.Axes.mouseover   propertyAxes.mouseover
 
If this property is set to True, the artist will be queried for custom context information when the mouse cursor moves over it. See also get_cursor_data(), ToolCursorPosition and NavigationToolbar2.
matplotlib.axes.Axes.pchanged   Axes.pchanged()[source]
 
Call all of the registered callbacks. This function is triggered internally when a property is changed.  See also  add_callback
remove_callback
matplotlib.axes.Axes.quiverkey   Axes.quiverkey(Q, X, Y, U, label, **kwargs)[source]
 
Add a key to a quiver plot. The positioning of the key depends on X, Y, coordinates, and labelpos. If labelpos is 'N' or 'S', X, Y give the position of the middle of the key arrow. If labelpos is 'E', X, Y positions the head, and if labelpos is 'W', X, Y positions the tail; in either of these two cases, X, Y is somewhere in the middle of the arrow+label key object.  Parameters 
 
Qmatplotlib.quiver.Quiver


A Quiver object as returned by a call to quiver().  
X, Yfloat


The location of the key.  
Ufloat


The length of the key.  
labelstr


The key label (e.g., length and units of the key).  
anglefloat, default: 0


The angle of the key arrow, in degrees anti-clockwise from the x-axis.  
coordinates{'axes', 'figure', 'data', 'inches'}, default: 'axes'


Coordinate system and units for X, Y: 'axes' and 'figure' are normalized coordinate systems with (0, 0) in the lower left and (1, 1) in the upper right; 'data' are the axes data coordinates (used for the locations of the vectors in the quiver plot itself); 'inches' is position in the figure in inches, with (0, 0) at the lower left corner.  
colorcolor


Overrides face and edge colors from Q.  
labelpos{'N', 'S', 'E', 'W'}


Position the label above, below, to the right, to the left of the arrow, respectively.  
labelsepfloat, default: 0.1


Distance in inches between the arrow and the label.  
labelcolorcolor, default: rcParams["text.color"] (default: 'black')


Label color.  
fontpropertiesdict, optional


A dictionary with keyword arguments accepted by the FontProperties initializer: family, style, variant, size, weight.  **kwargs

Any additional keyword arguments are used to override vector properties taken from Q.     
  Examples using matplotlib.axes.Axes.quiverkey
 
   Advanced quiver and quiverkey functions   

   Quiver Simple Demo
matplotlib.axes.Axes.redraw_in_frame   Axes.redraw_in_frame()[source]
 
Efficiently redraw Axes data, but not axis ticks, labels, etc. This method can only be used after an initial draw which caches the renderer.
matplotlib.axes.Axes.relim   Axes.relim(visible_only=False)[source]
 
Recompute the data limits based on current artists. At present, Collection instances are not supported.  Parameters 
 
visible_onlybool, default: False


Whether to exclude invisible artists.     
  Examples using matplotlib.axes.Axes.relim
 
   Packed-bubble chart   

   Textbox
matplotlib.axes.Axes.remove_callback   Axes.remove_callback(oid)[source]
 
Remove a callback based on its observer id.  See also  add_callback
matplotlib.axes.Axes.reset_position   Axes.reset_position()[source]
 
Reset the active position to the original position. This resets the a possible position change due to aspect constraints. For an explanation of the positions see set_position.
matplotlib.axes.Axes.secondary_xaxis   Axes.secondary_xaxis(location, *, functions=None, **kwargs)[source]
 
Add a second x-axis to this Axes. For example if we want to have a second scale for the data plotted on the xaxis.  Parameters 
 
location{'top', 'bottom', 'left', 'right'} or float


The position to put the secondary axis. Strings can be 'top' or 'bottom' for orientation='x' and 'right' or 'left' for orientation='y'. A float indicates the relative position on the parent axes to put the new axes, 0.0 being the bottom (or left) and 1.0 being the top (or right).  
functions2-tuple of func, or Transform with an inverse


If a 2-tuple of functions, the user specifies the transform function and its inverse. i.e. functions=(lambda x: 2 / x, lambda x: 2 / x) would be an reciprocal transform with a factor of 2. The user can also directly supply a subclass of transforms.Transform so long as it has an inverse. See Secondary Axis for examples of making these conversions.    Returns 
 
axaxes._secondary_axes.SecondaryAxis

  Other Parameters 
 
**kwargsAxes properties.


Other miscellaneous axes parameters.      Warning This method is experimental as of 3.1, and the API may change.  Examples The main axis shows frequency, and the secondary axis shows period. (Source code, png, pdf)    
  Examples using matplotlib.axes.Axes.secondary_xaxis
 
   Secondary Axis   

   Basic Usage
matplotlib.axes.Axes.secondary_yaxis   Axes.secondary_yaxis(location, *, functions=None, **kwargs)[source]
 
Add a second y-axis to this Axes. For example if we want to have a second scale for the data plotted on the yaxis.  Parameters 
 
location{'top', 'bottom', 'left', 'right'} or float


The position to put the secondary axis. Strings can be 'top' or 'bottom' for orientation='x' and 'right' or 'left' for orientation='y'. A float indicates the relative position on the parent axes to put the new axes, 0.0 being the bottom (or left) and 1.0 being the top (or right).  
functions2-tuple of func, or Transform with an inverse


If a 2-tuple of functions, the user specifies the transform function and its inverse. i.e. functions=(lambda x: 2 / x, lambda x: 2 / x) would be an reciprocal transform with a factor of 2. The user can also directly supply a subclass of transforms.Transform so long as it has an inverse. See Secondary Axis for examples of making these conversions.    Returns 
 
axaxes._secondary_axes.SecondaryAxis

  Other Parameters 
 
**kwargsAxes properties.


Other miscellaneous axes parameters.      Warning This method is experimental as of 3.1, and the API may change.  Examples Add a secondary Axes that converts from radians to degrees (Source code, png, pdf)    
  Examples using matplotlib.axes.Axes.secondary_yaxis
 
   Secondary Axis
matplotlib.axes.Axes.semilogx   Axes.semilogx(*args, **kwargs)[source]
 
Make a plot with log scaling on the x axis. Call signatures: semilogx([x], y, [fmt], data=None, **kwargs)
semilogx([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
 This is just a thin wrapper around plot which additionally changes the x-axis to log scaling. All of the concepts and parameters of plot can be used here as well. The additional parameters base, subs, and nonpositive control the x-axis properties. They are just forwarded to Axes.set_xscale.  Parameters 
 
basefloat, default: 10


Base of the x logarithm.  
subsarray-like, optional


The location of the minor xticks. If None, reasonable locations are automatically chosen depending on the number of decades in the plot. See Axes.set_xscale for details.  
nonpositive{'mask', 'clip'}, default: 'mask'


Non-positive values in x can be masked as invalid, or clipped to a very small positive number.  **kwargs

All parameters supported by plot.    Returns 
 list of Line2D


Objects representing the plotted data.     
  Examples using matplotlib.axes.Axes.semilogx
 
   Log Demo   

   Log Axis   

   Transformations Tutorial
matplotlib.axes.Axes.semilogy   Axes.semilogy(*args, **kwargs)[source]
 
Make a plot with log scaling on the y axis. Call signatures: semilogy([x], y, [fmt], data=None, **kwargs)
semilogy([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)
 This is just a thin wrapper around plot which additionally changes the y-axis to log scaling. All of the concepts and parameters of plot can be used here as well. The additional parameters base, subs, and nonpositive control the y-axis properties. They are just forwarded to Axes.set_yscale.  Parameters 
 
basefloat, default: 10


Base of the y logarithm.  
subsarray-like, optional


The location of the minor yticks. If None, reasonable locations are automatically chosen depending on the number of decades in the plot. See Axes.set_yscale for details.  
nonpositive{'mask', 'clip'}, default: 'mask'


Non-positive values in y can be masked as invalid, or clipped to a very small positive number.  **kwargs

All parameters supported by plot.    Returns 
 list of Line2D


Objects representing the plotted data.     
  Examples using matplotlib.axes.Axes.semilogy
 
   Log Demo   

   SkewT-logP diagram: using transforms and custom projections
matplotlib.axes.Axes.set_adjustable   Axes.set_adjustable(adjustable, share=False)[source]
 
Set how the Axes adjusts to achieve the required aspect ratio.  Parameters 
 
adjustable{'box', 'datalim'}


If 'box', change the physical dimensions of the Axes. If 'datalim', change the x or y data limits.  
sharebool, default: False


If True, apply the settings to all shared Axes.      See also  matplotlib.axes.Axes.set_aspect

For a description of aspect handling.    Notes Shared Axes (of which twinned Axes are a special case) impose restrictions on how aspect ratios can be imposed. For twinned Axes, use 'datalim'. For Axes that share both x and y, use 'box'. Otherwise, either 'datalim' or 'box' may be used. These limitations are partly a requirement to avoid over-specification, and partly a result of the particular implementation we are currently using, in which the adjustments for aspect ratios are done sequentially and independently on each Axes as it is drawn. 
  Examples using matplotlib.axes.Axes.set_adjustable
 
   Loglog Aspect
matplotlib.axes.Axes.set_anchor   Axes.set_anchor(anchor, share=False)[source]
 
Define the anchor location. The actual drawing area (active position) of the Axes may be smaller than the Bbox (original position) when a fixed aspect is required. The anchor defines where the drawing area will be located within the available space.  Parameters 
 
anchor(float, float) or {'C', 'SW', 'S', 'SE', 'E', 'NE', ...}


Either an (x, y) pair of relative coordinates (0 is left or bottom, 1 is right or top), 'C' (center), or a cardinal direction ('SW', southwest, is bottom left, etc.). str inputs are shorthands for (x, y) coordinates, as shown in the following table: .. code-block:: none
  
'NW' (0.0, 1.0) 'N' (0.5, 1.0) 'NE' (1.0, 1.0)  
'W' (0.0, 0.5) 'C' (0.5, 0.5) 'E' (1.0, 0.5)  
'SW' (0.0, 0.0) 'S' (0.5, 0.0) 'SE' (1.0, 0.0)    
sharebool, default: False


If True, apply the settings to all shared Axes.      See also  matplotlib.axes.Axes.set_aspect

for a description of aspect handling.
matplotlib.axes.Axes.set_aspect   Axes.set_aspect(aspect, adjustable=None, anchor=None, share=False)[source]
 
Set the aspect ratio of the axes scaling, i.e. y/x-scale.  Parameters 
 
aspect{'auto', 'equal'} or float


Possible values:  'auto': fill the position rectangle with data. 'equal': same as aspect=1, i.e. same scaling for x and y. 
float: The displayed size of 1 unit in y-data coordinates will be aspect times the displayed size of 1 unit in x-data coordinates; e.g. for aspect=2 a square in data coordinates will be rendered with a height of twice its width.   
adjustableNone or {'box', 'datalim'}, optional


If not None, this defines which parameter will be adjusted to meet the required aspect. See set_adjustable for further details.  
anchorNone or str or (float, float), optional


If not None, this defines where the Axes will be drawn if there is extra space due to aspect constraints. The most common way to to specify the anchor are abbreviations of cardinal directions:   
value description   
'C' centered  
'SW' lower left corner  
'S' middle of bottom edge  
'SE' lower right corner  
etc.    See set_anchor for further details.  
sharebool, default: False


If True, apply the settings to all shared Axes.      See also  matplotlib.axes.Axes.set_adjustable

Set how the Axes adjusts to achieve the required aspect ratio.  matplotlib.axes.Axes.set_anchor

Set the position in case of extra space.    
  Examples using matplotlib.axes.Axes.set_aspect
 
   Bar chart with gradients   

   Streamplot   

   Tricontour Demo   

   Tricontour Smooth Delaunay   

   Tricontour Smooth User   

   Trigradient Demo   

   Tripcolor Demo   

   Triplot Demo   

   Axes box aspect   

   Controlling view limits using margins and sticky_edges   

   Placing Colorbars   

   Multiline   

   Mmh Donuts!!!   

   Inset Locator Demo2   

   Scatter Histogram (Locatable Axes)   

   Simple Anchored Artists   

   axis_direction demo   

   Simple Axis Pad   

   The double pendulum problem   

   Anchored Artists   

   Rasterization for vector graphics   

   Loglog Aspect   

   Annotate Text Arrow   

   Transformations Tutorial   

   Colormap Normalization
matplotlib.axes.Axes.set_autoscale_on   Axes.set_autoscale_on(b)[source]
 
Set whether autoscaling is applied to each axis on the next draw or call to Axes.autoscale_view.  Parameters 
 
bbool

   
  Examples using matplotlib.axes.Axes.set_autoscale_on
 
   Resampling Data
matplotlib.axes.Axes.set_autoscalex_on   Axes.set_autoscalex_on(b)[source]
 
Set whether the x-axis is autoscaled on the next draw or call to Axes.autoscale_view.  Parameters 
 
bbool
matplotlib.axes.Axes.set_autoscaley_on   Axes.set_autoscaley_on(b)[source]
 
Set whether the y-axis is autoscaled on the next draw or call to Axes.autoscale_view.  Parameters 
 
bbool