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matplotlib.fontconfig_pattern.generate_fontconfig_pattern(d)[source]
Given a dictionary of key/value pairs, generates a fontconfig pattern string. | matplotlib.fontconfig_pattern_api#matplotlib.fontconfig_pattern.generate_fontconfig_pattern |
matplotlib.fontconfig_pattern.parse_fontconfig_pattern(pattern)[source]
Parse the given fontconfig pattern and return a dictionary of key/value pairs useful for initializing a font_manager.FontProperties object. | matplotlib.fontconfig_pattern_api#matplotlib.fontconfig_pattern.parse_fontconfig_pattern |
matplotlib.fontconfig_pattern.value_escape(/, repl, string, count=0)
Return the string obtained by replacing the leftmost non-overlapping occurrences of pattern in string by the replacement repl. | matplotlib.fontconfig_pattern_api#matplotlib.fontconfig_pattern.value_escape |
matplotlib.fontconfig_pattern.value_unescape(/, repl, string, count=0)
Return the string obtained by replacing the leftmost non-overlapping occurrences of pattern in string by the replacement repl. | matplotlib.fontconfig_pattern_api#matplotlib.fontconfig_pattern.value_unescape |
matplotlib.get_backend()[source]
Return the name of the current backend. See also matplotlib.use | matplotlib_configuration_api#matplotlib.get_backend |
matplotlib.get_cachedir()[source]
Return the string path of the cache directory. The procedure used to find the directory is the same as for _get_config_dir, except using $XDG_CACHE_HOME/$HOME/.cache instead. | matplotlib_configuration_api#matplotlib.get_cachedir |
matplotlib.get_configdir()[source]
Return the string path of the configuration directory. The directory is chosen as follows: If the MPLCONFIGDIR environment variable is supplied, choose that. On Linux, follow the XDG specification and look first in $XDG_CONFIG_HOME, if defined, or $HOME/.config. On other platforms,... | matplotlib_configuration_api#matplotlib.get_configdir |
matplotlib.get_data_path()[source]
Return the path to Matplotlib data. | matplotlib_configuration_api#matplotlib.get_data_path |
matplotlib.gridspec gridspec contains classes that help to layout multiple Axes in a grid-like pattern within a figure. The GridSpec specifies the overall grid structure. Individual cells within the grid are referenced by SubplotSpecs. Often, users need not access this module directly, and can use higher-level methods ... | matplotlib.gridspec_api |
matplotlib.gridspec.GridSpec classmatplotlib.gridspec.GridSpec(nrows, ncols, figure=None, left=None, bottom=None, right=None, top=None, wspace=None, hspace=None, width_ratios=None, height_ratios=None)[source]
Bases: matplotlib.gridspec.GridSpecBase A grid layout to place subplots within a figure. The location of th... | matplotlib._as_gen.matplotlib.gridspec.gridspec |
get_subplot_params(figure=None)[source]
Return the SubplotParams for the GridSpec. In order of precedence the values are taken from non-None attributes of the GridSpec the provided figure
rcParams["figure.subplot.*"] | matplotlib._as_gen.matplotlib.gridspec.gridspec#matplotlib.gridspec.GridSpec.get_subplot_params |
locally_modified_subplot_params()[source]
Return a list of the names of the subplot parameters explicitly set in the GridSpec. This is a subset of the attributes of SubplotParams. | matplotlib._as_gen.matplotlib.gridspec.gridspec#matplotlib.gridspec.GridSpec.locally_modified_subplot_params |
tight_layout(figure, renderer=None, pad=1.08, h_pad=None, w_pad=None, rect=None)[source]
Adjust subplot parameters to give specified padding. Parameters
padfloat
Padding between the figure edge and the edges of subplots, as a fraction of the font-size.
h_pad, w_padfloat, optional
Padding (height/width) betw... | matplotlib._as_gen.matplotlib.gridspec.gridspec#matplotlib.gridspec.GridSpec.tight_layout |
update(**kwargs)[source]
Update the subplot parameters of the grid. Parameters that are not explicitly given are not changed. Setting a parameter to None resets it to rcParams["figure.subplot.*"]. Parameters
left, right, top, bottomfloat or None, optional
Extent of the subplots as a fraction of figure width or ... | matplotlib._as_gen.matplotlib.gridspec.gridspec#matplotlib.gridspec.GridSpec.update |
matplotlib.gridspec.GridSpecBase classmatplotlib.gridspec.GridSpecBase(nrows, ncols, height_ratios=None, width_ratios=None)[source]
Bases: object A base class of GridSpec that specifies the geometry of the grid that a subplot will be placed. Parameters
nrows, ncolsint
The number of rows and columns of the gri... | matplotlib._as_gen.matplotlib.gridspec.gridspecbase |
get_geometry()[source]
Return a tuple containing the number of rows and columns in the grid. | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.get_geometry |
get_grid_positions(fig, raw=False)[source]
Return the positions of the grid cells in figure coordinates. Parameters
figFigure
The figure the grid should be applied to. The subplot parameters (margins and spacing between subplots) are taken from fig.
rawbool, default: False
If True, the subplot parameters of... | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.get_grid_positions |
get_height_ratios()[source]
Return the height ratios. This is None if no height ratios have been set explicitly. | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.get_height_ratios |
get_subplot_params(figure=None)[source] | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.get_subplot_params |
get_width_ratios()[source]
Return the width ratios. This is None if no width ratios have been set explicitly. | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.get_width_ratios |
new_subplotspec(loc, rowspan=1, colspan=1)[source]
Create and return a SubplotSpec instance. Parameters
loc(int, int)
The position of the subplot in the grid as (row_index, column_index).
rowspan, colspanint, default: 1
The number of rows and columns the subplot should span in the grid. | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.new_subplotspec |
set_height_ratios(height_ratios)[source]
Set the relative heights of the rows. height_ratios must be of length nrows. Each row gets a relative height of height_ratios[i] / sum(height_ratios). | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.set_height_ratios |
set_width_ratios(width_ratios)[source]
Set the relative widths of the columns. width_ratios must be of length ncols. Each column gets a relative width of width_ratios[i] / sum(width_ratios). | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.set_width_ratios |
subplots(*, sharex=False, sharey=False, squeeze=True, subplot_kw=None)[source]
Add all subplots specified by this GridSpec to its parent figure. See Figure.subplots for detailed documentation. | matplotlib._as_gen.matplotlib.gridspec.gridspecbase#matplotlib.gridspec.GridSpecBase.subplots |
matplotlib.gridspec.GridSpecFromSubplotSpec classmatplotlib.gridspec.GridSpecFromSubplotSpec(nrows, ncols, subplot_spec, wspace=None, hspace=None, height_ratios=None, width_ratios=None)[source]
Bases: matplotlib.gridspec.GridSpecBase GridSpec whose subplot layout parameters are inherited from the location specified... | matplotlib._as_gen.matplotlib.gridspec.gridspecfromsubplotspec |
get_subplot_params(figure=None)[source]
Return a dictionary of subplot layout parameters. | matplotlib._as_gen.matplotlib.gridspec.gridspecfromsubplotspec#matplotlib.gridspec.GridSpecFromSubplotSpec.get_subplot_params |
get_topmost_subplotspec()[source]
Return the topmost SubplotSpec instance associated with the subplot. | matplotlib._as_gen.matplotlib.gridspec.gridspecfromsubplotspec#matplotlib.gridspec.GridSpecFromSubplotSpec.get_topmost_subplotspec |
matplotlib.gridspec.SubplotSpec classmatplotlib.gridspec.SubplotSpec(gridspec, num1, num2=None)[source]
Bases: object The location of a subplot in a GridSpec. Note Likely, you'll never instantiate a SubplotSpec yourself. Instead you will typically obtain one from a GridSpec using item-access. Parameters
grids... | matplotlib._as_gen.matplotlib.gridspec.subplotspec |
get_geometry()[source]
Return the subplot geometry as tuple (n_rows, n_cols, start, stop). The indices start and stop define the range of the subplot within the GridSpec. stop is inclusive (i.e. for a single cell start == stop). | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.get_geometry |
get_gridspec()[source] | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.get_gridspec |
get_position(figure, return_all=<deprecated parameter>)[source]
Update the subplot position from figure.subplotpars. | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.get_position |
get_topmost_subplotspec()[source]
Return the topmost SubplotSpec instance associated with the subplot. | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.get_topmost_subplotspec |
is_first_col()[source] | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.is_first_col |
is_first_row()[source] | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.is_first_row |
is_last_col()[source] | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.is_last_col |
is_last_row()[source] | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.is_last_row |
subgridspec(nrows, ncols, **kwargs)[source]
Create a GridSpec within this subplot. The created GridSpecFromSubplotSpec will have this SubplotSpec as a parent. Parameters
nrowsint
Number of rows in grid.
ncolsint
Number or columns in grid. Returns
GridSpecFromSubplotSpec
Other Parameters
**kwargs
A... | matplotlib._as_gen.matplotlib.gridspec.subplotspec#matplotlib.gridspec.SubplotSpec.subgridspec |
matplotlib.image The image module supports basic image loading, rescaling and display operations. classmatplotlib.image.AxesImage(ax, cmap=None, norm=None, interpolation=None, origin=None, extent=None, filternorm=True, filterrad=4.0, resample=False, *, interpolation_stage=None, **kwargs)[source]
Bases: matplotlib.i... | matplotlib.image_api |
classmatplotlib.image.AxesImage(ax, cmap=None, norm=None, interpolation=None, origin=None, extent=None, filternorm=True, filterrad=4.0, resample=False, *, interpolation_stage=None, **kwargs)[source]
Bases: matplotlib.image._ImageBase An image attached to an Axes. Parameters
axAxes
The axes the image will belong... | matplotlib.image_api#matplotlib.image.AxesImage |
get_cursor_data(event)[source]
Return the image value at the event position or None if the event is outside the image. See also matplotlib.artist.Artist.get_cursor_data | matplotlib.image_api#matplotlib.image.AxesImage.get_cursor_data |
get_extent()[source]
Return the image extent as tuple (left, right, bottom, top). | matplotlib.image_api#matplotlib.image.AxesImage.get_extent |
get_window_extent(renderer=None)[source]
Get the artist's bounding box in display space. The bounding box' width and height are nonnegative. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0. Be careful when using this function, the re... | matplotlib.image_api#matplotlib.image.AxesImage.get_window_extent |
make_image(renderer, magnification=1.0, unsampled=False)[source]
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N,... | matplotlib.image_api#matplotlib.image.AxesImage.make_image |
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, array=<UNSET>, clim=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, cmap=<UNSET>, data=<UNSET>, extent=<UNSET>, filternorm=<UNSET>, filterrad=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, interpolation=<UNSET>, interpolation_stage=<UNSET>, label=<UNS... | matplotlib.image_api#matplotlib.image.AxesImage.set |
set_extent(extent)[source]
Set the image extent. Parameters
extent4-tuple of float
The position and size of the image as tuple (left, right, bottom, top) in data coordinates. Notes This updates ax.dataLim, and, if autoscaling, sets ax.viewLim to tightly fit the image, regardless of dataLim. Autoscaling stat... | matplotlib.image_api#matplotlib.image.AxesImage.set_extent |
classmatplotlib.image.BboxImage(bbox, cmap=None, norm=None, interpolation=None, origin=None, filternorm=True, filterrad=4.0, resample=False, **kwargs)[source]
Bases: matplotlib.image._ImageBase The Image class whose size is determined by the given bbox. cmap is a colors.Colormap instance norm is a colors.Normalize in... | matplotlib.image_api#matplotlib.image.BboxImage |
contains(mouseevent)[source]
Test whether the mouse event occurred within the image. | matplotlib.image_api#matplotlib.image.BboxImage.contains |
get_window_extent(renderer=None)[source]
Get the artist's bounding box in display space. The bounding box' width and height are nonnegative. Subclasses should override for inclusion in the bounding box "tight" calculation. Default is to return an empty bounding box at 0, 0. Be careful when using this function, the re... | matplotlib.image_api#matplotlib.image.BboxImage.get_window_extent |
make_image(renderer, magnification=1.0, unsampled=False)[source]
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N,... | matplotlib.image_api#matplotlib.image.BboxImage.make_image |
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, array=<UNSET>, clim=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, cmap=<UNSET>, data=<UNSET>, filternorm=<UNSET>, filterrad=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, interpolation=<UNSET>, interpolation_stage=<UNSET>, label=<UNSET>, norm=<UNSET... | matplotlib.image_api#matplotlib.image.BboxImage.set |
matplotlib.image.composite_images(images, renderer, magnification=1.0)[source]
Composite a number of RGBA images into one. The images are composited in the order in which they appear in the images list. Parameters
imageslist of Images
Each must have a make_image method. For each image, can_composite should retu... | matplotlib.image_api#matplotlib.image.composite_images |
classmatplotlib.image.FigureImage(fig, cmap=None, norm=None, offsetx=0, offsety=0, origin=None, **kwargs)[source]
Bases: matplotlib.image._ImageBase An image attached to a figure. cmap is a colors.Colormap instance norm is a colors.Normalize instance to map luminance to 0-1 kwargs are an optional list of Artist keywo... | matplotlib.image_api#matplotlib.image.FigureImage |
get_extent()[source]
Return the image extent as tuple (left, right, bottom, top). | matplotlib.image_api#matplotlib.image.FigureImage.get_extent |
make_image(renderer, magnification=1.0, unsampled=False)[source]
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N,... | matplotlib.image_api#matplotlib.image.FigureImage.make_image |
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, array=<UNSET>, clim=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, cmap=<UNSET>, data=<UNSET>, filternorm=<UNSET>, filterrad=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, interpolation=<UNSET>, interpolation_stage=<UNSET>, label=<UNSET>, norm=<UNSET... | matplotlib.image_api#matplotlib.image.FigureImage.set |
set_data(A)[source]
Set the image array. | matplotlib.image_api#matplotlib.image.FigureImage.set_data |
zorder=0 | matplotlib.image_api#matplotlib.image.FigureImage.zorder |
matplotlib.image.imread(fname, format=None)[source]
Read an image from a file into an array. Note This function exists for historical reasons. It is recommended to use PIL.Image.open instead for loading images. Parameters
fnamestr or file-like
The image file to read: a filename, a URL or a file-like object op... | matplotlib.image_api#matplotlib.image.imread |
matplotlib.image.imsave(fname, arr, vmin=None, vmax=None, cmap=None, format=None, origin=None, dpi=100, *, metadata=None, pil_kwargs=None)[source]
Save an array as an image file. Parameters
fnamestr or path-like or file-like
A path or a file-like object to store the image in. If format is not set, then the outp... | matplotlib.image_api#matplotlib.image.imsave |
classmatplotlib.image.NonUniformImage(ax, *, interpolation='nearest', **kwargs)[source]
Bases: matplotlib.image.AxesImage Parameters
interpolation{'nearest', 'bilinear'}, default: 'nearest'
**kwargs
All other keyword arguments are identical to those of AxesImage. get_extent()[source]
Return the image ex... | matplotlib.image_api#matplotlib.image.NonUniformImage |
get_extent()[source]
Return the image extent as tuple (left, right, bottom, top). | matplotlib.image_api#matplotlib.image.NonUniformImage.get_extent |
make_image(renderer, magnification=1.0, unsampled=False)[source]
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N,... | matplotlib.image_api#matplotlib.image.NonUniformImage.make_image |
mouseover=False | matplotlib.image_api#matplotlib.image.NonUniformImage.mouseover |
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, array=<UNSET>, clim=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, cmap=<UNSET>, data=<UNSET>, extent=<UNSET>, filternorm=<UNSET>, filterrad=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, interpolation=<UNSET>, interpolation_stage=<UNSET>, label=<UNS... | matplotlib.image_api#matplotlib.image.NonUniformImage.set |
set_array(*args)[source]
Retained for backwards compatibility - use set_data instead. Parameters
Aarray-like | matplotlib.image_api#matplotlib.image.NonUniformImage.set_array |
set_cmap(cmap)[source]
Set the colormap for luminance data. Parameters
cmapColormap or str or None | matplotlib.image_api#matplotlib.image.NonUniformImage.set_cmap |
set_data(x, y, A)[source]
Set the grid for the pixel centers, and the pixel values. Parameters
x, y1D array-like
Monotonic arrays of shapes (N,) and (M,), respectively, specifying pixel centers.
Aarray-like
(M, N) ndarray or masked array of values to be colormapped, or (M, N, 3) RGB array, or (M, N, 4) RGBA... | matplotlib.image_api#matplotlib.image.NonUniformImage.set_data |
set_filternorm(s)[source]
Set whether the resize filter normalizes the weights. See help for imshow. Parameters
filternormbool | matplotlib.image_api#matplotlib.image.NonUniformImage.set_filternorm |
set_filterrad(s)[source]
Set the resize filter radius only applicable to some interpolation schemes -- see help for imshow Parameters
filterradpositive float | matplotlib.image_api#matplotlib.image.NonUniformImage.set_filterrad |
set_interpolation(s)[source]
Parameters
s{'nearest', 'bilinear'} or None
If None, use rcParams["image.interpolation"] (default: 'antialiased'). | matplotlib.image_api#matplotlib.image.NonUniformImage.set_interpolation |
set_norm(norm)[source]
Set the normalization instance. Parameters
normNormalize or None
Notes If there are any colorbars using the mappable for this norm, setting the norm of the mappable will reset the norm, locator, and formatters on the colorbar to default. | matplotlib.image_api#matplotlib.image.NonUniformImage.set_norm |
classmatplotlib.image.PcolorImage(ax, x=None, y=None, A=None, cmap=None, norm=None, **kwargs)[source]
Bases: matplotlib.image.AxesImage Make a pcolor-style plot with an irregular rectangular grid. This uses a variation of the original irregular image code, and it is used by pcolorfast for the corresponding grid type.... | matplotlib.image_api#matplotlib.image.PcolorImage |
get_cursor_data(event)[source]
Return the image value at the event position or None if the event is outside the image. See also matplotlib.artist.Artist.get_cursor_data | matplotlib.image_api#matplotlib.image.PcolorImage.get_cursor_data |
make_image(renderer, magnification=1.0, unsampled=False)[source]
Normalize, rescale, and colormap this image's data for rendering using renderer, with the given magnification. If unsampled is True, the image will not be scaled, but an appropriate affine transformation will be returned instead. Returns
image(M, N,... | matplotlib.image_api#matplotlib.image.PcolorImage.make_image |
set(*, agg_filter=<UNSET>, alpha=<UNSET>, animated=<UNSET>, array=<UNSET>, clim=<UNSET>, clip_box=<UNSET>, clip_on=<UNSET>, clip_path=<UNSET>, cmap=<UNSET>, data=<UNSET>, extent=<UNSET>, filternorm=<UNSET>, filterrad=<UNSET>, gid=<UNSET>, in_layout=<UNSET>, interpolation=<UNSET>, interpolation_stage=<UNSET>, label=<UNS... | matplotlib.image_api#matplotlib.image.PcolorImage.set |
set_array(*args)[source]
Retained for backwards compatibility - use set_data instead. Parameters
Aarray-like | matplotlib.image_api#matplotlib.image.PcolorImage.set_array |
set_data(x, y, A)[source]
Set the grid for the rectangle boundaries, and the data values. Parameters
x, y1D array-like, optional
Monotonic arrays of length N+1 and M+1, respectively, specifying rectangle boundaries. If not given, will default to range(N + 1) and range(M + 1), respectively.
Aarray-like
The d... | matplotlib.image_api#matplotlib.image.PcolorImage.set_data |
matplotlib.image.pil_to_array(pilImage)[source]
Load a PIL image and return it as a numpy int array. Returns
numpy.array
The array shape depends on the image type: (M, N) for grayscale images. (M, N, 3) for RGB images. (M, N, 4) for RGBA images. | matplotlib.image_api#matplotlib.image.pil_to_array |
matplotlib.image.thumbnail(infile, thumbfile, scale=0.1, interpolation='bilinear', preview=False)[source]
Make a thumbnail of image in infile with output filename thumbfile. See Image Thumbnail. Parameters
infilestr or file-like
The image file. Matplotlib relies on Pillow for image reading, and thus supports a ... | matplotlib.image_api#matplotlib.image.thumbnail |
matplotlib.interactive(b)[source]
Set whether to redraw after every plotting command (e.g. pyplot.xlabel). | matplotlib_configuration_api#matplotlib.interactive |
matplotlib.is_interactive()[source]
Return whether to redraw after every plotting command. Note This function is only intended for use in backends. End users should use pyplot.isinteractive instead. | matplotlib_configuration_api#matplotlib.is_interactive |
matplotlib.legend The legend module defines the Legend class, which is responsible for drawing legends associated with axes and/or figures. Important It is unlikely that you would ever create a Legend instance manually. Most users would normally create a legend via the legend function. For more details on legends ther... | matplotlib.legend_api |
classmatplotlib.legend.DraggableLegend(legend, use_blit=False, update='loc')[source]
Bases: matplotlib.offsetbox.DraggableOffsetBox Wrapper around a Legend to support mouse dragging. Parameters
legendLegend
The Legend instance to wrap.
use_blitbool, optional
Use blitting for faster image composition. For de... | matplotlib.legend_api#matplotlib.legend.DraggableLegend |
finalize_offset()[source] | matplotlib.legend_api#matplotlib.legend.DraggableLegend.finalize_offset |
classmatplotlib.legend.Legend(parent, handles, labels, loc=None, numpoints=None, markerscale=None, markerfirst=True, scatterpoints=None, scatteryoffsets=None, prop=None, fontsize=None, labelcolor=None, borderpad=None, labelspacing=None, handlelength=None, handleheight=None, handletextpad=None, borderaxespad=None, colum... | matplotlib.legend_api#matplotlib.legend.Legend |
codes={'best': 0, 'center': 10, 'center left': 6, 'center right': 7, 'lower center': 8, 'lower left': 3, 'lower right': 4, 'right': 5, 'upper center': 9, 'upper left': 2, 'upper right': 1} | matplotlib.legend_api#matplotlib.legend.Legend.codes |
contains(event)[source]
Test whether the artist contains the mouse event. Parameters
mouseeventmatplotlib.backend_bases.MouseEvent
Returns
containsbool
Whether any values are within the radius.
detailsdict
An artist-specific dictionary of details of the event context, such as which points are containe... | matplotlib.legend_api#matplotlib.legend.Legend.contains |
draw(renderer)[source]
Draw the Artist (and its children) using the given renderer. This has no effect if the artist is not visible (Artist.get_visible returns False). Parameters
rendererRendererBase subclass.
Notes This method is overridden in the Artist subclasses. | matplotlib.legend_api#matplotlib.legend.Legend.draw |
draw_frame(b)[source]
Set whether the legend box patch is drawn. Parameters
bbool | matplotlib.legend_api#matplotlib.legend.Legend.draw_frame |
get_bbox_to_anchor()[source]
Return the bbox that the legend will be anchored to. | matplotlib.legend_api#matplotlib.legend.Legend.get_bbox_to_anchor |
get_children()[source]
Return a list of the child Artists of this Artist. | matplotlib.legend_api#matplotlib.legend.Legend.get_children |
classmethodget_default_handler_map()[source]
A class method that returns the default handler map. | matplotlib.legend_api#matplotlib.legend.Legend.get_default_handler_map |
get_draggable()[source]
Return True if the legend is draggable, False otherwise. | matplotlib.legend_api#matplotlib.legend.Legend.get_draggable |
get_frame()[source]
Return the Rectangle used to frame the legend. | matplotlib.legend_api#matplotlib.legend.Legend.get_frame |
get_frame_on()[source]
Get whether the legend box patch is drawn. | matplotlib.legend_api#matplotlib.legend.Legend.get_frame_on |
staticget_legend_handler(legend_handler_map, orig_handle)[source]
Return a legend handler from legend_handler_map that corresponds to orig_handler. legend_handler_map should be a dictionary object (that is returned by the get_legend_handler_map method). It first checks if the orig_handle itself is a key in the legend... | matplotlib.legend_api#matplotlib.legend.Legend.get_legend_handler |
get_legend_handler_map()[source]
Return the handler map. | matplotlib.legend_api#matplotlib.legend.Legend.get_legend_handler_map |
get_lines()[source]
Return the list of Line2Ds in the legend. | matplotlib.legend_api#matplotlib.legend.Legend.get_lines |
get_patches()[source]
Return the list of Patchs in the legend. | matplotlib.legend_api#matplotlib.legend.Legend.get_patches |
get_texts()[source]
Return the list of Texts in the legend. | matplotlib.legend_api#matplotlib.legend.Legend.get_texts |
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