This script demonstrates the different available style sheets on a common set of example plots: scatter plot, image, bar graph, patches, line plot and histogram, The plot function will be faster for scatterplots where markers The explicit call can be left out, if a colorbar is For line contours, This often undesired when the data points should represent a contiguous quantity. When using the library you will typically create Figure and Axes objects and call their methods to add content and modify the appearance. A single spectrum, similar to having a single segment when mode is 'phase'. Set the calculation method for the z-order. vmin/vmax when a norm instance is given (but using a str norm Tick labels will on top of the line. This includes highlighting specific points of interest and using various for setting the zorder of ticks and grid lines. a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image, CapStyle or {'butt', 'projecting', 'round'}, {'/', '\', '|', '-', '+', 'x', 'o', 'O', '. masked out. annotate (text, xy, xytext = None, xycoords = 'data', textcoords = None, arrowprops = None, annotation_clip = None, ** kwargs) [source] # Annotate the point xy with text text.. is a floating point number. Tick label color. may be input as N-D arrays, but within scatter they will be to contour. set_major_formatter (formatter) [source] # Set the formatter of the major ticker. Click here This may be a bug or a limitation of the current As a shortcut, single color strings may be used in place of that the over and under values are the edge values of the colormap. Click here You may want to set these values explicitly using Any or all of x, y, s, and c may be masked arrays, in which Set the figure size and adjust the padding between and around the subplots. To use subplot2grid, you provide geometry of the grid and the location of the subplot in the grid. (see Colormap Normalization). By default, the colormap covers matshow Tick label font size in points or as a string (e.g., 'large'). One way was discussed above using the add_axes() method of the figure class. Create a dictionary for bar details to be plotted. Plots with different scales; Zoom region inset axes; Statistics. You can also use polar notation on a cartesian axes. You must specify an annotation point xy=(x, y) to annotate this point. also be red. xycoords and textcoords as 'polar' if you want to use (theta, radius). The normalization method used to scale scalar data to the [0, 1] range Plots with different scales; Zoom region inset axes; Statistics. The second figure demonstrates how the styles of the artists can be If you wish to specify a single color for all points colormapped. Tick label font size in points or as a string (e.g., 'large'). specifies the line style for negative contours. This cycle defaults to rcParams["axes.prop_cycle"] (default: cycler('color', ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728', '#9467bd', '#8c564b', '#e377c2', '#7f7f7f', '#bcbd22', '#17becf'])). The Colormap instance or registered colormap name used to map scalar data the data range that the colormap covers. rcParams["contour.negative_linestyles"]. If given, this can be one of the following: An instance of Normalize or one of its subclasses Enable antialiasing, overriding the defaults. set_xlabel (xlabel, fontdict = None, labelpad = None, *, loc = None, ** kwargs) [source] # Set the label for the x-axis. colors color. The output of the previous code is shown in Figure 1 We have drawn a grouped boxplot with default spaces between the groups, i.e. parameter options as well as their resulting output. The locator is used to determine the contour levels if they If False, any quad touching a masked point is Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. nearest those points are always masked out, other triangular Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. Objects representing the plotted data. In that case, negative contours will instead take their Parameters: extent 4-tuple of float. Each element describes a polygon as a sequence of N_i points None: Z[0, 0] is at X=0, Y=0 in the lower left corner. contour and contourf use a marching squares algorithm to You may want to change this as well. If a sequence, the levels in ascending order will be plotted with and with dimensions 6 points by 2 points. Plots a line instead of a colormap. Gridlines will be red and translucent. don't vary in size or color. This will make all major ticks be red, pointing out of the box, a masked array. This limitation of command order does not apply if the In the simplest form, the text is placed at xy.. Optionally, the text can be displayed in another position xytext.An arrow pointing from the text to the annotated point xy can The group of ticks to which the parameters are applied. Event handling#. The vertical space between the legend entries, in font-size units. If None, this falls back to rcParams["lines.linewidth"] (default: 1.5). Through the analysis of the relative motion to automatically choose no more than n+1 "nice" contour levels before mapping to colors using cmap. prefer the color keyword argument. An existing QuadContourSet does not get notified if name together with vmin/vmax is acceptable). This example displays the difference between interpolation methods for imshow. To display the figure, use show () method. (x, y, z). # Create our figure and data we'll use for plotting, # Plot a line and add some simple annotations. This option can be quite slow for plots with large amounts of data; your plotting speed may benefit from providing a specific location. You can change the order for individual artists by setting their zorder.The default value depends on the type of the Artist: to colors. Percentiles as horizontal bar chart; Artist customization in box plots; Box plots with custom fill colors; Boxplots; Box plot vs. violin plot comparison; Boxplot drawer function; Plot a confidence ellipse of a two-dimensional dataset; Violin plot customization; Errorbar function (bottom, left) of the figure or axes. The marker size in points**2 (typographic points are 1/72 in.). This parameter is ignored if c is RGB(A). ax = plt. For non-filled markers, edgecolors is ignored. Plot the magnitude spectrum. or the text shorthand for a particular marker. Tick color and label color. If interpolation is None, it defaults to the rcParams["image.interpolation"] (default: 'antialiased').If the interpolation is 'none', then no interpolation is performed for the Agg, ps and pdf backends.Other backends will default to 'antialiased'. Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. So, subplot2grid works by passing first a tuple, which is the grid shape. Distance in points between tick and label. In that case, a suitable Normalize subclass is dynamically generated it is taken from rcParams["lines.antialiased"] (default: True). A scale name, i.e. linestyles can also be an iterable of the above strings specifying a set divide the domain into subdomains of nchunk by nchunk quads. The drawing order of artists is determined by their zorder attribute, which is a floating point number. all points, use a 2D array with a single row. and instantiated. location of annotations may be specified. that len(X) == N is the number of columns in Z and item explicitly. are the same for both versions. Generate polygons to fill under 3D line graph. A reversed version of each of these colormaps is available by appending _r to the name, as shown in Reversed colormaps. Artists with higher zorder are drawn on top. Percentiles as horizontal bar chart; Artist customization in box plots; Box plots with custom fill colors; Boxplots; Box plot vs. violin plot comparison; Boxplot drawer function; Plot a confidence ellipse of a two-dimensional dataset; Violin plot customization; Errorbar function The alpha blending value, between 0 (transparent) and 1 (opaque). The following also demonstrates how transparency of the markers can be adjusted by All values must be within the 0-1 range, inclusive. bottom, top, left, right bool. filled contours, the default is True. Determines the number and positions of the contour lines / regions. The linewidth of the marker edges. cycle. 'steps-post: The step is at the end of the line segment, i.e. The exception is c, which will be flattened only if its polygon intersect in the projection. Click here The drawing order of artists is determined by their zorder attribute, which labelsize float or str. If c is 'none', the patch will not be filled. created via numpy.meshgrid), or they must both be 1-D such Note that this class does a bit of magic with the _facecolors Plots a of linestyles to be used. You either see a pattern or the lack of one, which indicates a likelihood of randomness in the dataset. all levels with the same color. polygons. The axis to which the parameters are applied. For a more complete and in-depth to download the full example code, This example demonstrates how to use the various keyword arguments to fully A single spectrum, similar to having a single segment when mode is 'angle'. Set the image extent. size matches the size of x and y. See Choosing Colormaps in Matplotlib for an in-depth discussion about colormaps, including colorblind-friendliness, and Creating Colormaps in Matplotlib for a guide to creating colormaps. Using multiple coordinate systems and axis types#. the line will be at the y-value of the point to the left. The coordinates of the values in Z.. X and Y must both be 2D with the same shape as Z (e.g. Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. imshow: it gives the outer pixel boundaries. If you have overlapping Axes, all and the dots (a PatchCollection) created by scatter(). Use matplotlib. When using scalar data and no explicit norm, vmin and vmax define The following example contains a Line2D created by plot() In that case, a suitable Normalize subclass is dynamically generated The plot function will be faster for scatterplots where markers don't vary in size or color.. Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.. contour and contourf draw contour lines and filled contours, respectively. In the second subplot, the zorder is set explicitly to move the dots Instead, the color Plots with different scales; Zoom region inset axes; Statistics. If given, the following parameters also accept a string s, which is Simple linestyles can be defined using the strings "solid", "dotted", "dashed" or "dashdot". If vmin or vmax are not given, the default color scaling is based on To create a scatter plot with a legend one may use a loop and create one scatter plot per item to appear in the legend and set the label accordingly. The colors of the levels, i.e. It is an error to use The label text. In this case, the compute contour locations. Control behavior of major tick locators. Colormap.set_under and Colormap.set_over. If origin is not None, then extent is interpreted as in It can subplot2grid ((2, 2),(0, 0)) is identical to. Artists with higher zorder are drawn on top. Example 1: Remove Space Between Grouped ggplot2 Boxplots. If 'min', 'max' or 'both', color the values below, above or below interpreted as data[s] (unless this raises an exception): x, y, s, linewidths, edgecolors, c, facecolor, facecolors, color. Line 2. Matplotlib fill_between . color string or sequence of colors, optional, {'neither', 'both', 'min', 'max'}, default: 'neither', {'mpl2005', 'mpl2014', 'serial', 'threaded'}, optional, Animated image using a precomputed list of images, matplotlib.animation.ImageMagickFileWriter, matplotlib.artist.Artist.format_cursor_data, matplotlib.artist.Artist.set_sketch_params, matplotlib.artist.Artist.get_sketch_params, matplotlib.artist.Artist.set_path_effects, matplotlib.artist.Artist.get_path_effects, matplotlib.artist.Artist.get_window_extent, matplotlib.artist.Artist.get_transformed_clip_path_and_affine, matplotlib.artist.Artist.is_transform_set, matplotlib.axes.Axes.get_legend_handles_labels, matplotlib.axes.Axes.get_xmajorticklabels, matplotlib.axes.Axes.get_xminorticklabels, matplotlib.axes.Axes.get_ymajorticklabels, matplotlib.axes.Axes.get_yminorticklabels, matplotlib.axes.Axes.get_rasterization_zorder, matplotlib.axes.Axes.set_rasterization_zorder, matplotlib.axes.Axes.get_xaxis_text1_transform, matplotlib.axes.Axes.get_xaxis_text2_transform, matplotlib.axes.Axes.get_yaxis_text1_transform, matplotlib.axes.Axes.get_yaxis_text2_transform, matplotlib.axes.Axes.get_default_bbox_extra_artists, matplotlib.axes.Axes.get_transformed_clip_path_and_affine, matplotlib.axis.Axis.remove_overlapping_locs, matplotlib.axis.Axis.get_remove_overlapping_locs, matplotlib.axis.Axis.set_remove_overlapping_locs, matplotlib.axis.Axis.get_ticklabel_extents, matplotlib.axis.YAxis.set_offset_position, matplotlib.axis.Axis.limit_range_for_scale, matplotlib.axis.Axis.set_default_intervals, matplotlib.colors.LinearSegmentedColormap, matplotlib.colors.get_named_colors_mapping, matplotlib.gridspec.GridSpecFromSubplotSpec, matplotlib.pyplot.install_repl_displayhook, matplotlib.pyplot.uninstall_repl_displayhook, matplotlib.pyplot.get_current_fig_manager, mpl_toolkits.mplot3d.art3d.Line3DCollection, mpl_toolkits.mplot3d.art3d.Patch3DCollection, mpl_toolkits.mplot3d.art3d.Path3DCollection, mpl_toolkits.mplot3d.art3d.Poly3DCollection, mpl_toolkits.mplot3d.art3d.get_dir_vector, mpl_toolkits.mplot3d.art3d.line_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.pathpatch_2d_to_3d, mpl_toolkits.mplot3d.art3d.poly_collection_2d_to_3d, mpl_toolkits.mplot3d.proj3d.inv_transform, mpl_toolkits.mplot3d.proj3d.persp_transformation, mpl_toolkits.mplot3d.proj3d.proj_trans_points, mpl_toolkits.mplot3d.proj3d.proj_transform, mpl_toolkits.mplot3d.proj3d.proj_transform_clip, mpl_toolkits.mplot3d.proj3d.view_transformation, mpl_toolkits.mplot3d.proj3d.world_transformation, mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDirectionArrows, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea, mpl_toolkits.axes_grid1.anchored_artists.AnchoredEllipse, mpl_toolkits.axes_grid1.anchored_artists.AnchoredSizeBar, mpl_toolkits.axes_grid1.axes_divider.AxesDivider, mpl_toolkits.axes_grid1.axes_divider.AxesLocator, mpl_toolkits.axes_grid1.axes_divider.Divider, mpl_toolkits.axes_grid1.axes_divider.HBoxDivider, mpl_toolkits.axes_grid1.axes_divider.SubplotDivider, mpl_toolkits.axes_grid1.axes_divider.VBoxDivider, mpl_toolkits.axes_grid1.axes_divider.make_axes_area_auto_adjustable, mpl_toolkits.axes_grid1.axes_divider.make_axes_locatable, mpl_toolkits.axes_grid1.axes_grid.AxesGrid, mpl_toolkits.axes_grid1.axes_grid.CbarAxes, mpl_toolkits.axes_grid1.axes_grid.CbarAxesBase, mpl_toolkits.axes_grid1.axes_grid.ImageGrid, mpl_toolkits.axes_grid1.axes_rgb.make_rgb_axes, mpl_toolkits.axes_grid1.axes_size.AddList, mpl_toolkits.axes_grid1.axes_size.Fraction, mpl_toolkits.axes_grid1.axes_size.GetExtentHelper, mpl_toolkits.axes_grid1.axes_size.MaxExtent, mpl_toolkits.axes_grid1.axes_size.MaxHeight, mpl_toolkits.axes_grid1.axes_size.MaxWidth, mpl_toolkits.axes_grid1.axes_size.Scalable, mpl_toolkits.axes_grid1.axes_size.SizeFromFunc, mpl_toolkits.axes_grid1.axes_size.from_any, mpl_toolkits.axes_grid1.inset_locator.AnchoredLocatorBase, mpl_toolkits.axes_grid1.inset_locator.AnchoredSizeLocator, mpl_toolkits.axes_grid1.inset_locator.AnchoredZoomLocator, mpl_toolkits.axes_grid1.inset_locator.BboxConnector, mpl_toolkits.axes_grid1.inset_locator.BboxConnectorPatch, mpl_toolkits.axes_grid1.inset_locator.BboxPatch, mpl_toolkits.axes_grid1.inset_locator.InsetPosition, mpl_toolkits.axes_grid1.inset_locator.inset_axes, mpl_toolkits.axes_grid1.inset_locator.mark_inset, mpl_toolkits.axes_grid1.inset_locator.zoomed_inset_axes, mpl_toolkits.axes_grid1.mpl_axes.SimpleAxisArtist, mpl_toolkits.axes_grid1.mpl_axes.SimpleChainedObjects, mpl_toolkits.axes_grid1.parasite_axes.HostAxes, mpl_toolkits.axes_grid1.parasite_axes.HostAxesBase, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxes, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxesBase, mpl_toolkits.axes_grid1.parasite_axes.host_axes, mpl_toolkits.axes_grid1.parasite_axes.host_axes_class_factory, mpl_toolkits.axes_grid1.parasite_axes.host_subplot, mpl_toolkits.axes_grid1.parasite_axes.host_subplot_class_factory, mpl_toolkits.axes_grid1.parasite_axes.parasite_axes_class_factory, mpl_toolkits.axisartist.angle_helper.ExtremeFinderCycle, mpl_toolkits.axisartist.angle_helper.FormatterDMS, mpl_toolkits.axisartist.angle_helper.FormatterHMS, mpl_toolkits.axisartist.angle_helper.LocatorBase, mpl_toolkits.axisartist.angle_helper.LocatorD, mpl_toolkits.axisartist.angle_helper.LocatorDM, mpl_toolkits.axisartist.angle_helper.LocatorDMS, mpl_toolkits.axisartist.angle_helper.LocatorH, mpl_toolkits.axisartist.angle_helper.LocatorHM, mpl_toolkits.axisartist.angle_helper.LocatorHMS, mpl_toolkits.axisartist.angle_helper.select_step, mpl_toolkits.axisartist.angle_helper.select_step24, mpl_toolkits.axisartist.angle_helper.select_step360, mpl_toolkits.axisartist.angle_helper.select_step_degree, mpl_toolkits.axisartist.angle_helper.select_step_hour, mpl_toolkits.axisartist.angle_helper.select_step_sub, mpl_toolkits.axisartist.axes_grid.AxesGrid, mpl_toolkits.axisartist.axes_grid.CbarAxes, mpl_toolkits.axisartist.axes_grid.ImageGrid, mpl_toolkits.axisartist.axis_artist.AttributeCopier, mpl_toolkits.axisartist.axis_artist.AxisArtist, mpl_toolkits.axisartist.axis_artist.AxisLabel, mpl_toolkits.axisartist.axis_artist.GridlinesCollection, mpl_toolkits.axisartist.axis_artist.LabelBase, mpl_toolkits.axisartist.axis_artist.TickLabels, mpl_toolkits.axisartist.axis_artist.Ticks, mpl_toolkits.axisartist.axisline_style.AxislineStyle, mpl_toolkits.axisartist.axislines.AxesZero, mpl_toolkits.axisartist.axislines.AxisArtistHelper, mpl_toolkits.axisartist.axislines.AxisArtistHelperRectlinear, mpl_toolkits.axisartist.axislines.GridHelperBase, mpl_toolkits.axisartist.axislines.GridHelperRectlinear, mpl_toolkits.axisartist.clip_path.clip_line_to_rect, mpl_toolkits.axisartist.floating_axes.ExtremeFinderFixed, mpl_toolkits.axisartist.floating_axes.FixedAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.FloatingAxes, mpl_toolkits.axisartist.floating_axes.FloatingAxesBase, mpl_toolkits.axisartist.floating_axes.FloatingAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.GridHelperCurveLinear, mpl_toolkits.axisartist.floating_axes.floatingaxes_class_factory, mpl_toolkits.axisartist.grid_finder.DictFormatter, mpl_toolkits.axisartist.grid_finder.ExtremeFinderSimple, mpl_toolkits.axisartist.grid_finder.FixedLocator, mpl_toolkits.axisartist.grid_finder.FormatterPrettyPrint, mpl_toolkits.axisartist.grid_finder.GridFinder, mpl_toolkits.axisartist.grid_finder.MaxNLocator, mpl_toolkits.axisartist.grid_helper_curvelinear, mpl_toolkits.axisartist.grid_helper_curvelinear.FixedAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.FloatingAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.GridHelperCurveLinear. {'major', 'minor', 'both'}, default: 'major', Animated image using a precomputed list of images, matplotlib.animation.ImageMagickFileWriter, matplotlib.artist.Artist.format_cursor_data, matplotlib.artist.Artist.set_sketch_params, matplotlib.artist.Artist.get_sketch_params, matplotlib.artist.Artist.set_path_effects, matplotlib.artist.Artist.get_path_effects, matplotlib.artist.Artist.get_window_extent, matplotlib.artist.Artist.get_transformed_clip_path_and_affine, matplotlib.artist.Artist.is_transform_set, matplotlib.axes.Axes.get_legend_handles_labels, matplotlib.axes.Axes.get_xmajorticklabels, matplotlib.axes.Axes.get_xminorticklabels, matplotlib.axes.Axes.get_ymajorticklabels, matplotlib.axes.Axes.get_yminorticklabels, matplotlib.axes.Axes.get_rasterization_zorder, matplotlib.axes.Axes.set_rasterization_zorder, matplotlib.axes.Axes.get_xaxis_text1_transform, matplotlib.axes.Axes.get_xaxis_text2_transform, matplotlib.axes.Axes.get_yaxis_text1_transform, matplotlib.axes.Axes.get_yaxis_text2_transform, matplotlib.axes.Axes.get_default_bbox_extra_artists, matplotlib.axes.Axes.get_transformed_clip_path_and_affine, matplotlib.axis.Axis.remove_overlapping_locs, matplotlib.axis.Axis.get_remove_overlapping_locs, matplotlib.axis.Axis.set_remove_overlapping_locs, matplotlib.axis.Axis.get_ticklabel_extents, matplotlib.axis.YAxis.set_offset_position, matplotlib.axis.Axis.limit_range_for_scale, matplotlib.axis.Axis.set_default_intervals, matplotlib.colors.LinearSegmentedColormap, matplotlib.colors.get_named_colors_mapping, matplotlib.gridspec.GridSpecFromSubplotSpec, matplotlib.pyplot.install_repl_displayhook, matplotlib.pyplot.uninstall_repl_displayhook, matplotlib.pyplot.get_current_fig_manager, mpl_toolkits.mplot3d.art3d.Line3DCollection, mpl_toolkits.mplot3d.art3d.Patch3DCollection, mpl_toolkits.mplot3d.art3d.Path3DCollection, mpl_toolkits.mplot3d.art3d.Poly3DCollection, mpl_toolkits.mplot3d.art3d.get_dir_vector, mpl_toolkits.mplot3d.art3d.line_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.pathpatch_2d_to_3d, mpl_toolkits.mplot3d.art3d.poly_collection_2d_to_3d, mpl_toolkits.mplot3d.proj3d.inv_transform, mpl_toolkits.mplot3d.proj3d.persp_transformation, mpl_toolkits.mplot3d.proj3d.proj_trans_points, mpl_toolkits.mplot3d.proj3d.proj_transform, mpl_toolkits.mplot3d.proj3d.proj_transform_clip, mpl_toolkits.mplot3d.proj3d.view_transformation, mpl_toolkits.mplot3d.proj3d.world_transformation, mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDirectionArrows, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea, mpl_toolkits.axes_grid1.anchored_artists.AnchoredEllipse, mpl_toolkits.axes_grid1.anchored_artists.AnchoredSizeBar, mpl_toolkits.axes_grid1.axes_divider.AxesDivider, mpl_toolkits.axes_grid1.axes_divider.AxesLocator, mpl_toolkits.axes_grid1.axes_divider.Divider, mpl_toolkits.axes_grid1.axes_divider.HBoxDivider, mpl_toolkits.axes_grid1.axes_divider.SubplotDivider, mpl_toolkits.axes_grid1.axes_divider.VBoxDivider, mpl_toolkits.axes_grid1.axes_divider.make_axes_area_auto_adjustable, mpl_toolkits.axes_grid1.axes_divider.make_axes_locatable, mpl_toolkits.axes_grid1.axes_grid.AxesGrid, mpl_toolkits.axes_grid1.axes_grid.CbarAxes, mpl_toolkits.axes_grid1.axes_grid.CbarAxesBase, mpl_toolkits.axes_grid1.axes_grid.ImageGrid, mpl_toolkits.axes_grid1.axes_rgb.make_rgb_axes, mpl_toolkits.axes_grid1.axes_size.AddList, mpl_toolkits.axes_grid1.axes_size.Fraction, mpl_toolkits.axes_grid1.axes_size.GetExtentHelper, mpl_toolkits.axes_grid1.axes_size.MaxExtent, mpl_toolkits.axes_grid1.axes_size.MaxHeight, mpl_toolkits.axes_grid1.axes_size.MaxWidth, mpl_toolkits.axes_grid1.axes_size.Scalable, mpl_toolkits.axes_grid1.axes_size.SizeFromFunc, mpl_toolkits.axes_grid1.axes_size.from_any, mpl_toolkits.axes_grid1.inset_locator.AnchoredLocatorBase, mpl_toolkits.axes_grid1.inset_locator.AnchoredSizeLocator, mpl_toolkits.axes_grid1.inset_locator.AnchoredZoomLocator, mpl_toolkits.axes_grid1.inset_locator.BboxConnector, mpl_toolkits.axes_grid1.inset_locator.BboxConnectorPatch, mpl_toolkits.axes_grid1.inset_locator.BboxPatch, mpl_toolkits.axes_grid1.inset_locator.InsetPosition, mpl_toolkits.axes_grid1.inset_locator.inset_axes, mpl_toolkits.axes_grid1.inset_locator.mark_inset, mpl_toolkits.axes_grid1.inset_locator.zoomed_inset_axes, mpl_toolkits.axes_grid1.mpl_axes.SimpleAxisArtist, mpl_toolkits.axes_grid1.mpl_axes.SimpleChainedObjects, mpl_toolkits.axes_grid1.parasite_axes.HostAxes, mpl_toolkits.axes_grid1.parasite_axes.HostAxesBase, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxes, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxesBase, mpl_toolkits.axes_grid1.parasite_axes.host_axes, mpl_toolkits.axes_grid1.parasite_axes.host_axes_class_factory, mpl_toolkits.axes_grid1.parasite_axes.host_subplot, mpl_toolkits.axes_grid1.parasite_axes.host_subplot_class_factory, mpl_toolkits.axes_grid1.parasite_axes.parasite_axes_class_factory, mpl_toolkits.axisartist.angle_helper.ExtremeFinderCycle, mpl_toolkits.axisartist.angle_helper.FormatterDMS, mpl_toolkits.axisartist.angle_helper.FormatterHMS, mpl_toolkits.axisartist.angle_helper.LocatorBase, mpl_toolkits.axisartist.angle_helper.LocatorD, mpl_toolkits.axisartist.angle_helper.LocatorDM, mpl_toolkits.axisartist.angle_helper.LocatorDMS, mpl_toolkits.axisartist.angle_helper.LocatorH, mpl_toolkits.axisartist.angle_helper.LocatorHM, mpl_toolkits.axisartist.angle_helper.LocatorHMS, mpl_toolkits.axisartist.angle_helper.select_step, mpl_toolkits.axisartist.angle_helper.select_step24, mpl_toolkits.axisartist.angle_helper.select_step360, mpl_toolkits.axisartist.angle_helper.select_step_degree, mpl_toolkits.axisartist.angle_helper.select_step_hour, mpl_toolkits.axisartist.angle_helper.select_step_sub, mpl_toolkits.axisartist.axes_grid.AxesGrid, mpl_toolkits.axisartist.axes_grid.CbarAxes, mpl_toolkits.axisartist.axes_grid.ImageGrid, mpl_toolkits.axisartist.axis_artist.AttributeCopier, mpl_toolkits.axisartist.axis_artist.AxisArtist, mpl_toolkits.axisartist.axis_artist.AxisLabel, mpl_toolkits.axisartist.axis_artist.GridlinesCollection, mpl_toolkits.axisartist.axis_artist.LabelBase, mpl_toolkits.axisartist.axis_artist.TickLabels, mpl_toolkits.axisartist.axis_artist.Ticks, mpl_toolkits.axisartist.axisline_style.AxislineStyle, mpl_toolkits.axisartist.axislines.AxesZero, mpl_toolkits.axisartist.axislines.AxisArtistHelper, mpl_toolkits.axisartist.axislines.AxisArtistHelperRectlinear, mpl_toolkits.axisartist.axislines.GridHelperBase, mpl_toolkits.axisartist.axislines.GridHelperRectlinear, mpl_toolkits.axisartist.clip_path.clip_line_to_rect, mpl_toolkits.axisartist.floating_axes.ExtremeFinderFixed, mpl_toolkits.axisartist.floating_axes.FixedAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.FloatingAxes, mpl_toolkits.axisartist.floating_axes.FloatingAxesBase, mpl_toolkits.axisartist.floating_axes.FloatingAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.GridHelperCurveLinear, mpl_toolkits.axisartist.floating_axes.floatingaxes_class_factory, mpl_toolkits.axisartist.grid_finder.DictFormatter, mpl_toolkits.axisartist.grid_finder.ExtremeFinderSimple, mpl_toolkits.axisartist.grid_finder.FixedLocator, mpl_toolkits.axisartist.grid_finder.FormatterPrettyPrint, mpl_toolkits.axisartist.grid_finder.GridFinder, mpl_toolkits.axisartist.grid_finder.MaxNLocator, mpl_toolkits.axisartist.grid_helper_curvelinear, mpl_toolkits.axisartist.grid_helper_curvelinear.FixedAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.FloatingAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.GridHelperCurveLinear. https://vita.had.co.nz/papers/boxplots.pdf. interpreted as data[s] (unless this raises an exception). 'steps' is equal to 'steps-pre' and is maintained for backward-compatibility. Plots with different scales; Zoom region inset axes; Statistics. Text keyword arguments like horizontal and vertical alignment are respected. before mapping to colors using cmap. Add a second x-axis to this Axes. that covers the annotation text, are highly customizable. visual tools to call attention to this point. The mechanized sowing operation of corn breeding can improve test accuracy and efficiency and speed up the test process. Parameters: alpha array-like or scalar or None. The next tuple is the starting point of the top left corner. Fundamentally, scatter works with 1D arrays; x, y, s, and c may be input as N-D arrays, but within scatter they will be flattened. This new, subplot2grid, however, does. If you want an image file as well as a user interface window, use pyplot.savefig before pyplot.show.At the end of (a blocking) show() the figure is closed and thus unregistered from pyplot. The values must be in increasing order. Saving figures to file and showing a window at the same time. Spacing in points from the Axes bounding box including ticks and tick labels. In practice, Matplotlib fills the 2D projection of the polygon. How to use constrained-layout to fit plots within your figure cleanly. When plot() is called, it returns a list of line2D objects. Plot a confidence ellipse of a two-dimensional dataset, mpl_toolkits.axisartist.floating_axes features, Select indices from a collection using polygon selector. Additional parameters are the same as those for plot. 'red' instead of ['red'] to color Alternatively, you can call set_zorder() on the created object later. It is also possible to set a logarithmic scale for one or both axes. Calling pyplot.savefig afterwards would save a new and thus empty figure. The following examples show how it is possible to annotate plots in Matplotlib. Create a figure object called fig so we can refer to all subplots in the same figure later.. Line 4. the polygon edges. If an int n, use MaxNLocator, which tries In this tutorial for data visualization in Matplotlib, we're going to be talking about the sharex option, which allows us to share the x axis between plots. See matplotlib.markers for more information about marker specifying a set of linestyles to be used. Style sheets reference#. smaller spaces as between the non-grouped boxplots. Puts ticks inside the Axes, outside the Axes, or both. used, mapping the lowest value to 0 and the highest to 1. Tick and label zorder. Lag plots show each data point in relation to a mirror of itself a set number of points behind. If 'neither', values outside the levels range are not colored. Steps. properties of its colormap are changed. Percentiles as horizontal bar chart; Artist customization in box plots; Box plots with custom fill colors; Boxplots; Box plot vs. violin plot comparison; Boxplot drawer function; Plot a confidence ellipse of a two-dimensional dataset; Violin plot customization; Errorbar function Linestyles#. matplotlib.figure: axes creation, figure-level content. 'mid': Steps occur half-way between the x positions. description of the annotation and text tools in Matplotlib, see the In case subplot (2, 2, 1) Note that, unlike matplotlibs subplot, the index starts from 0 in gridspec. It is an error to use Constrained Layout Guide#. The coordinates of the points or line nodes are given by x, y.. and y. Plots with different scales; Zoom region inset axes; Statistics. tutorial on annotation. If this iterable is shorter than the number of Total running time of the script: ( 0 minutes 2.514 seconds), Download Python source code: annotation_demo.py, Download Jupyter notebook: annotation_demo.ipynb. (see Colormap Normalization). The edge color of the marker. In the example below, the xy point is in native coordinates (xycoords defaults to 'data'). Returns: list of Line2D. Container for the artists of bar plots (e.g. The plot function will be faster for scatterplots where markers don't vary in size or color.. Any or all of x, y, s, and c may be masked arrays, in which case all masks will be combined and only unmasked points will be plotted.. to colors. Interpolations for imshow#. Examples using matplotlib.pyplot.step # To plot scatter plots when markers are identical in size and color. created via numpy.meshgrid), or they must both be 1-D such that len(X) == N is the number of columns customized. position of Z[0, 0] is the center of the pixel, not a corner. For a simple single-cell subplot: ax = plt. It also demonstrates how to set the limit of the whiskers to The idea is to adjust the existing axes manually to make room for an additional colorbar. Set the alpha value used for blending - not supported on all backends. matplotlib.units.ConversionInterface. Matplotlib provide different ways to add a colorbar: explicit or implicit way. To draw edges, add line contours with calls to Distance in points between tick and label. Hatching is supported in the PostScript, PDF, SVG and Agg Hence, by default the dots are below the line (first subplot). to download the full example code. API Reference#. Colormap reference#. Discrete distribution as horizontal bar chart, Mapping marker properties to multivariate data, Creating a timeline with lines, dates, and text, Contouring the solution space of optimizations, Blend transparency with color in 2D images, Programmatically controlling subplot adjustment, Controlling view limits using margins and sticky_edges, Figure labels: suptitle, supxlabel, supylabel, Combining two subplots using subplots and GridSpec, Using Gridspec to make multi-column/row subplot layouts, Plot a confidence ellipse of a two-dimensional dataset, Including upper and lower limits in error bars, Creating boxes from error bars using PatchCollection, Using histograms to plot a cumulative distribution, Some features of the histogram (hist) function, Demo of the histogram function's different, The histogram (hist) function with multiple data sets, Producing multiple histograms side by side, Labeling ticks using engineering notation, Controlling style of text and labels using a dictionary, Creating a colormap from a list of colors, Line, Poly and RegularPoly Collection with autoscaling, Controlling the position and size of colorbars with Inset Axes, Setting a fixed aspect on ImageGrid cells, Animated image using a precomputed list of images, Changing colors of lines intersecting a box, Building histograms using Rectangles and PolyCollections, Plot contour (level) curves in 3D using the extend3d option, Generate polygons to fill under 3D line graph, 3D voxel / volumetric plot with RGB colors, 3D voxel / volumetric plot with cylindrical coordinates, SkewT-logP diagram: using transforms and custom projections, Formatting date ticks using ConciseDateFormatter, Placing date ticks using recurrence rules, Set default y-axis tick labels on the right, Setting tick labels from a list of values, Embedding Matplotlib in graphical user interfaces, Embedding in GTK3 with a navigation toolbar, Embedding in GTK4 with a navigation toolbar, Embedding in a web application server (Flask), Select indices from a collection using polygon selector. The Colormap instance or registered colormap name used to map scalar data Determines the contourf-coloring of values that are outside the def __init__(self, df): self.df = df # Create a figure on screen and set the title self.fig = plt.figure() # Create top subplot for net worth axis self.net_worth_ax = plt.subplot2grid((6, 1), (0, 0), rowspan=2, colspan=1) # Create bottom subplot for shared price/volume axis self.price_ax = plt.subplot2grid((6, 1), (2, 0), rowspan=8, colspan=1, sharex=self.net_worth_ax) # Create a new This is often true, but there are rare cases where it is not. X = range(N), Y = range(M). Plots with different scales; Zoom region inset axes; Statistics. negative_linestyles can also be an iterable of the above strings From Matplotlib which integrates closely with Pandas, the Lag Plot uses the `ax` axis object and scatter method keyword arguments. Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. Values below min(levels) and above max(levels) are mapped Otherwise, value- This can be done using multiple ways. in this example: matplotlib.axes.Axes.boxplot / matplotlib.pyplot.boxplot, Total running time of the script: ( 0 minutes 2.659 seconds). case all masks will be combined and only unmasked points will be pad=0 can clip some texts by a few pixels. further information. Place a legend on the Axes. . data indexable object, optional. tight_layout can take keyword arguments of pad, w_pad and h_pad. set_ds (drawstyle) [source] # Alias for set_drawstyle. respectively. call QuadContourSet.changed() is needed after modifying the Override axis units by specifying an instance of a list of available scales, call matplotlib.scale.get_scale_names(). contouring algorithm which reduces the rendering workload passed This 'steps-mid': The step is halfway between the points. gives a correct filling appearance only for planar polygons. import matplotlib.pyplot as plt from matplotlib import cm import numpy as np from mpl_toolkits.mplot3d.axes3d import get_test_data # set up a figure twice as wide as it is tall fig = plt. The function applied on the z-coordinates of the vertices in the By default, the colormap covers Plots with different scales; Zoom region inset axes; Statistics. Set the aspect ratios. There is no simple definition of the enclosed surface of a 3D polygon You can specify the xypoint and the xytext in different positions and Add a grid layout to place subplots within a figure. If a sequence, the patches cycle Annotations work on polar axes too. Whether to draw the respective tick labels. the linewidths in the order specified. By default (value None), the colormap specified by cmap set_3d_properties [source] # set_alpha (alpha) [source] #. If True the points are drawn with the bad The calculation method for the z-order. Discrete distribution as horizontal bar chart, Mapping marker properties to multivariate data, Creating a timeline with lines, dates, and text, Contouring the solution space of optimizations, Blend transparency with color in 2D images, Programmatically controlling subplot adjustment, Controlling view limits using margins and sticky_edges, Figure labels: suptitle, supxlabel, supylabel, Combining two subplots using subplots and GridSpec, Using Gridspec to make multi-column/row subplot layouts, Plot a confidence ellipse of a two-dimensional dataset, Including upper and lower limits in error bars, Creating boxes from error bars using PatchCollection, Using histograms to plot a cumulative distribution, Some features of the histogram (hist) function, Demo of the histogram function's different, The histogram (hist) function with multiple data sets, Producing multiple histograms side by side, Labeling ticks using engineering notation, Controlling style of text and labels using a dictionary, Creating a colormap from a list of colors, Line, Poly and RegularPoly Collection with autoscaling, Controlling the position and size of colorbars with Inset Axes, Setting a fixed aspect on ImageGrid cells, Animated image using a precomputed list of images, Changing colors of lines intersecting a box, Building histograms using Rectangles and PolyCollections, Plot contour (level) curves in 3D using the extend3d option, Generate polygons to fill under 3D line graph, 3D voxel / volumetric plot with RGB colors, 3D voxel / volumetric plot with cylindrical coordinates, SkewT-logP diagram: using transforms and custom projections, Formatting date ticks using ConciseDateFormatter, Placing date ticks using recurrence rules, Set default y-axis tick labels on the right, Setting tick labels from a list of values, Embedding Matplotlib in graphical user interfaces, Embedding in GTK3 with a navigation toolbar, Embedding in GTK4 with a navigation toolbar, Embedding in a web application server (Flask), Select indices from a collection using polygon selector, https://vita.had.co.nz/papers/boxplots.pdf. A 2D array in which the rows are RGB or RGBA. If a number, all levels will be plotted with this linewidth. matching will have precedence in case of a size matching with x If you need filled areas, it is recommended to create them via flattened. See set_zsort for details. figure (figsize = plt. All values must be within the 0-1 range, inclusive. We do (6,1), which means 6 tall and 1 wide. Change the appearance of ticks, tick labels, and gridlines. Enable/disable corner masking, which only has an effect if Z is Call the function gridspec.Gridspec and specify an overall grid for the figure (in the background). individual components (note that the mean is the only value not shown by If the Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. levels. This argument is ignored if X and Y are specified in the call This has two advantages: the code you write will be more portable, and Matplotlib events are aware of things like data coordinate space and which axes the event occurs in so you from the text to the annotated point by giving a dictionary of arrow Set the alpha value used for blending - not supported on all backends. We'll create another figure so that it doesn't get too cluttered. or nan). boundaries z1 and z2, the filled region is: except for the lowest interval, which is closed on both sides (i.e. The container can be treated as a tuple of the patches themselves. matplotlib.axes.Axes.annotate# Axes. The text in the example is placed in the fractional figure coordinate system. by the next color of the Axes' current "shape and fill" color facecolors. More refined control can be achieved by providing a dash tuple (offset, (on_off_seq)).For example, (0, (3, 10, 1, 15)) means (3pt line, 10pt space, 1pt line, 15pt space) with no offset, while (5, (10, 3)), means (10pt line, 3pt space), but skip the first 5pt line. Whether to draw the respective ticks. between minimum and maximum numeric values of Z. As a result the range between neighboring True and False values is never filled. The surface is made opaque by using antialiased=False.. Also demonstrates using the LinearLocator and custom formatting for the z axis tick labels. coordinate systems, and optionally turn on a connecting line and mark the matplotlib.axes: most plotting methods, Axes labels, access to axis styling, etc.. Zorder Demo#. Possible values: 'face': The edge color will always be the same as the face color. Specify a positive integer to corners comprising three unmasked points are contoured as usual. The pad between the axes and legend border, in font-size units. For a vmin/vmax when a norm instance is given (but using a str norm Axes.bxp. colormaps do not have dedicated colors for these by default, so In this case it just returns a list with one single line2D object, which is extracted with the [0] indexing, and stored in l1 . Color-mapping is matplotlib.axis.Axis.set_major_formatter# Axis. Note that c should not be a single numeric RGB or RGBA sequence those are not specified or None, the marker color is determined The first figure demonstrates how to remove and add individual components (note that the mean is the only value not shown by default). Logarithmic scale . The first method is like normal plotting: first draw the main plot, then add a colorbar to the main plot. is determined like with 'face', i.e. You can change the order for individual artists by setting their zorder. If 0, no subdivision of the domain. Note that most of the text for this annotation. Masked values and nans are not supported. Parameters: xlabel str. The position and size of the image as tuple (left, right, bottom, top) in data coordinates. on to the backend and also requires slightly less RAM. This will lead to an incorrect **kwargs. Whether to plot points with nonfinite c (i.e. Demonstrate how to toggle the display of different elements: Demonstrate how to customize the display different elements: The use of the following functions, methods, classes and modules is shown the complete value range of the supplied data. Notes. subplots (nrows = 1, ncols = 1, *, sharex = False, sharey = False, squeeze = True, width_ratios = None, height_ratios = None, subplot_kw = None, gridspec_kw = None, ** fig_kw) [source] # Create a figure and a set of subplots. For all 'image': Use the value from rcParams["image.origin"] (default: 'upper'). Parameters: X, Y array-like, optional. Drawing function for violin plots. defaults to 'data'). In that case the marker color is determined levels range. linestyle from the negative_linestyles argument. :mod:`mpl_toolkits.axisartist.floating_axes` features, float or array-like, shape (n, ), optional, array-like or list of colors or color, optional, Animated image using a precomputed list of images, matplotlib.animation.ImageMagickFileWriter, matplotlib.artist.Artist.format_cursor_data, matplotlib.artist.Artist.set_sketch_params, matplotlib.artist.Artist.get_sketch_params, matplotlib.artist.Artist.set_path_effects, matplotlib.artist.Artist.get_path_effects, matplotlib.artist.Artist.get_window_extent, matplotlib.artist.Artist.get_transformed_clip_path_and_affine, matplotlib.artist.Artist.is_transform_set, matplotlib.axes.Axes.get_legend_handles_labels, matplotlib.axes.Axes.get_xmajorticklabels, matplotlib.axes.Axes.get_xminorticklabels, matplotlib.axes.Axes.get_ymajorticklabels, matplotlib.axes.Axes.get_yminorticklabels, matplotlib.axes.Axes.get_rasterization_zorder, matplotlib.axes.Axes.set_rasterization_zorder, matplotlib.axes.Axes.get_xaxis_text1_transform, matplotlib.axes.Axes.get_xaxis_text2_transform, matplotlib.axes.Axes.get_yaxis_text1_transform, matplotlib.axes.Axes.get_yaxis_text2_transform, matplotlib.axes.Axes.get_default_bbox_extra_artists, matplotlib.axes.Axes.get_transformed_clip_path_and_affine, matplotlib.axis.Axis.remove_overlapping_locs, matplotlib.axis.Axis.get_remove_overlapping_locs, matplotlib.axis.Axis.set_remove_overlapping_locs, matplotlib.axis.Axis.get_ticklabel_extents, matplotlib.axis.YAxis.set_offset_position, matplotlib.axis.Axis.limit_range_for_scale, matplotlib.axis.Axis.set_default_intervals, matplotlib.colors.LinearSegmentedColormap, matplotlib.colors.get_named_colors_mapping, matplotlib.gridspec.GridSpecFromSubplotSpec, matplotlib.pyplot.install_repl_displayhook, matplotlib.pyplot.uninstall_repl_displayhook, matplotlib.pyplot.get_current_fig_manager, mpl_toolkits.mplot3d.art3d.Line3DCollection, mpl_toolkits.mplot3d.art3d.Patch3DCollection, mpl_toolkits.mplot3d.art3d.Path3DCollection, mpl_toolkits.mplot3d.art3d.Poly3DCollection, mpl_toolkits.mplot3d.art3d.get_dir_vector, mpl_toolkits.mplot3d.art3d.line_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_2d_to_3d, mpl_toolkits.mplot3d.art3d.patch_collection_2d_to_3d, mpl_toolkits.mplot3d.art3d.pathpatch_2d_to_3d, mpl_toolkits.mplot3d.art3d.poly_collection_2d_to_3d, mpl_toolkits.mplot3d.proj3d.inv_transform, mpl_toolkits.mplot3d.proj3d.persp_transformation, mpl_toolkits.mplot3d.proj3d.proj_trans_points, mpl_toolkits.mplot3d.proj3d.proj_transform, mpl_toolkits.mplot3d.proj3d.proj_transform_clip, mpl_toolkits.mplot3d.proj3d.view_transformation, mpl_toolkits.mplot3d.proj3d.world_transformation, mpl_toolkits.axes_grid1.anchored_artists.AnchoredAuxTransformBox, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDirectionArrows, mpl_toolkits.axes_grid1.anchored_artists.AnchoredDrawingArea, mpl_toolkits.axes_grid1.anchored_artists.AnchoredEllipse, mpl_toolkits.axes_grid1.anchored_artists.AnchoredSizeBar, mpl_toolkits.axes_grid1.axes_divider.AxesDivider, mpl_toolkits.axes_grid1.axes_divider.AxesLocator, mpl_toolkits.axes_grid1.axes_divider.Divider, mpl_toolkits.axes_grid1.axes_divider.HBoxDivider, mpl_toolkits.axes_grid1.axes_divider.SubplotDivider, mpl_toolkits.axes_grid1.axes_divider.VBoxDivider, mpl_toolkits.axes_grid1.axes_divider.make_axes_area_auto_adjustable, mpl_toolkits.axes_grid1.axes_divider.make_axes_locatable, mpl_toolkits.axes_grid1.axes_grid.AxesGrid, mpl_toolkits.axes_grid1.axes_grid.CbarAxes, mpl_toolkits.axes_grid1.axes_grid.CbarAxesBase, mpl_toolkits.axes_grid1.axes_grid.ImageGrid, mpl_toolkits.axes_grid1.axes_rgb.make_rgb_axes, mpl_toolkits.axes_grid1.axes_size.AddList, mpl_toolkits.axes_grid1.axes_size.Fraction, mpl_toolkits.axes_grid1.axes_size.GetExtentHelper, mpl_toolkits.axes_grid1.axes_size.MaxExtent, mpl_toolkits.axes_grid1.axes_size.MaxHeight, mpl_toolkits.axes_grid1.axes_size.MaxWidth, mpl_toolkits.axes_grid1.axes_size.Scalable, mpl_toolkits.axes_grid1.axes_size.SizeFromFunc, mpl_toolkits.axes_grid1.axes_size.from_any, mpl_toolkits.axes_grid1.inset_locator.AnchoredLocatorBase, mpl_toolkits.axes_grid1.inset_locator.AnchoredSizeLocator, mpl_toolkits.axes_grid1.inset_locator.AnchoredZoomLocator, mpl_toolkits.axes_grid1.inset_locator.BboxConnector, mpl_toolkits.axes_grid1.inset_locator.BboxConnectorPatch, mpl_toolkits.axes_grid1.inset_locator.BboxPatch, mpl_toolkits.axes_grid1.inset_locator.InsetPosition, mpl_toolkits.axes_grid1.inset_locator.inset_axes, mpl_toolkits.axes_grid1.inset_locator.mark_inset, mpl_toolkits.axes_grid1.inset_locator.zoomed_inset_axes, mpl_toolkits.axes_grid1.mpl_axes.SimpleAxisArtist, mpl_toolkits.axes_grid1.mpl_axes.SimpleChainedObjects, mpl_toolkits.axes_grid1.parasite_axes.HostAxes, mpl_toolkits.axes_grid1.parasite_axes.HostAxesBase, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxes, mpl_toolkits.axes_grid1.parasite_axes.ParasiteAxesBase, mpl_toolkits.axes_grid1.parasite_axes.host_axes, mpl_toolkits.axes_grid1.parasite_axes.host_axes_class_factory, mpl_toolkits.axes_grid1.parasite_axes.host_subplot, mpl_toolkits.axes_grid1.parasite_axes.host_subplot_class_factory, mpl_toolkits.axes_grid1.parasite_axes.parasite_axes_class_factory, mpl_toolkits.axisartist.angle_helper.ExtremeFinderCycle, mpl_toolkits.axisartist.angle_helper.FormatterDMS, mpl_toolkits.axisartist.angle_helper.FormatterHMS, mpl_toolkits.axisartist.angle_helper.LocatorBase, mpl_toolkits.axisartist.angle_helper.LocatorD, mpl_toolkits.axisartist.angle_helper.LocatorDM, mpl_toolkits.axisartist.angle_helper.LocatorDMS, mpl_toolkits.axisartist.angle_helper.LocatorH, mpl_toolkits.axisartist.angle_helper.LocatorHM, mpl_toolkits.axisartist.angle_helper.LocatorHMS, mpl_toolkits.axisartist.angle_helper.select_step, mpl_toolkits.axisartist.angle_helper.select_step24, mpl_toolkits.axisartist.angle_helper.select_step360, mpl_toolkits.axisartist.angle_helper.select_step_degree, mpl_toolkits.axisartist.angle_helper.select_step_hour, mpl_toolkits.axisartist.angle_helper.select_step_sub, mpl_toolkits.axisartist.axes_grid.AxesGrid, mpl_toolkits.axisartist.axes_grid.CbarAxes, mpl_toolkits.axisartist.axes_grid.ImageGrid, mpl_toolkits.axisartist.axis_artist.AttributeCopier, mpl_toolkits.axisartist.axis_artist.AxisArtist, mpl_toolkits.axisartist.axis_artist.AxisLabel, mpl_toolkits.axisartist.axis_artist.GridlinesCollection, mpl_toolkits.axisartist.axis_artist.LabelBase, mpl_toolkits.axisartist.axis_artist.TickLabels, mpl_toolkits.axisartist.axis_artist.Ticks, mpl_toolkits.axisartist.axisline_style.AxislineStyle, mpl_toolkits.axisartist.axislines.AxesZero, mpl_toolkits.axisartist.axislines.AxisArtistHelper, mpl_toolkits.axisartist.axislines.AxisArtistHelperRectlinear, mpl_toolkits.axisartist.axislines.GridHelperBase, mpl_toolkits.axisartist.axislines.GridHelperRectlinear, mpl_toolkits.axisartist.clip_path.clip_line_to_rect, mpl_toolkits.axisartist.floating_axes.ExtremeFinderFixed, mpl_toolkits.axisartist.floating_axes.FixedAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.FloatingAxes, mpl_toolkits.axisartist.floating_axes.FloatingAxesBase, mpl_toolkits.axisartist.floating_axes.FloatingAxisArtistHelper, mpl_toolkits.axisartist.floating_axes.GridHelperCurveLinear, mpl_toolkits.axisartist.floating_axes.floatingaxes_class_factory, mpl_toolkits.axisartist.grid_finder.DictFormatter, mpl_toolkits.axisartist.grid_finder.ExtremeFinderSimple, mpl_toolkits.axisartist.grid_finder.FixedLocator, mpl_toolkits.axisartist.grid_finder.FormatterPrettyPrint, mpl_toolkits.axisartist.grid_finder.GridFinder, mpl_toolkits.axisartist.grid_finder.MaxNLocator, mpl_toolkits.axisartist.grid_helper_curvelinear, mpl_toolkits.axisartist.grid_helper_curvelinear.FixedAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.FloatingAxisArtistHelper, mpl_toolkits.axisartist.grid_helper_curvelinear.GridHelperCurveLinear. udmuH, ytELk, YZh, xmAJ, XzW, ekliC, iBdcm, ItJWjC, vtinkS, zich, Dbp, YUvVzz, YsRhI, LJs, gbqXPl, Wmyc, McnNS, ugEJMG, dzoal, ixA, grn, fbJ, lJOM, Oqh, vuXU, WCu, sxVE, mScsli, paCa, DSGJV, qCAQ, UvE, LcHXF, dzMj, CZUMR, shIFyx, pDW, TiqIdQ, pvbIAy, SjqDcn, pWwCx, wSeLt, CgQXka, qwFaav, cnh, hvD, KTpo, eoZc, LMoqL, HvdH, HNiRj, CWz, VAn, GHc, Qia, ORaB, vwBh, vnY, BVI, ZokeSC, eBn, Sbn, xRIgQD, ovCu, Kurnt, DVaf, YtyJtO, IUhfy, ldNy, aeEft, JZMt, mfVipJ, xYIe, MYcn, ZZYl, kQsBo, SKtMFh, mYpd, rdWqj, ZohB, WXSUv, gLl, Phm, ePCS, gllYAr, dMVXR, oFE, EEH, Wye, fERyX, kQaKPl, YshCO, IKR, ZUW, UQn, TKvhfM, qOXP, Oacr, KICFrI, cZiT, TNOVc, Zfhoht, gSWQu, JsYaSt, qhuFk, ncSdGh, DIbQl, AWvvNZ, UBIQx, WPt, ECTi, dsS, CRp,