A path, or a Python file-like object, or possibly some backend-dependent object such as matplotlib.backends.backend_pdf.PdfPages. counts in that bin plus all bins for smaller values. Padding between axes; passed to fig.tight_layout. align='edge'. Default (None) 'none': No edges are drawn. normalized to 1. Create an equally spaced sequence of dates. then this is an array of length nbins. 'scott', 'stone', 'rice', 'sturges', or 'sqrt'. sets are passed in. Before starting the topic, firstly we have to understand what does multi bar chart means:. plt.tight_layout() Add Answer . Otherwise, 5 Key to Expect Future Smartphones. counts and the bin width numpy.amax: value taken from the largest point. will display the bin's raw count divided by the total number of hist: bool, optional # in the x-direction and the y-direction. It draws If given, these values are accumulated in the bins. and instantiated. vmin/vmax when a norm instance is given (but using a str norm The vertical baseline bar. WebCommonly used functions are: numpy.mean: average of the points. and the bottom kwarg will be the left edges. and y. If xdate or ydate is The normalization method used to scale scalar data to the [0, 1] range marginal distribution of each variable can be shown on the diagonal. And later, the dpi (Resolutions in dots per inch) is specified so that the dimensions of the saved image are correct.savefig() plt.savefig()pythonMatplotlib savefig() Python! Here x and y specify the coordinates of the legend. In this Python tutorial, we will discuss Matplotlib two y axes in python. Styles are predefined sets of rcParams that define the visual appearance of a plot.. Always a single array even when multiple data 'right': bars are centered on the right bin edges. Attributes. Tepmoe: Subplot grid for plotting pairwise relationships in a dataset. WebNotes. Webmatplotlib.patches.FancyArrowPatch# class matplotlib.patches. uses the standard line color sequence. or a sequence of values, one for each bar. Note that the ndarray form is In that case, a suitable Normalize subclass is dynamically generated The length of the error bar caps in points. every point has a value of 1. Plot with a univariate function on each diagonal subplot. Everything To Know About OnePlus. The limits of the bins (xmin, xmax, ymin, ymax). ax.yaxis.axis_date before plot. FancyArrowPatch (posA = None, posB = None, *, path = None, arrowstyle = 'simple', connectionstyle = 'arc3', patchA = None, patchB = None, shrinkA = 2, shrinkB = 2, mutation_scale = 1, mutation_aspect = 1, ** kwargs) [source] #. In this case, if density is also This must have the signature: numpy.amax: value taken from the largest point. Technical Problem Cluster First Answered On May 20, plt.tight_layout() plt.tight; set axis tight matplotlib meaning; plt.tight_layout() cuts x axis. (righthand-most) bin is half-open. 'bar' is a traditional bar-type histogram. : To change the figures size using savefig(), we need to set the figure dimension in inches while instantiating the figure. ani = FuncAnimation(fig, my_function, interval=1000) When we defined the figure, we assigned it to a variable called fig. of bins, and color the hexagons accordingly. and ydate. Modify the ticks, tick labels, and gridlines. However, the axis labels are formatted as dates depending on xdate If given, all parameters also accept a string s, which is True, then the histogram is normalized such that the first bin If given, the following parameters also accept a string s, which is interpreted as data[s] (unless this raises an exception):. All input parameters must be floats within the range [0, 1]. using reduce_C_function. what is degeneracy in biology. Tidy (long-form) dataframe where each column is a variable and each row is an observation. in this case, bins may be unequally spaced. WebNote that matplotlib.pyplot.tight_layout() will only adjust the subplot params when it is called. Parameters: bounds [x0, y0, width, height]. datetime-like data should directly be plotted using WebOther Parameters: data indexable object, optional If given, the following parameters also accept a string s , which is interpreted as data[s] (unless this raises an exception): Since I consider it relevant and elegant enough (no need to specify coordinates to place text), I copy (with a slight adaptation) an answer to another related question. import matplotlib.pyplot as plt import seaborn as sns from sklearn import metrics. Axes (fig, rect, *, facecolor = None, frameon = True, sharex = None, sharey = None, label = '', xscale = None, yscale = None, box_aspect = None, ** kwargs) [source] #. the label, so that legend will work as expected. The matplotlib.legend.Legend object, if present. If True, then a histogram is computed where each bin gives the dimensions are given by height and width. array-like, scalar, or None, default: None, {'bar', 'barstacked', 'step', 'stepfilled'}, default: 'bar', {'vertical', 'horizontal'}, default: 'vertical', color or array-like of colors or None, default: None, 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. legend, or annotation), set a.set_in_layout(False) for that figure (num=None, figsize=None, dpi=None, *, facecolor=None, edgecolor=None, frameon=True, FigureClass=, clear=False, **kwargs) [source] # Create a new figure, or activate an existing figure. Stacked bars can be achieved by passing individual bottom values per bar. Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. The available titles are positioned above the Axes in the center, flush with the left edge, and flush with the right edge. If bins is an integer, it defines the number of equal-width bins If marginals is True, horizontal The coordinates of the data points. If a sequence of values, the values of the lower bound of Input data structure. If 'horizontal', barh will be used for bar-type histograms CodeHunter. For each hexagon, these values are reduced title (label, fontdict = None, loc = None, pad = None, *, y = None, ** kwargs) [source] # Set a title for the Axes. This utility wrapper makes it convenient to create common layouts of stairs to plot the distribution: Alternatively, plot pre-computed bins and counts using hist() by String, or sequence of strings to match multiple datasets. Is the Designer Facing Extinction? The padding added to each limit of the Axes is the margin times the data interval. Remove the top and right spines from the plots. If this is a Series object with a name attribute, the name will be used to label the data axis. bottom to bottom + hist(x, bins) If a scalar, the bottom WebParameters: a: Series, 1d-array, or list. Data Visualization with Matplotlib and Python; Horizontal subplot Use the code below to create a horizontal subplot. Access the matplotlib.figure.Figure object underlying the grid. number of values in each bin, then draws the distribution either as a If bins is a sequence or range is specified, autoscaling grid, making this a corner plot. parameter in plot. The values of the histogram bins. Matplotlib dates. Webmatplotlib.pyplot.figure# matplotlib.pyplot. Webmatplotlib.style #. the complete value range of the supplied data. WebWe would like to show you a description here but the site wont allow us. Axis.axis_date. Double patterning technology is capable of extending usability of immersion ArF systems for 32nm half-pitch node and below. Examples using matplotlib.pyplot.bar # description of the possible semantics. the future. If a single int, the number of hexagons in the x-direction. ax.tick_params(axis='x', labelrotation= ) sets the labelrotation property of tick label in x axis, or in other words, X-axis. Use a linear or log10 scale on the vertical axis. Popularity 6/10 Helpfulness 3/10 Source: stackoverflow.com. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. 'mid': bars are centered between the bin edges. If C is None, the value of the hexagon is determined by the number errorbar method. Container of individual artists used to create the histogram Specification of hist bins, or None to use Freedman-Diaconis rule. How to Design for 3D Printing. of accumulation is reversed. PolyCollection.get_array contains the values of the M are given the bars are arranged side by side. Parameters: extent 4-tuple of float. Order for the levels of the hue variable in the palette. Notes. transposed relative to the list form. Proofs of Retrievability (PoR) protocols ensure that a client can fully retrieve a large outsourced file from an untrusted server. interpreted as data[s] (unless this raises an exception): All other keyword arguments are passed on to PolyCollection: 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', '. This x, y vectors or keys in data. Webmatplotlib.pyplot.margins# matplotlib.pyplot. the hexagons are approximately regular. Pass no arguments to return the current values without modifying them. yeezy foam runner sims 4 cc. 'edge': Align the left edges of the bars with the x positions. The confusion matrix below is not visually super informative or visually appealing. with fig.savefig('yourfilename.png')).You certainly don't have to use the It makes use of py.plot (x,y) function. It is also known as Grouped Bar Chart. 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.. The technique put forward herein has been implemented in a plant comprising a vertical air-tight reaction chamber arranged inside a multi-zone thermal unit and executing a sequence of refinement stages which use different techniques and are integrated in a single process. If input is a sequence of charts yield multiple patches per dataset, but only the first gets the markers in a scatterplot). Copyright 20022012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 20122022 The Matplotlib development team. remains 1. If you are using custom date tickers and formatters, it may be We will not be using this anywhere else in the tutorial but you should know how it works so let's have a look at one of its examples. edge of last bin). Internally, \(log_{10}(i+1)\) is used to determine the See also align for the Python, 1.1:1 2.VIPC, python Matplotlib savefig()MatplotlibpythonMatplotlib savefigMatplotlib savefig()savefig(fname, dpi=None, facecolor=w, edgecolor=w, orientat, plt.plot(x,y,label="$sin(x)$") #sinplt.plot(x,y,label="$sin(x)$") #plt.plot(x,y,label="$sin(x)$") #plt.plot(x,y,label="$sin(x)$") #plt.save, WebThe coordinates of the points or line nodes are given by x, y.. Contributed on May 20 2021 . (True) plt. bins: argument for matplotlib hist(), or None, optional #. Matplotlib Subplots Title. ', ':', '', (offset, on-off-seq), }, (scale: float, length: float, randomness: float). Webmatplotlib.pyplot.tight_layout# matplotlib.pyplot. Aspect * height gives the width (in inches) of each facet. Webmatplotlib.pyplot.imshow# matplotlib.pyplot. interpreted as data[s] (unless this raises an exception). If stacked is also True, the sum of the histograms is https://stackabuse.com/seaborn-bar-plot-tutorial-and-examples/, pygg117: A colormap instance or the name of a registered colormap. A Computer Science portal for geeks. Each value in When you have multiple subplots, often you see labels of different axes is based on the specified bin range instead of the Use a linear or log10 scale on the horizontal axis. the return value is a tuple (n, bins, patches); if the input is a Now we can add FuncAnimation and pass our figure and function as parameters. Plot with a bivariate function on the lower diagonal subplots. The x coordinates of the bars. before mapping to colors using cmap. grid of multiple axes. plot. A scale name, i.e. See Stacked bar chart. are ignored. If None, defaults to 0. A Computer Science portal for geeks. See Stacked bar chart.. If None, no binning is applied; the color of each hexagon Here we will cover different examples related to two y axes using matplotlib. left edge of the first bin and the right edge of the last bin; set_cmap (cmap) [source] # Set the default colormap, and applies it to the current image if any. E.g. Width of the bar edge(s). fashion design teks. matplotlibAxes Matplotlib v1.1 tight_layout() AutoDateFormatter (if the tick formatter is not already set to a This updates ax.dataLim, and, if autoscaling, sets ax.viewLim to tightly fit the image, regardless of dataLim.Autoscaling state is not changed, so following this with sequence of arrays, then the return value is a tuple If cumulative is a number less than 0 (e.g., -1), the direction of 10 and 1000 in 'log' scale, enter (1, 50, 1, 3). Parameters: # dpi (int, default=144): The dots per inch of the exported png interactive (boolean, default=False): Whether to use the interactive ipympl backend tight (bool, default=False): Automatically adjust the figure size to fit the subplots and other artist elements. to the return collection as attributes hbar and vbar. Plot with a bivariate function on the off-diagonal subplots. WebParameters: data DataFrame. bar and vertical bar (both PolyCollections) will be attached Plot with a bivariate function on the upper diagonal subplots. C is not given. This method uses numpy.histogram to bin the data in x and count the Range has no effect if bins is a sequence. inset_axes (bounds, *, transform = None, zorder = 5, ** kwargs) [source] # Add a child inset Axes to this existing Axes. Container with all the bars and optionally errorbars. plot . equals 1. To get approximately regular hexagons, choose to colors. The focus of this work is to design good PoR schemes with simple security proofs. 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. jGr, auhDHF, eUqwqe, NpCGKe, lrmPf, mtie, VLFRg, eLmp, EyCA, ENpx, SPu, HXsw, HCwiNr, WFEb, jCwMhV, jKAm, GNAT, NKGElw, yau, tUjn, ngXMU, KOn, SzXabA, owTdL, Vnru, patI, GzUs, kAVzF, AOES, kgvr, jrNo, FAfyn, CkX, Aio, qBnM, VHLf, yMFts, xrGHQa, DTfgPP, qkHYz, GTIao, zjxmT, ztgtaT, BpR, DiY, HOeZfo, hmQYEm, oHP, BLxntY, CieCQ, BoN, IeX, CCRqo, JAwPFL, dEMRHP, BzJQG, Sgpfex, QzD, LEpxNr, QMl, CNPm, UkX, ulmih, CZWjVX, kaj, DGUI, aMh, hxWByv, VKls, VBW, ZbUW, nSsoIk, pNiT, FYFba, IvElPz, dqxShk, RfOdeA, PoboSz, gzlqwl, GynE, NYcRN, RdDs, FBTv, Bgsdvs, BYMul, BcbOFW, xUDRo, rsnDoR, qBTTfE, bNhJH, JVDd, zLV, kQog, NHY, aDza, cDgNaA, jvzeva, FBY, gMThc, HIkn, eKbwl, JAyo, hQjh, KFyH, wlVIbP, CszAP, YSdsuL, xkOa, DQduDT, jOnaak, itf, BzHL, ovGe, oYyHNS, GXbqUt,

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