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Path TutorialDefining paths in your Matplotlib visualization. The object underlying all of the matplotlib.patch objects isthe Path, which supports the standard set ofmoveto, lineto, curveto commands to draw simple and compound outlinesconsisting of line segments and splines. The Path is instantiatedwith a (N,2) array of (x,y) vertices, and a N-length array of pathcodes. For example to draw the unit rectangle from (0,0) to (1,1), wecould use this code 123456789101112131415161718192021222324252...

Transformations TutorialLike any graphics packages, Matplotlib is built on top of atransformation framework to easily move between coordinate systems,the userland data coordinate system, the axes coordinate system,the figure coordinate system, and the display coordinate system.In 95% of your plotting, you won’t need to think about this, as ithappens under the hood, but as you push the limits of custom figuregeneration, it helps to have an understanding of these objects so youcan reuse the exi...

Path effects guideDefining paths that objects follow on a canvas. Matplotlib’s patheffects module provides functionality toapply a multiple draw stage to any Artist which can be rendered via aPath. Artists which can have a path effect applied to them include Patch,Line2D, Collection and evenText. Each artist’s path effects can be controlled via theset_path_effects method (set_path_effects), which takesan iterable of AbstractPathEffect instances. The simplest path effect is the Normal effect, ...

Creating Colormaps in MatplotlibMatplotlib has a number of built-in colormaps accessible viamatplotlib.cm.get_cmap. There are also external libraries likepalettable that have many extra colormaps. However, we often want to create or manipulate colormaps in Matplotlib.This can be done using the class ListedColormap and a Nx4 numpy array ofvalues between 0 and 1 to represent the RGBA values of the colormap. Thereis also a LinearSegmentedColormap class that allows colormaps to bespecified with a...

Customized Colorbars TutorialThis tutorial shows how to build colorbars without an attached plot. Customized ColorbarsColorbarBase puts a colorbar in a specified axes,and can make a colorbar for a given colormap; it does not need a mappableobject like an image. In this tutorial we will explore what can be done withstandalone colorbar. Basic continuous colorbarSet the colormap and norm to correspond to the data for which the colorbarwill be used. Then create the colorbar by callingColorbarBase...

Choosing Colormaps in MatplotlibMatplotlib has a number of built-in colormaps accessible viamatplotlib.cm.get_cmap. There are also external libraries like[palettable] and [colorcet] that have many extra colormaps.Here we briefly discuss how to choose between the many options. Forhelp on creating your own colormaps, seeCreating Colormaps in Matplotlib. OverviewThe idea behind choosing a good colormap is to find a good representation in 3Dcolorspace for your data set. The best colormap for any ...

Colormap NormalizationObjects that use colormaps by default linearly map the colors in thecolormap from data values vmin to vmax. For example: 1pcm = ax.pcolormesh(x, y, Z, vmin=-1., vmax=1., cmap='RdBu_r') will map the data in Z linearly from -1 to +1, so Z=0 willgive a color at the center of the colormap RdBu_r (white in thiscase). Matplotlib does this mapping in two steps, with a normalization fromthe input data to [0, 1] occurring first, and then mapping onto theindices in...

Specifying ColorsMatplotlib recognizes the following formats to specify a color: an RGB or RGBA (red, green, blue, alpha) tuple of float values in [0, 1](e.g., (0.1, 0.2, 0.5) or (0.1, 0.2, 0.5, 0.3)); a hex RGB or RGBA string (e.g., '#0f0f0f' or '#0f0f0f80';case-insensitive); a string representation of a float value in [0, 1] inclusive for graylevel (e.g., '0.5'); one of {'b', 'g', 'r', 'c', 'm', 'y', 'k', '...

Artist tutorialUsing Artist objects to render on the canvas. There are three layers to the matplotlib API. the matplotlib.backend_bases.FigureCanvas is the area onto whichthe figure is drawn the matplotlib.backend_bases.Renderer isthe object which knows how to draw on theFigureCanvas and the matplotlib.artist.Artist is the object that knows how to usea renderer to paint onto the canvas. The FigureCanvas andRenderer handle all the details oftalking to user interface toolkits like wxPython or...

Constrained Layout GuideHow to use constrained-layout to fit plots within your figure cleanly. constrained_layout automatically adjusts subplots and decorations likelegends and colorbars so that they fit in the figure window while stillpreserving, as best they can, the logical layout requested by the user. constrained_layout is similar totight_layout,but uses a constraint solver to determine the size of axes that allowsthem to fit. constrained_layout needs to be activated before any axes are ...