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""" Customizing Matplotlib with style sheets and rcParams ===================================================== Tips for customizing the properties and default styles of Matplotlib. Using style sheets ------------------ The ``style`` package adds support for easy-to-switch plotting "styles" with the same parameters as a :ref:`matplotlib rc ` file (which is read at startup to configure matplotlib). There are a number of pre-defined styles `provided by Matplotlib`_. For example, there's a pre-defined style called "ggplot", which emulates the aesthetics of ggplot_ (a popular plotting package for R_). To use this style, just add: """ import numpy as np import matplotlib.pyplot as plt import matplotlib as mpl plt.style.use('ggplot') data = np.random.randn(50) ############################################################################### # To list all available styles, use: print(plt.style.available) ############################################################################### # Defining your own style # ----------------------- # # You can create custom styles and use them by calling ``style.use`` with the # path or URL to the style sheet. Additionally, if you add your # ``.mplstyle`` file to ``mpl_configdir/stylelib``, you can reuse # your custom style sheet with a call to ``style.use()``. By default # ``mpl_configdir`` should be ``~/.config/matplotlib``, but you can check where # yours is with ``matplotlib.get_configdir()``; you may need to create this # directory. You also can change the directory where matplotlib looks for # the stylelib/ folder by setting the MPLCONFIGDIR environment variable, # see :ref:`locating-matplotlib-config-dir`. # # Note that a custom style sheet in ``mpl_configdir/stylelib`` will # override a style sheet defined by matplotlib if the styles have the same name. # # For example, you might want to create # ``mpl_configdir/stylelib/presentation.mplstyle`` with the following:: # # axes.titlesize : 24 # axes.labelsize : 20 # lines.linewidth : 3 # lines.markersize : 10 # xtick.labelsize : 16 # ytick.labelsize : 16 # # Then, when you want to adapt a plot designed for a paper to one that looks # good in a presentation, you can just add:: # # >>> import matplotlib.pyplot as plt # >>> plt.style.use('presentation') # # # Composing styles # ---------------- # # Style sheets are designed to be composed together. So you can have a style # sheet that customizes colors and a separate style sheet that alters element # sizes for presentations. These styles can easily be combined by passing # a list of styles:: # # >>> import matplotlib.pyplot as plt # >>> plt.style.use(['dark_background', 'presentation']) # # Note that styles further to the right will overwrite values that are already # defined by styles on the left. # # # Temporary styling # ----------------- # # If you only want to use a style for a specific block of code but don't want # to change the global styling, the style package provides a context manager # for limiting your changes to a specific scope. To isolate your styling # changes, you can write something like the following: with plt.style.context('dark_background'): plt.plot(np.sin(np.linspace(0, 2 * np.pi)), 'r-o') plt.show() ############################################################################### # .. _matplotlib-rcparams: # # matplotlib rcParams # =================== # # .. _customizing-with-dynamic-rc-settings: # # Dynamic rc settings # ------------------- # # You can also dynamically change the default rc settings in a python script or # interactively from the python shell. All of the rc settings are stored in a # dictionary-like variable called :data:`matplotlib.rcParams`, which is global to # the matplotlib package. rcParams can be modified directly, for example: mpl.rcParams['lines.linewidth'] = 2 mpl.rcParams['lines.color'] = 'r' plt.plot(data) ############################################################################### # Matplotlib also provides a couple of convenience functions for modifying rc # settings. The :func:`matplotlib.rc` command can be used to modify multiple # settings in a single group at once, using keyword arguments: mpl.rc('lines', linewidth=4, color='g') plt.plot(data) ############################################################################### # The :func:`matplotlib.rcdefaults` command will restore the standard matplotlib # default settings. # # There is some degree of validation when setting the values of rcParams, see # :mod:`matplotlib.rcsetup` for details. # # .. _customizing-with-matplotlibrc-files: # # The :file:`matplotlibrc` file # ----------------------------- # # matplotlib uses :file:`matplotlibrc` configuration files to customize all kinds # of properties, which we call `rc settings` or `rc parameters`. You can control # the defaults of almost every property in matplotlib: figure size and dpi, line # width, color and style, axes, axis and grid properties, text and font # properties and so on. matplotlib looks for :file:`matplotlibrc` in four # locations, in the following order: # # 1. :file:`matplotlibrc` in the current working directory, usually used for # specific customizations that you do not want to apply elsewhere. # # 2. :file:`$MATPLOTLIBRC` if it is a file, else :file:`$MATPLOTLIBRC/matplotlibrc`. # # 3. It next looks in a user-specific place, depending on your platform: # # - On Linux and FreeBSD, it looks in :file:`.config/matplotlib/matplotlibrc` # (or `$XDG_CONFIG_HOME/matplotlib/matplotlibrc`) if you've customized # your environment. # # - On other platforms, it looks in :file:`.matplotlib/matplotlibrc`. # # See :ref:`locating-matplotlib-config-dir`. # # 4. :file:`{INSTALL}/matplotlib/mpl-data/matplotlibrc`, where # :file:`{INSTALL}` is something like # :file:`/usr/lib/python3.7/site-packages` on Linux, and maybe # :file:`C:\\Python37\\Lib\\site-packages` on Windows. Every time you # install matplotlib, this file will be overwritten, so if you want # your customizations to be saved, please move this file to your # user-specific matplotlib directory. # # Once a :file:`matplotlibrc` file has been found, it will *not* search any of # the other paths. # # To display where the currently active :file:`matplotlibrc` file was # loaded from, one can do the following:: # # >>> import matplotlib # >>> matplotlib.matplotlib_fname() # '/home/foo/.config/matplotlib/matplotlibrc' # # See below for a sample :ref:`matplotlibrc file`. # # .. _matplotlibrc-sample: # # A sample matplotlibrc file # ~~~~~~~~~~~~~~~~~~~~~~~~~~ # # .. literalinclude:: ../../../matplotlibrc.template # # # .. _ggplot: https://ggplot2.tidyverse.org/ # .. _R: https://www.r-project.org/ # .. _provided by Matplotlib: https://github.com/matplotlib/matplotlib/tree/master/lib/matplotlib/mpl-data/stylelib