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Writing documentation

Getting started

Installing dependencies

The documentation for Matplotlib is generated from reStructuredText using the Sphinx documentation generation tool. There are several extra requirements that are needed to build the documentation. They are listed in doc-requirements.txt and listed below:

  1. Sphinx 1.3 or later (1.5.0 is not supported)
  2. numpydoc 0.4 or later
  3. IPython
  4. mock
  5. colorspacious
  6. Pillow
  7. Graphviz


  • You’ll need a minimal working LaTeX distribution for many examples to run.
  • Graphviz is not a Python package, and needs to be installed separately.

General file structure

All documentation is built from the doc/ directory. This directory contains both .rst files that contain pages in the documentation and configuration files for Sphinx.

The .rst files are kept in doc/users, doc/devel, doc/api and doc/faq. The main entry point is doc/index.rst, which pulls in the index.rst file for the users guide, developers guide, api reference, and FAQs. The documentation suite is built as a single document in order to make the most effective use of cross referencing.


An exception to this are the directories examples and tutorials, which exist in the root directory. These contain Python files that are built by Sphinx Gallery. When the docs are built, the directories docs/gallery and docs/tutorials are automatically generated. Do not edit the rst files in :file:docs/gallery and :file:docs/tutorials, as they are rebuilt from the original sources in the root directory.

Additional files can be added to the various guides by including their base file name (the .rst extension is not necessary) in the table of contents. It is also possible to include other documents through the use of an include statement, such as:

.. include:: ../../TODO

The configuration file for Sphinx is doc/ It controls which directories Sphinx parses, how the docs are built, and how the extensions are used.

Building the docs

The documentation sources are found in the doc/ directory in the trunk. To build the documentation in html format, cd into doc/ and run:

python html

The list of commands and flags for can be listed by running python --help. In particular,

  • python clean will delete the built Sphinx files. Use this command if you’re getting strange errors about missing paths or broken links, particularly if you move files around.
  • python latex builds a PDF of the documentation.
  • The --allowsphinxwarnings flag allows the docs to continue building even if Sphinx throws a warning. This is useful for debugging and spot-checking many warnings at once.

Writing new documentation

Most documentation lives in “docstrings”. These are comment blocks in source code that explain how the code works. All new or edited docstrings should conform to the numpydoc guidelines. These split the docstring into a number of sections - see for more details and a guide to how docstrings should be formatted.

An example docstring looks like:

def hlines(self, y, xmin, xmax, colors='k', linestyles='solid',
           label='', **kwargs):
      Plot horizontal lines at each *y* from *xmin* to *xmax*.

      y : scalar or sequence of scalar
          y-indexes where to plot the lines.

      xmin, xmax : scalar or 1D array_like
          Respective beginning and end of each line. If scalars are
          provided, all lines will have same length.

      colors : array_like of colors, optional, default: 'k'

      linestyles : ['solid' | 'dashed' | 'dashdot' | 'dotted'], optional

      label : string, optional, default: ''

      lines : `~matplotlib.collections.LineCollection`

      Other Parameters
      **kwargs : `~matplotlib.collections.LineCollection` properties.

      See also
      vlines : vertical lines
      axhline: horizontal line across the axes

The Sphinx website also contains plenty of documentation concerning ReST markup and working with Sphinx in general.


Some parts of the documentation do not yet conform to the current documentation style. If in doubt, follow the rules given here and not what you may see in the source code. Pull requests updating docstrings to the current style are very welcome.

Additional formatting conventions

There are some additional conventions, not handled by numpydoc and the Sphinx guide:

  • We do not have a convention whether to use single-quotes or double-quotes. There is a mixture of both in the current code. Please leave them as they are.

  • Long parameter lists should be wrapped using a \ for continuation and starting on the new line without any indent:

    def add_axes(self, *args, **kwargs):
        projection :
            ['aitoff' | 'hammer' | 'lambert' | 'mollweide' | \
    'polar' | 'rectilinear'], optional
            The projection type of the axes.

    Alternatively, you can describe the valid parameter values in a dedicated section of the docstring.

  • Generally, do not add markup to types for Parameters and Returns. This is usually not needed because Sphinx will link them automatically and would unnecessarily clutter the docstring. However, it does seem to fail in some situations. If you encounter such a case, you are allowed to add markup:

    lines : `~matplotlib.collections.LineCollection`

Linking to other code

To link to other methods, classes, or modules in Matplotlib you can encase the name to refer to in back ticks, for example:


It is also possible to add links to code in Python, Numpy, Scipy, or Pandas. Sometimes it is tricky to get external Sphinx linking to work; to check that a something exists to link to the following shell command outputs a list of all objects that can be referenced (in this case for Numpy):

python -m sphinx.ext.intersphinx ''

Function arguments

Function arguments and keywords within docstrings should be referred to using the *emphasis* role. This will keep Matplotlib’s documentation consistent with Python’s documentation:

Here is a description of *argument*

Please do not use the `default role`:

Please do not describe `argument` like this.

nor the ``literal`` role:

Please do not describe ``argument`` like this.

Setters and getters

Matplotlib uses artist introspection of docstrings to support properties. All properties that you want to support through setp and getp should have a set_property and get_property method in the Artist class. The setter methods use the docstring with the ACCEPTS token to indicate the type of argument the method accepts. e.g., in Line2D:

# in
def set_linestyle(self, linestyle):
    Set the linestyle of the line

    ACCEPTS: [ '-' | '--' | '-.' | ':' | 'steps' | 'None' | ' ' | '' ]

Keyword arguments

Since Matplotlib uses a lot of pass-through kwargs, e.g., in every function that creates a line (plot, semilogx, semilogy, etc…), it can be difficult for the new user to know which kwargs are supported. Matplotlib uses a docstring interpolation scheme to support documentation of every function that takes a **kwargs. The requirements are:

  1. single point of configuration so changes to the properties don’t require multiple docstring edits.
  2. as automated as possible so that as properties change, the docs are updated automatically.

The function matplotlib.artist.kwdoc and the decorator matplotlib.docstring.dedent_interpd facilitate this. They combine Python string interpolation in the docstring with the Matplotlib artist introspection facility that underlies setp and getp. The kwdoc function gives the list of properties as a docstring. In order to use this in another docstring, first update the matplotlib.docstring.interpd object, as seen in this example from matplotlib.lines:

# in

Then in any function accepting Line2D pass-through kwargs, e.g., matplotlib.axes.Axes.plot:

# in
def plot(self, *args, **kwargs):
    Some stuff omitted

    The kwargs are Line2D properties:

    kwargs scalex and scaley, if defined, are passed on
    to autoscale_view to determine whether the x and y axes are
    autoscaled; default True.  See Axes.autoscale_view for more

Note there is a problem for Artist __init__ methods, e.g., matplotlib.patches.Patch.__init__, which supports Patch kwargs, since the artist inspector cannot work until the class is fully defined and we can’t modify the Patch.__init__.__doc__ docstring outside the class definition. There are some some manual hacks in this case, violating the “single entry point” requirement above – see the docstring.interpd.update calls in matplotlib.patches.

Adding figures

Figures in the documentation are automatically generated from scripts. It is not necessary to explicitly save the figure from the script; this will be done automatically when the docs are built to ensure that the code that is included runs and produces the advertised figure.

There are two options for where to put the code that generates a figure. If you want to include a plot in the examples gallery, the code should be added to the examples directory. Plots from the examples directory can then be referenced through the symlink mpl_examples in the doc directory, e.g.:

.. plot:: mpl_examples/lines_bars_and_markers/

Alternatively the plotting code can be placed directly in the docstring. To include plots directly in docstrings, see the following guide:

Plot directive documentation

A directive for including a matplotlib plot in a Sphinx document.

By default, in HTML output, plot will include a .png file with a link to a high-res .png and .pdf. In LaTeX output, it will include a .pdf.

The source code for the plot may be included in one of three ways:

  1. A path to a source file as the argument to the directive:

    .. plot:: path/to/

    When a path to a source file is given, the content of the directive may optionally contain a caption for the plot:

    .. plot:: path/to/
       This is the caption for the plot

    Additionally, one may specify the name of a function to call (with no arguments) immediately after importing the module:

    .. plot:: path/to/ plot_function1
  2. Included as inline content to the directive:

    .. plot::
       import matplotlib.pyplot as plt
       import matplotlib.image as mpimg
       import numpy as np
       img = mpimg.imread('_static/stinkbug.png')
       imgplot = plt.imshow(img)
  3. Using doctest syntax:

    .. plot::
       A plotting example:
       >>> import matplotlib.pyplot as plt
       >>> plt.plot([1,2,3], [4,5,6])


The plot directive supports the following options:

format : {‘python’, ‘doctest’}
Specify the format of the input
include-source : bool
Whether to display the source code. The default can be changed using the plot_include_source variable in
encoding : str
If this source file is in a non-UTF8 or non-ASCII encoding, the encoding must be specified using the :encoding: option. The encoding will not be inferred using the -*- coding -*- metacomment.
context : bool or str
If provided, the code will be run in the context of all previous plot directives for which the :context: option was specified. This only applies to inline code plot directives, not those run from files. If the :context: reset option is specified, the context is reset for this and future plots, and previous figures are closed prior to running the code. :context:close-figs keeps the context but closes previous figures before running the code.
nofigs : bool
If specified, the code block will be run, but no figures will be inserted. This is usually useful with the :context: option.

Additionally, this directive supports all of the options of the image directive, except for target (since plot will add its own target). These include alt, height, width, scale, align and class.

Configuration options

The plot directive has the following configuration options:

Default value for the include-source option
Whether to show a link to the source in HTML.

Code that should be executed before each plot. If not specified or None it will default to a string containing:

import numpy as np
from matplotlib import pyplot as plt
Base directory, to which plot:: file names are relative to. (If None or empty, file names are relative to the directory where the file containing the directive is.)

File formats to generate. List of tuples or strings:

[(suffix, dpi), suffix, ...]

that determine the file format and the DPI. For entries whose DPI was omitted, sensible defaults are chosen. When passing from the command line through sphinx_build the list should be passed as suffix:dpi,suffix:dpi, ….

Whether to show links to the files in HTML.
A dictionary containing any non-standard rcParams that should be applied before each plot.
By default, rcParams are applied when context option is not used in a plot directive. This configuration option overrides this behavior and applies rcParams before each plot.
By default, the working directory will be changed to the directory of the example, so the code can get at its data files, if any. Also its path will be added to sys.path so it can import any helper modules sitting beside it. This configuration option can be used to specify a central directory (also added to sys.path) where data files and helper modules for all code are located.
Provide a customized template for preparing restructured text.
matplotlib.sphinxext.plot_directive.mark_plot_labels(app, document)

To make plots referenceable, we need to move the reference from the “htmlonly” (or “latexonly”) node to the actual figure node itself.

matplotlib.sphinxext.plot_directive.out_of_date(original, derived)

Returns True if derivative is out-of-date wrt original, both of which are full file paths.

matplotlib.sphinxext.plot_directive.plot_directive(name, arguments, options, content, lineno, content_offset, block_text, state, state_machine)

A directive for including a matplotlib plot in a Sphinx document.

By default, in HTML output, plot will include a .png file with a link to a high-res .png and .pdf. In LaTeX output, it will include a .pdf.

The source code for the plot may be included in one of three ways:

  1. A path to a source file as the argument to the directive:

    .. plot:: path/to/

    When a path to a source file is given, the content of the directive may optionally contain a caption for the plot:

    .. plot:: path/to/
       This is the caption for the plot

    Additionally, one may specify the name of a function to call (with no arguments) immediately after importing the module:

    .. plot:: path/to/ plot_function1
  2. Included as inline content to the directive:

    .. plot::
       import matplotlib.pyplot as plt
       import matplotlib.image as mpimg
       import numpy as np
       img = mpimg.imread('_static/stinkbug.png')
       imgplot = plt.imshow(img)
  3. Using doctest syntax:

    .. plot::
       A plotting example:
       >>> import matplotlib.pyplot as plt
       >>> plt.plot([1,2,3], [4,5,6])

Remove the coding comment, which six.exec_ doesn’t like.

matplotlib.sphinxext.plot_directive.render_figures(code, code_path, output_dir, output_base, context, function_name, config, context_reset=False, close_figs=False)

Run a pyplot script and save the images in output_dir.

Save the images under output_dir with file names derived from output_base

matplotlib.sphinxext.plot_directive.run_code(code, code_path, ns=None, function_name=None)

Import a Python module from a path, and run the function given by name, if function_name is not None.


Split code at


Extract code from a piece of text, which contains either Python code or doctests.


The source of the files in the examples directory are automatically run and their output plots included in the documentation. To exclude an example from having an plot generated insert “sgskip” somewhere in the filename.

Adding animations

We have a Matplotlib Google/Gmail account with username mplgithub which we used to setup the github account but can be used for other purposes, like hosting Google docs or Youtube videos. You can embed a Matplotlib animation in the docs by first saving the animation as a movie using, and then uploading to matplotlib’s Youtube channel and inserting the embedding string youtube provides like:

.. raw:: html

   <iframe width="420" height="315"
     frameborder="0" allowfullscreen>

An example save command to generate a movie looks like this

ani = animation.FuncAnimation(fig, animate, np.arange(1, len(y)),
    interval=25, blit=True, init_func=init)'double_pendulum.mp4', fps=15)

Contact Michael Droettboom for the login password to upload youtube videos of google docs to the mplgithub account.

Referring to data files

In the documentation, you may want to include to a data file in the Matplotlib sources, e.g., a license file or an image file from mpl-data, refer to it via a relative path from the document where the rst file resides, e.g., in users/navigation_toolbar.rst, you can refer to the image icons with:

.. image:: ../../lib/matplotlib/mpl-data/images/subplots.png

In the users subdirectory, if you want to refer to a file in the mpl-data directory, you can use the symlink directory. For example, from customizing.rst:

.. literalinclude:: ../../lib/matplotlib/mpl-data/matplotlibrc

One exception to this is when referring to the examples directory. Relative paths are extremely confusing in the sphinx plot extensions, so it is easier to simply include a symlink to the files at the top doc level directory. This way, API documents like matplotlib.pyplot.plot() can refer to the examples in a known location.

In the top level doc directory we have symlinks pointing to the Matplotlib examples:

home:~/mpl/doc> ls -l mpl_*
mpl_examples -> ../examples

So we can include plots from the examples dir using the symlink:

.. plot:: mpl_examples/pylab_examples/

Internal section references

To maximize internal consistency in section labeling and references, use hyphen separated, descriptive labels for section references, e.g.:

.. _howto-webapp:

and refer to it using the standard reference syntax:

See :ref:`howto-webapp`

Keep in mind that we may want to reorganize the contents later, so please try to avoid top level names in references like user or devel or faq unless necessary, because for example the FAQ “what is a backend?” could later become part of the users guide, so the label:

.. _what-is-a-backend

is better than:

.. _faq-backend

In addition, since underscores are widely used by Sphinx itself, please use hyphens to separate words.

Section name formatting

For everything but top level chapters, please use Upper lower for section titles, e.g., Possible hangups rather than Possible Hangups

Generating inheritance diagrams

Class inheritance diagrams can be generated with the inheritance-diagram directive. To use it, provide the directive with a number of class or module names (separated by whitespace). If a module name is provided, all classes in that module will be used. All of the ancestors of these classes will be included in the inheritance diagram.

A single option is available: parts controls how many of parts in the path to the class are shown. For example, if parts == 1, the class matplotlib.patches.Patch is shown as Patch. If parts == 2, it is shown as patches.Patch. If parts == 0, the full path is shown.


.. inheritance-diagram:: matplotlib.patches matplotlib.lines matplotlib.text
   :parts: 2
Inheritance diagram of matplotlib.patches, matplotlib.lines, matplotlib.text

Emacs helpers

There is an emacs mode rst.el which automates many important ReST tasks like building and updating table-of-contents, and promoting or demoting section headings. Here is the basic .emacs configuration:

(require 'rst)
(setq auto-mode-alist
      (append '(("\\.txt$" . rst-mode)
                ("\\.rst$" . rst-mode)
                ("\\.rest$" . rst-mode)) auto-mode-alist))

Some helpful functions:

C-c TAB - rst-toc-insert

  Insert table of contents at point

C-c C-u - rst-toc-update

    Update the table of contents at point

C-c C-l rst-shift-region-left

    Shift region to the left

C-c C-r rst-shift-region-right

    Shift region to the right