Writing documentation

Getting started

General file structure

All documentation is built from the doc/, tutorials/, and examples/ directories. The doc/ directory contains configuration files for Sphinx and reStructuredText (ReST; .rst) files that are rendered to documentation pages.

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

Sphinx also creates .rst files that are staged in doc/api from the docstrings of the classes in the Matplotlib library. Except for doc/api/api_changes/, these .rst files are created when the documentation is built.

Similarly, the contents of doc/gallery and doc/tutorials are generated by the Sphinx Gallery from the sources in examples/ and tutorials/. These sources consist of python scripts that have ReST documentation built into their comments.


Don't directly edit the .rst files in doc/gallery, doc/tutorials, and doc/api (excepting doc/api/api_changes/). Sphinx regenerates files in these directories when building documentation.

Installing dependencies

The documentation for Matplotlib is generated from reStructuredText (ReST) using the Sphinx documentation generation tool. To build the documentation you will need to (1) set up an appropriate Python environment and (2) separately install LaTeX and Graphviz.

To (1) set up an appropriate Python environment for building the documentation, you should:

  • create a clean virtual environment with no existing Matplotlib installation
  • install the Python packages required for Matplotlib
  • install the additional Python packages required to build the documentation

There are several extra python packages that are needed to build the documentation. They are listed in doc-requirements.txt, which is shown below:

# Requirements for building docs
# You will first need a matching Matplotlib installation
# e.g (from the Matplotlib root directory)
#     pip install -e .
# Install the documentation requirements with:
#     pip install -r requirements/doc/doc-requirements.txt

To (2) set up LaTeX and Graphviz dependencies you should:

  • install a minimal working LaTeX distribution
  • install the LaTeX packages cm-super and dvipng
  • install Graphviz


The documentation will not build without LaTeX and Graphviz. These are not Python packages and must be installed separately.

Building the docs

The documentation sources are found in the doc/ directory in the trunk. The configuration file for Sphinx is doc/conf.py. It controls which directories Sphinx parses, how the docs are built, and how the extensions are used. To build the documentation in html format, cd into doc/ and run:

make html

Other useful invocations include

# Delete built files.  May help if you get errors about missing paths or
# broken links.
make clean

# Build pdf docs.
make latexpdf

The SPHINXOPTS variable is set to -W --keep-going by default to build the complete docs but exit with exit status 1 if there are warnings. To unset it, use

make SPHINXOPTS= html

You can use the O variable to set additional options:

  • make O=-j4 html runs a parallel build with 4 processes.
  • make O=-Dplot_formats=png:100 html saves figures in low resolution.
  • make O=-Dplot_gallery=0 html skips the gallery build.

Multiple options can be combined using e.g. make O='-j4 -Dplot_gallery=0' html.

On Windows, options needs to be set as environment variables, e.g. set O=-W --keep-going -j4 & make html.

Writing ReST pages

Most documentation is either in the docstring of individual classes and methods, in explicit .rst files, or in examples and tutorials. All of these use the ReST syntax. Users should look at the ReST documentation for a full description. But some specific hints and conventions Matplotlib uses are useful for creating documentation.

Formatting and style conventions

It is useful to strive for consistency in the Matplotlib documentation. Here are some formatting and style conventions that are used.

Section name formatting

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

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*

Do not use the `default role`:

Do not describe `argument` like this.  As per the next section,
this syntax will (unsuccessfully) attempt to resolve the argument as a
link to a class or method in the library.

nor the ``literal`` role:

Do not describe ``argument`` like this.

Referring to other documents and sections

Sphinx allows internal references between documents.

Documents can be linked with the :doc: directive:

See the :doc:`/faq/installing_faq`

See the tutorial :doc:`/tutorials/introductory/sample_plots`

See the example :doc:`/gallery/lines_bars_and_markers/simple_plot`

will render as:

See the Installation

See the tutorial Sample plots in Matplotlib

See the example Simple Plot

Sections can also be given reference names. For instance from the Installation link:

.. _clean-install:

How to completely remove Matplotlib

Occasionally, problems with Matplotlib can be solved with a clean...

and refer to it using the standard reference syntax:

See :ref:`clean-install`

will give the following link: How to completely remove Matplotlib

To maximize internal consistency in section labeling and references, use hyphen separated, descriptive labels for section references. Keep in mind that contents may be reorganized later, so 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, use hyphens to separate words.

Referring to other code

To link to other methods, classes, or modules in Matplotlib you can use back ticks, for example:


generates a link like this: matplotlib.collections.LineCollection.

Note: We use the sphinx setting default_role = 'obj' so that you don't have to use qualifiers like :class:, :func:, :meth: and the likes.

Often, you don't want to show the full package and module name. As long as the target is unanbigous you can simply leave them out:


and the link still works: LineCollection.

If there are multiple code elements with the same name (e.g. plot() is a method in multiple classes), you'll have to extend the definition:

`.pyplot.plot` or `.Axes.plot`

These will show up as pyplot.plot or Axes.plot. To still show only the last segment you can add a tilde as prefix:

`~.pyplot.plot` or `~.Axes.plot`

will render as plot or plot.

Other packages can also be linked via intersphinx:


will return this link: numpy.mean. This works for Python, Numpy, Scipy, and Pandas (full list is in doc/conf.py). 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 'https://docs.scipy.org/doc/numpy/objects.inv'

Including figures and files

Image files can directly included in pages with the image:: directive. e.g., users/navigation_toolbar.rst displays the toolbar icons with a call to a static image:

.. image:: ../_static/toolbar.png

as rendered on the page: Interactive navigation.

Files can be included verbatim. For instance the matplotlibrc file is important for customizing Matplotlib, and is included verbatim in the tutorial in Customizing Matplotlib with style sheets and rcParams:

.. literalinclude:: ../../_static/matplotlibrc

This is rendered at the bottom of Customizing Matplotlib with style sheets and rcParams. Note that this is in a tutorial; see Writing examples and tutorials below.

The examples directory is also copied to doc/gallery by sphinx-gallery, so plots from the examples directory can be included using

.. plot:: gallery/lines_bars_and_markers/simple_plot.py

Note that the python script that generates the plot is referred to, rather than any plot that is created. Sphinx-gallery will provide the correct reference when the documentation is built.

Writing docstrings

Most of the API documentation is written in docstrings. These are comment blocks in source code that explain how the code works.


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.

All new or edited docstrings should conform to the numpydoc docstring guide. Much of the ReST syntax discussed above (Writing ReST pages) can be used for links and references. These docstrings eventually populate the doc/api directory and form the reference documentation for the library.

Example docstring

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 : float or array-like
        y-indexes where to plot the lines.

    xmin, xmax : float or array-like
        Respective beginning and end of each line. If scalars are
        provided, all lines will have the same length.

    colors : array-like of colors, default: 'k'

    linestyles : {'solid', 'dashed', 'dashdot', 'dotted'}, default: 'solid'

    label : str, default: ''

    lines : `~matplotlib.collections.LineCollection`

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

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

See the hlines documentation for how this renders.

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

Formatting conventions

The basic docstring conventions are covered in the numpydoc docstring guide and the Sphinx documentation. Some Matplotlib-specific formatting conventions to keep in mind:

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:

If *linestyles* is *None*, the default is 'solid'.

Do not use the `default role` or the ``literal`` role:

Neither `argument` nor ``argument`` should be used.

Quotes for strings

Matplotlib does not have a convention whether to use single-quotes or double-quotes. There is a mixture of both in the current code.

Use simple single or double quotes when giving string values, e.g.

If 'tight', try to figure out the tight bbox of the figure.

No ``'extra'`` literal quotes.

The use of extra literal quotes around the text is discouraged. While they slightly improve the rendered docs, they are cumbersome to type and difficult to read in plain-text docs.

Parameter type descriptions

The main goal for parameter type descriptions is to be readable and understandable by humans. If the possible types are too complex use a simplification for the type description and explain the type more precisely in the text.

Generally, the numpydoc docstring guide conventions apply. The following rules expand on them where the numpydoc conventions are not specific.

Use float for a type that can be any number.

Use (float, float) to describe a 2D position. The parentheses should be included to make the tuple-ness more obvious.

Use array-like for homogeneous numeric sequences, which could typically be a numpy.array. Dimensionality may be specified using 2D, 3D, n-dimensional. If you need to have variables denoting the sizes of the dimensions, use capital letters in brackets (array-like (M, N)). When referring to them in the text they are easier read and no special formatting is needed.

float is the implicit default dtype for array-likes. For other dtypes use array-like of int.

Some possible uses:

2D array-like
array-like (N)
array-like (M, N)
array-like (M, N, 3)
array-like of int

Non-numeric homogeneous sequences are described as lists, e.g.:

list of str
list of `.Artist`

Referencing types

Generally, the rules from referring-to-other-code apply. More specifically:

Use full references `~matplotlib.colors.Normalize` with an abbreviation tilde in parameter types. While the full name helps the reader of plain text docstrings, the HTML does not need to show the full name as it links to it. Hence, the ~-shortening keeps it more readable.

Use abbreviated links `.Normalize` in the text.

norm : `~matplotlib.colors.Normalize`, optional
     A `.Normalize` instance is used to scale luminance data to 0, 1.

Default values

As opposed to the numpydoc guide, parameters need not be marked as optional if they have a simple default:

  • use {name} : {type}, default: {val} when possible.
  • use {name} : {type}, optional and describe the default in the text if it cannot be explained sufficiently in the recommended manner.

The default value should provide semantic information targeted at a human reader. In simple cases, it restates the value in the function signature. If applicable, units should be added.

    interval : int, default: 1000ms
    interval : int, default: 1000

If None is only used as a sentinel value for "parameter not specified", do not document it as the default. Depending on the context, give the actual default, or mark the parameter as optional if not specifying has no particular effect.

    dpi : int, default: :rc:`figure.dpi`
    dpi : int, default: None

    textprops : dict, optional
        Dictionary of keyword parameters to be passed to the
        `~matplotlib.text.Text` instance contained inside TextArea.
    textprops : dict, default: None
        Dictionary of keyword parameters to be passed to the
        `~matplotlib.text.Text` instance contained inside TextArea.

See also sections

Sphinx automatically links code elements in the definition blocks of See also sections. No need to use backticks there:

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

Wrapping parameter lists

Long parameter lists should be wrapped using a \ for continuation and starting on the new line without any indent (no indent because pydoc will parse the docstring and strip the line continuation so that indent would result in a lot of whitespace within the line):

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.


rcParams can be referenced with the custom :rc: role: :rc:`foo` yields rcParams["foo"] = 'default', which is a link to the matplotlibrc file description.

Setters and getters

Artist properties are implemented using setter and getter methods (because Matplotlib predates the introductions of the property decorator in Python). By convention, these setters and getters are named set_PROPERTYNAME and get_PROPERTYNAME; the list of properties thusly defined on an artist and their values can be listed by the setp and getp functions.


ACCEPTS blocks have recently become optional. You may now use a numpydoc Parameters block because the accepted values can now be read from the type description of the first parameter.

Property setter methods should indicate the values they accept using a (legacy) special block in the docstring, starting with ACCEPTS, as follows:

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

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

The ACCEPTS block is used to render a table of all properties and their acceptable values in the docs; it can also be displayed using, e.g., plt.setp(Line2D) (all properties) or plt.setp(Line2D, 'linestyle') (just one property).

There are cases in which the ACCEPTS string is not useful in the generated Sphinx documentation, e.g. if the valid parameters are already defined in the numpydoc parameter list. You can hide the ACCEPTS string from Sphinx by making it a ReST comment (i.e. use .. ACCEPTS:):

def set_linestyle(self, linestyle):
    An ACCEPTS string invisible to Sphinx.

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

Keyword arguments


The information in this section is being actively discussed by the development team, so use the docstring interpolation only if necessary. This section has been left in place for now because this interpolation is part of the existing documentation.

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 lines.py

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

# in axes.py
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.

Inheriting docstrings

If a subclass overrides a method but does not change the semantics, we can reuse the parent docstring for the method of the child class. Python does this automatically, if the subclass method does not have a docstring.

Use a plain comment # docstring inherited to denote the intention to reuse the parent docstring. That way we do not accidentally create a docstring in the future:

class A:
    def foo():
        """The parent docstring."""

class B(A):
    def foo():
        # docstring inherited

Adding figures

As above (see Including figures and files), figures in the examples gallery can be referenced with a :plot: directive pointing to the python script that created the figure. For instance the legend docstring references the file examples/text_labels_and_annotations/legend.py:



.. plot:: gallery/text_labels_and_annotations/legend.py

Note that examples/text_labels_and_annotations/legend.py has been mapped to gallery/text_labels_and_annotations/legend.py, a redirection that may be fixed in future re-organization of the docs.

Plots can also be directly placed inside docstrings. Details are in matplotlib.sphinxext.plot_directive. A short example is:



.. plot::
   import matplotlib.image as mpimg
   img = mpimg.imread('_static/stinkbug.png')
   imgplot = plt.imshow(img)

An advantage of this style over referencing an example script is that the code will also appear in interactive docstrings.

Writing examples and tutorials

Examples and tutorials are python scripts that are run by Sphinx Gallery to create a gallery of images in the /doc/gallery and /doc/tutorials directories respectively. To exclude an example from having an plot generated insert "sgskip" somewhere in the filename.

The format of these files is relatively straightforward. Properly formatted comment blocks are treated as ReST text, the code is displayed, and figures are put into the built page.

For instance the example Simple Plot example is generated from /examples/lines_bars_and_markers/simple_plot.py, which looks like:

Simple Plot

Create a simple plot.
import matplotlib.pyplot as plt
import numpy as np

# Data for plotting
t = np.arange(0.0, 2.0, 0.01)
s = 1 + np.sin(2 * np.pi * t)

# Note that using plt.subplots below is equivalent to using
# fig = plt.figure and then ax = fig.add_subplot(111)
fig, ax = plt.subplots()
ax.plot(t, s)

ax.set(xlabel='time (s)', ylabel='voltage (mV)',
       title='About as simple as it gets, folks')

The first comment block is treated as ReST text. The other comment blocks render as comments in Simple Plot.

Tutorials are made with the exact same mechanism, except they are longer, and typically have more than one comment block (i.e. Usage Guide). The first comment block can be the same as the example above. Subsequent blocks of ReST text are delimited by a line of ### characters:

Simple Plot

Create a simple plot.

# Second plot
# ===========
# This is a second plot that is very nice

fig, ax = plt.subplots()

In this way text, code, and figures are output in a "notebook" style.


Adding animations

There is a Matplotlib Google/Gmail account with username mplgithub which was 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 matplotlib.animation.Animation.save(), 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)

ani.save('double_pendulum.mp4', fps=15)

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

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