# Writing documentation¶

## Getting started¶

### General file structure¶

All documentation is built from the doc/ directory. This directory contains both reStructuredText (ReST; .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.

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 and doc/tutorials as they are regenerated when the documentation are built.

### Installing dependencies¶

The documentation for Matplotlib is generated from reStructuredText (ReST) 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:

• Sphinx>=1.3, !=1.5.0, !=1.6.4, !=1.7.3
• colorspacious
• IPython
• numpydoc>=0.8
• Pillow>=3.4
• sphinx-gallery>=0.2
• graphviz

Note

• 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.

### 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
make clean

# Build pdf docs.
make latexpdf


The SPHINXOPTS variable is set to -W by default to turn warnings into errors. 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 -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:

matplotlib.collections.LineCollection


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:

.LineCollection


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:

numpy.mean


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.

Note

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*.

Parameters
----------
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, optional, default: 'k'

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

label : string, optional, default: ''

Returns
-------
lines : ~matplotlib.collections.LineCollection

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

--------
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 'solid' is used.


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.


#### 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.

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 refering 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.


#### 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:

def add_axes(self, *args, **kwargs):
"""
...

Parameters
----------
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¶

rcParams can be referenced with the custom :rc: role: :rc:foo yields rcParams["foo"]. Use = [default-val] to indicate the default value of the parameter. The default value should be literal, i.e. enclosed in double backticks. For simplicity these may be omitted for string default values.

If not provided, defaults to :rc:figure.figsize = [6.4, 4.8].
If not provided, defaults to :rc:figure.facecolor = 'w'.


### Deprecated formatting conventions¶

Formerly, we have used square brackets for explicit parameter lists ['solid' | 'dashed' | 'dotted']. With numpydoc we have switched to their standard using curly braces {'solid', 'dashed', 'dotted'}.

### 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.

Note

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¶

Note

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
docstring.interpd.update(Line2D=artist.kwdoc(Line2D))


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

# in axes.py
@docstring.dedent_interpd
def plot(self, *args, **kwargs):
"""
Some stuff omitted

The kwargs are Line2D properties:
%(Line2D)s

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
information
"""


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 accidentially create a docstring in the future:

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

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


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:

"""
...

Examples
--------

.. 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 Plot directive documentation. A short example is:

"""
...

Examples
--------

.. plot::
import matplotlib.image as mpimg
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')
ax.grid()
plt.show()


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.
"""
...
ax.grid()
plt.show()

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

fig, ax = plt.subplots()
ax.plot(np.sin(range(50)))


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

## Miscellaneous¶

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>
</iframe>


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)


### 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.

Example:

.. inheritance-diagram:: matplotlib.patches matplotlib.lines matplotlib.text
:parts: 2


### 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))


C-c TAB - rst-toc-insert