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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"

"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">

<head>

<title>Sphinx extensions for embedded plots, math and more — sampledoc 1.0 documentation</title>

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<a href="index.html"><h1 style="font-size: 3em;">Sampledoc</h1></a>

</div>

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<h3><a href="index.html">Table Of Contents</a></h3>

<ul>

<li><a class="reference internal" href="#">Sphinx extensions for embedded plots, math and more</a><ul>

<li><a class="reference internal" href="#ipython-sessions">ipython sessions</a></li>

<li><a class="reference internal" href="#using-math">Using math</a></li>

<li><a class="reference internal" href="#inserting-matplotlib-plots">Inserting matplotlib plots</a></li>

<li><a class="reference internal" href="#inheritance-diagrams">Inheritance diagrams</a></li>

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<li><a href="_sources/extensions.rst.txt"

rel="nofollow">Show Source</a></li>

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<h1>Sphinx extensions for embedded plots, math and more<a class="headerlink" href="#sphinx-extensions-for-embedded-plots-math-and-more" title="Permalink to this headline">¶</a></h1>

Sphinx is written in python, and supports the ability to write custom

extensions. We’ve written a few for the matplotlib documentation,

some of which are part of matplotlib itself in the

matplotlib.sphinxext module, some of which are included only in the

sphinx doc directory, and there are other extensions written by other

groups, eg numpy and ipython. We’re collecting these in this tutorial

and showing you how to install and use them for your own project.

First let’s grab the python extension files from the <code class="file docutils literal">sphinxext</code>

directory from git (see <a class="reference internal" href="getting_started.html#fetching-the-data">Fetching the data</a>), and install them in

our <code class="file docutils literal">sampledoc</code> project <code class="file docutils literal">sphinxext</code> directory:

<div class="highlight-default"><div class="highlight"><pre>home:~/tmp/sampledoc> mkdir sphinxext

home:~/tmp/sampledoc> cp ../sampledoc_tut/sphinxext/*.py sphinxext/

apigen.py docscrape.py docscrape_sphinx.py numpydoc.py

</pre></div>

</div>

In addition to the builtin matplotlib extensions for embedding pyplot

plots and rendering math with matplotlib’s native math engine, we also

have extensions for syntax highlighting ipython sessions, making

inhertiance diagrams, and more.

We need to inform sphinx of our new extensions in the <code class="file docutils literal">conf.py</code>

file by adding the following. First we tell it where to find the extensions:

<div class="highlight-default"><div class="highlight"><pre># If your extensions are in another directory, add it here. If the

# directory is relative to the documentation root, use

# os.path.abspath to make it absolute, like shown here.

sys.path.append(os.path.abspath('sphinxext'))

</pre></div>

</div>

And then we tell it what extensions to load:

<div class="highlight-default"><div class="highlight"><pre># Add any Sphinx extension module names here, as strings. They can be extensions

# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.

extensions = ['matplotlib.sphinxext.only_directives',

'matplotlib.sphinxext.plot_directive',

'IPython.sphinxext.ipython_directive',

'IPython.sphinxext.ipython_console_highlighting',

'sphinx.ext.mathjax',

'sphinx.ext.autodoc',

'sphinx.ext.doctest',

'sphinx.ext.inheritance_diagram',

'numpydoc']

</pre></div>

</div>

Now let’s look at some of these in action. You can see the literal

source for this file at extensions-literal.

<h2>ipython sessions<a class="headerlink" href="#ipython-sessions" title="Permalink to this headline">¶</a></h2>

Michael Droettboom contributed a sphinx extension which does <a class="reference external" href="http://pygments.org">pygments</a> syntax highlighting on <a class="reference external" href="http://ipython.scipy.org">ipython</a> sessions. Just use ipython as the

language in the <code class="docutils literal">sourcecode</code> directive:

<div class="highlight-default"><div class="highlight"><pre>.. sourcecode:: ipython

In [69]: lines = plot([1,2,3])

In [70]: setp(lines)

alpha: float

animated: [True | False]

antialiased or aa: [True | False]

...snip

</pre></div>

</div>

and you will get the syntax highlighted output below.

<div class="highlight-ipython"><div class="highlight"><pre>In [69]: lines = plot([1,2,3])

In [70]: setp(lines)

alpha: float

animated: [True | False]

antialiased or aa: [True | False]

...snip

</pre></div>

</div>

This support is included in this template, but will also be included

in a future version of Pygments by default.

</div>

<h2>Using math<a class="headerlink" href="#using-math" title="Permalink to this headline">¶</a></h2>

In sphinx you can include inline math \(x\leftarrow y\ x\forall

y\ x-y\) or display math

\[W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]\]</div>

To include math in your document, just use the math directive; here is

a simpler equation:

<div class="highlight-default"><div class="highlight"><pre>.. math::

W^{3\beta}_{\delta_1 \rho_1 \sigma_2} \approx U^{3\beta}_{\delta_1 \rho_1}

</pre></div>

</div>

which is rendered as

\[W^{3\beta}_{\delta_1 \rho_1 \sigma_2} \approx U^{3\beta}_{\delta_1 \rho_1}\]</div>

Recent versions of Sphinx include built-in support for math.

There are three flavors:

<li>sphinx.ext.pngmath: uses dvipng to render the equation</li>

<li>sphinx.ext.mathjax: renders the math in the browser using Javascript</li>

<li>sphinx.ext.jsmath: it’s an older code, but it checks out</li>

</ul>

</div></blockquote>

Additionally, matplotlib has its own math support:

<li>matplotlib.sphinxext.mathmpl</li>

</ul>

</div></blockquote>

See the matplotlib <a class="reference external" href="http://matplotlib.sourceforge.net/users/mathtext.html">mathtext guide</a> for lots

more information on writing mathematical expressions in matplotlib.

</div>

<h2>Inserting matplotlib plots<a class="headerlink" href="#inserting-matplotlib-plots" title="Permalink to this headline">¶</a></h2>

Inserting automatically-generated plots is easy. Simply put the

script to generate the plot in the <code class="file docutils literal">pyplots</code> directory, and

refer to it using the <code class="docutils literal">plot</code> directive. First make a

<code class="file docutils literal">pyplots</code> directory at the top level of your project (next to

:<code class="docutils literal">conf.py</code>) and copy the <code class="file docutils literal">ellipses.py`</code> file into it:

home:~/tmp/sampledoc> cp ../sampledoc_tut/pyplots/ellipses.py pyplots/

</pre></div>

</div>

You can refer to this file in your sphinx documentation; by default it

will just inline the plot with links to the source and PF and high

resolution PNGS. To also include the source code for the plot in the

document, pass the <code class="docutils literal">include-source</code> parameter:

<div class="highlight-default"><div class="highlight"><pre>.. plot:: pyplots/ellipses.py

:include-source:

</pre></div>

</div>

In the HTML version of the document, the plot includes links to the

original source code, a high-resolution PNG and a PDF. In the PDF

version of the document, the plot is included as a scalable PDF.

<div class="highlight-python"><div class="highlight"><pre>from pylab import *

from matplotlib.patches import Ellipse

delta = 45.0 # degrees

angles = arange(0, 360+delta, delta)

ells = [Ellipse((1, 1), 4, 2, a) for a in angles]

a = subplot(111, aspect='equal')

for e in ells:

e.set_clip_box(a.bbox)

e.set_alpha(0.1)

a.add_artist(e)

xlim(-2, 4)

ylim(-1, 3)

show()

</pre></div>

</div>

(<a class="reference external" href="./pyplots/ellipses.py">Source code</a>, <a class="reference external" href="./pyplots/ellipses.png">png</a>, <a class="reference external" href="./pyplots/ellipses.hires.png">hires.png</a>, <a class="reference external" href="./pyplots/ellipses.pdf">pdf</a>)

</div>

You can also inline code for plots directly, and the code will be

executed at documentation build time and the figure inserted into your

docs; the following code:

<div class="highlight-default"><div class="highlight"><pre>.. plot::

import matplotlib.pyplot as plt

import numpy as np

x = np.random.randn(1000)

plt.hist( x, 20)

plt.grid()

plt.title(r'Normal: $\mu=%.2f, \sigma=%.2f$'%(x.mean(), x.std()))

plt.show()

</pre></div>

</div>

produces this output:

(<a class="reference external" href=".//extensions-1.py">Source code</a>, <a class="reference external" href=".//extensions-1.png">png</a>, <a class="reference external" href=".//extensions-1.hires.png">hires.png</a>, <a class="reference external" href=".//extensions-1.pdf">pdf</a>)

</div>

See the matplotlib <a class="reference external" href="http://matplotlib.sourceforge.net/users/pyplot_tutorial.html">pyplot tutorial</a> and

the <a class="reference external" href="http://matplotlib.sourceforge.net/gallery.html">gallery</a> for

lots of examples of matplotlib plots.

</div>

<h2>Inheritance diagrams<a class="headerlink" href="#inheritance-diagrams" title="Permalink to this headline">¶</a></h2>

Inheritance diagrams can be inserted directly into the document by

providing a list of class or module names to the

<code class="docutils literal">inheritance-diagram</code> directive.

For example:

<div class="highlight-default"><div class="highlight"><pre>.. inheritance-diagram:: codecs

</pre></div>

</div>

produces:

</map>

See the <a class="reference internal" href="ipython_directive.html#ipython-directive">Ipython Directive</a> for a tutorial on embedding stateful,

matplotlib aware ipython sessions into your rest docs with multiline

and doctest support.

</div>

<div class="highlight-default"><div class="highlight"><pre>.. _extensions:

****************************************************

Sphinx extensions for embedded plots, math and more

****************************************************

Sphinx is written in python, and supports the ability to write custom

extensions. We've written a few for the matplotlib documentation,

some of which are part of matplotlib itself in the

matplotlib.sphinxext module, some of which are included only in the

sphinx doc directory, and there are other extensions written by other

groups, eg numpy and ipython. We're collecting these in this tutorial

and showing you how to install and use them for your own project.

First let's grab the python extension files from the :file:`sphinxext`

directory from git (see :ref:`fetching-the-data`), and install them in

our :file:`sampledoc` project :file:`sphinxext` directory::

home:~/tmp/sampledoc> mkdir sphinxext

home:~/tmp/sampledoc> cp ../sampledoc_tut/sphinxext/*.py sphinxext/

home:~/tmp/sampledoc> ls sphinxext/

apigen.py docscrape.py docscrape_sphinx.py numpydoc.py

In addition to the builtin matplotlib extensions for embedding pyplot

plots and rendering math with matplotlib's native math engine, we also

have extensions for syntax highlighting ipython sessions, making

inhertiance diagrams, and more.

We need to inform sphinx of our new extensions in the :file:`conf.py`

file by adding the following. First we tell it where to find the extensions::

# If your extensions are in another directory, add it here. If the

# directory is relative to the documentation root, use

# os.path.abspath to make it absolute, like shown here.

sys.path.append(os.path.abspath('sphinxext'))

And then we tell it what extensions to load::

# Add any Sphinx extension module names here, as strings. They can be extensions

# coming with Sphinx (named 'sphinx.ext.*') or your custom ones.

extensions = ['matplotlib.sphinxext.only_directives',

'matplotlib.sphinxext.plot_directive',

'IPython.sphinxext.ipython_directive',

'IPython.sphinxext.ipython_console_highlighting',

'sphinx.ext.mathjax',

'sphinx.ext.autodoc',

'sphinx.ext.doctest',

'sphinx.ext.inheritance_diagram',

'numpydoc']

Now let's look at some of these in action. You can see the literal

source for this file at :ref:`extensions-literal`.

.. _ipython-highlighting:

ipython sessions

================

Michael Droettboom contributed a sphinx extension which does `pygments

<http://pygments.org>`_ syntax highlighting on `ipython

<http://ipython.scipy.org>`_ sessions. Just use ipython as the

language in the ``sourcecode`` directive::

.. sourcecode:: ipython

In [69]: lines = plot([1,2,3])

In [70]: setp(lines)

alpha: float

animated: [True | False]

antialiased or aa: [True | False]

...snip

and you will get the syntax highlighted output below.

.. sourcecode:: ipython

In [69]: lines = plot([1,2,3])

In [70]: setp(lines)

alpha: float

animated: [True | False]

antialiased or aa: [True | False]

...snip

This support is included in this template, but will also be included

in a future version of Pygments by default.

.. _using-math:

Using math

==========

In sphinx you can include inline math :math:`x\leftarrow y\ x\forall

y\ x-y` or display math

.. math::

W^{3\beta}_{\delta_1 \rho_1 \sigma_2} = U^{3\beta}_{\delta_1 \rho_1} + \frac{1}{8 \pi 2} \int^{\alpha_2}_{\alpha_2} d \alpha^\prime_2 \left[\frac{ U^{2\beta}_{\delta_1 \rho_1} - \alpha^\prime_2U^{1\beta}_{\rho_1 \sigma_2} }{U^{0\beta}_{\rho_1 \sigma_2}}\right]

To include math in your document, just use the math directive; here is

a simpler equation::

.. math::

W^{3\beta}_{\delta_1 \rho_1 \sigma_2} \approx U^{3\beta}_{\delta_1 \rho_1}

which is rendered as

.. math::

W^{3\beta}_{\delta_1 \rho_1 \sigma_2} \approx U^{3\beta}_{\delta_1 \rho_1}

Recent versions of Sphinx include built-in support for math.

There are three flavors:

- sphinx.ext.pngmath: uses dvipng to render the equation

- sphinx.ext.mathjax: renders the math in the browser using Javascript

- sphinx.ext.jsmath: it's an older code, but it checks out

Additionally, matplotlib has its own math support:

- matplotlib.sphinxext.mathmpl

See the matplotlib `mathtext guide

<http://matplotlib.sourceforge.net/users/mathtext.html>`_ for lots

more information on writing mathematical expressions in matplotlib.

.. _pyplots:

Inserting matplotlib plots

==========================

Inserting automatically-generated plots is easy. Simply put the

script to generate the plot in the :file:`pyplots` directory, and

refer to it using the ``plot`` directive. First make a

:file:`pyplots` directory at the top level of your project (next to

:``conf.py``) and copy the :file:`ellipses.py`` file into it::

home:~/tmp/sampledoc> mkdir pyplots

home:~/tmp/sampledoc> cp ../sampledoc_tut/pyplots/ellipses.py pyplots/

You can refer to this file in your sphinx documentation; by default it

will just inline the plot with links to the source and PF and high

resolution PNGS. To also include the source code for the plot in the

document, pass the ``include-source`` parameter::

.. plot:: pyplots/ellipses.py

:include-source:

In the HTML version of the document, the plot includes links to the

original source code, a high-resolution PNG and a PDF. In the PDF

version of the document, the plot is included as a scalable PDF.

.. plot:: pyplots/ellipses.py

:include-source:

You can also inline code for plots directly, and the code will be

executed at documentation build time and the figure inserted into your

docs; the following code::

.. plot::

import matplotlib.pyplot as plt

import numpy as np

x = np.random.randn(1000)

plt.hist( x, 20)

plt.grid()

plt.title(r'Normal: $\mu=%.2f, \sigma=%.2f$'%(x.mean(), x.std()))

plt.show()

produces this output:

.. plot::

import matplotlib.pyplot as plt

import numpy as np

x = np.random.randn(1000)

plt.hist( x, 20)

plt.grid()

plt.title(r'Normal: $\mu=%.2f, \sigma=%.2f$'%(x.mean(), x.std()))

plt.show()

See the matplotlib `pyplot tutorial

<http://matplotlib.sourceforge.net/users/pyplot_tutorial.html>`_ and

the `gallery <http://matplotlib.sourceforge.net/gallery.html>`_ for

lots of examples of matplotlib plots.

Inheritance diagrams

====================

Inheritance diagrams can be inserted directly into the document by

providing a list of class or module names to the

``inheritance-diagram`` directive.

For example::

.. inheritance-diagram:: codecs

produces:

.. inheritance-diagram:: codecs

.. _extensions-literal:

See the :ref:`ipython_directive` for a tutorial on embedding stateful,

matplotlib aware ipython sessions into your rest docs with multiline

and doctest support.

This file

=========

.. literalinclude:: extensions.rst

</pre></div>

</div>

</div>

<h3>Navigation</h3>

<ul>

<a href="genindex.html" title="General Index"

>index</a></li>

<a href="ipython_directive.html" title="Ipython Directive"

>next</a> |</li>

<a href="custom_look.html" title="Customizing the look and feel of the site"

>previous</a> |</li>

<li><a href="search.html">search</a>| </li>

</ul>

</div>

Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.5.1.

</div>

</body>

</html>

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