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<li><a class="reference internal" href="#defining-your-own-style">Defining your own style</a></li>
<li><a class="reference internal" href="#composing-styles">Composing styles</a></li>
<li><a class="reference internal" href="#temporary-styling">Temporary styling</a></li>
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<div class="section" id="customizing-matplotlib">
<span id="id1"></span><h1>Customizing matplotlib<a class="headerlink" href="#customizing-matplotlib" title="Permalink to this headline">¶</a></h1>
<div class="section" id="using-style-sheets">
<h2>Using style sheets<a class="headerlink" href="#using-style-sheets" title="Permalink to this headline">¶</a></h2>
<p>The <code class="docutils literal"><span class="pre">style</span></code> package adds support for easy-to-switch plotting “styles” with
the same parameters as a <a class="reference external" href="http://matplotlib.org/users/customizing.html">matplotlibrc</a> file (which is read at startup to
configure matplotlib).</p>
<p>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 <a class="reference external" href="http://ggplot2.org/">ggplot</a> (a popular plotting package for <a class="reference external" href="https://www.r-project.org/">R</a>). To use this style,
just add:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'ggplot'</span><span class="p">)</span>
</pre></div>
</div>
<p>To list all available styles, use:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="nb">print</span><span class="p">(</span><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">available</span><span class="p">)</span>
</pre></div>
</div>
<div class="section" id="defining-your-own-style">
<h3>Defining your own style<a class="headerlink" href="#defining-your-own-style" title="Permalink to this headline">¶</a></h3>
<p>You can create custom styles and use them by calling <code class="docutils literal"><span class="pre">style.use</span></code> with the
path or URL to the style sheet. Additionally, if you add your
<code class="docutils literal"><span class="pre"><style-name>.mplstyle</span></code> file to <code class="docutils literal"><span class="pre">mpl_configdir/stylelib</span></code>, you can reuse
your custom style sheet with a call to <code class="docutils literal"><span class="pre">style.use(<style-name>)</span></code>. By default
<code class="docutils literal"><span class="pre">mpl_configdir</span></code> should be <code class="docutils literal"><span class="pre">~/.config/matplotlib</span></code>, but you can check where
yours is with <code class="docutils literal"><span class="pre">matplotlib.get_configdir()</span></code>; 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 <a class="reference internal" href="../faq/troubleshooting_faq.html#locating-matplotlib-config-dir"><span class="std std-ref">matplotlib configuration and cache directory locations</span></a>.</p>
<p>Note that a custom style sheet in <code class="docutils literal"><span class="pre">mpl_configdir/stylelib</span></code> will
override a style sheet defined by matplotlib if the styles have the same name.</p>
<p>For example, you might want to create
<code class="docutils literal"><span class="pre">mpl_configdir/stylelib/presentation.mplstyle</span></code> with the following:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">axes</span><span class="o">.</span><span class="n">titlesize</span> <span class="p">:</span> <span class="mi">24</span>
<span class="n">axes</span><span class="o">.</span><span class="n">labelsize</span> <span class="p">:</span> <span class="mi">20</span>
<span class="n">lines</span><span class="o">.</span><span class="n">linewidth</span> <span class="p">:</span> <span class="mi">3</span>
<span class="n">lines</span><span class="o">.</span><span class="n">markersize</span> <span class="p">:</span> <span class="mi">10</span>
<span class="n">xtick</span><span class="o">.</span><span class="n">labelsize</span> <span class="p">:</span> <span class="mi">16</span>
<span class="n">ytick</span><span class="o">.</span><span class="n">labelsize</span> <span class="p">:</span> <span class="mi">16</span>
</pre></div>
</div>
<p>Then, when you want to adapt a plot designed for a paper to one that looks
good in a presentation, you can just add:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s1">'presentation'</span><span class="p">)</span>
</pre></div>
</div>
</div>
<div class="section" id="composing-styles">
<h3>Composing styles<a class="headerlink" href="#composing-styles" title="Permalink to this headline">¶</a></h3>
<p>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:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">use</span><span class="p">([</span><span class="s1">'dark_background'</span><span class="p">,</span> <span class="s1">'presentation'</span><span class="p">])</span>
</pre></div>
</div>
<p>Note that styles further to the right will overwrite values that are already
defined by styles on the left.</p>
</div>
<div class="section" id="temporary-styling">
<h3>Temporary styling<a class="headerlink" href="#temporary-styling" title="Permalink to this headline">¶</a></h3>
<p>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:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="k">with</span> <span class="n">plt</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">context</span><span class="p">((</span><span class="s1">'dark_background'</span><span class="p">)):</span>
<span class="gp">>>> </span> <span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">2</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="p">)),</span> <span class="s1">'r-o'</span><span class="p">)</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="c1"># Some plotting code with the default style</span>
<span class="go">>>></span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
</div>
</div>
</div>
<div class="section" id="matplotlib-rcparams">
<h2>matplotlib rcParams<a class="headerlink" href="#matplotlib-rcparams" title="Permalink to this headline">¶</a></h2>
<div class="section" id="dynamic-rc-settings">
<span id="customizing-with-dynamic-rc-settings"></span><h3>Dynamic rc settings<a class="headerlink" href="#dynamic-rc-settings" title="Permalink to this headline">¶</a></h3>
<p>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 <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rcParams" title="matplotlib.rcParams"><code class="xref py py-data docutils literal"><span class="pre">matplotlib.rcParams</span></code></a>, which is global to
the matplotlib package. rcParams can be modified directly, for example:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">'lines.linewidth'</span><span class="p">]</span> <span class="o">=</span> <span class="mi">2</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rcParams</span><span class="p">[</span><span class="s1">'lines.color'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'r'</span>
</pre></div>
</div>
<p>Matplotlib also provides a couple of convenience functions for modifying rc
settings. The <a class="reference internal" href="../api/matplotlib_configuration_api.html#matplotlib.rc" title="matplotlib.rc"><code class="xref py py-func docutils literal"><span class="pre">matplotlib.rc()</span></code></a> command can be used to modify multiple
settings in a single group at once, using keyword arguments:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">mpl</span>
<span class="n">mpl</span><span class="o">.</span><span class="n">rc</span><span class="p">(</span><span class="s1">'lines'</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'r'</span><span class="p">)</span>
</pre></div>
</div>
<p>The <code class="xref py py-func docutils literal"><span class="pre">matplotlib.rcdefaults()</span></code> command will restore the standard matplotlib
default settings.</p>
<p>There is some degree of validation when setting the values of rcParams, see
<a class="reference internal" href="../api/rcsetup_api.html#module-matplotlib.rcsetup" title="matplotlib.rcsetup"><code class="xref py py-mod docutils literal"><span class="pre">matplotlib.rcsetup</span></code></a> for details.</p>
</div>
<div class="section" id="the-matplotlibrc-file">
<span id="customizing-with-matplotlibrc-files"></span><h3>The <code class="file docutils literal"><span class="pre">matplotlibrc</span></code> file<a class="headerlink" href="#the-matplotlibrc-file" title="Permalink to this headline">¶</a></h3>
<p>matplotlib uses <code class="file docutils literal"><span class="pre">matplotlibrc</span></code> configuration files to customize all kinds
of properties, which we call <code class="xref py py-obj docutils literal"><span class="pre">rc</span> <span class="pre">settings</span></code> or <code class="xref py py-obj docutils literal"><span class="pre">rc</span> <span class="pre">parameters</span></code>. 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 <code class="file docutils literal"><span class="pre">matplotlibrc</span></code> in four
locations, in the following order:</p>
<ol class="arabic">
<li><p class="first"><code class="file docutils literal"><span class="pre">matplotlibrc</span></code> in the current working directory, usually used for
specific customizations that you do not want to apply elsewhere.</p>
</li>
<li><p class="first"><code class="file docutils literal"><span class="pre">$MATPLOTLIBRC/matplotlibrc</span></code>.</p>
</li>
<li><p class="first">It next looks in a user-specific place, depending on your platform:</p>
<ul class="simple">
<li>On Linux and FreeBSD, it looks in <code class="file docutils literal"><span class="pre">.config/matplotlib/matplotlibrc</span></code>
(or <code class="xref py py-obj docutils literal"><span class="pre">$XDG_CONFIG_HOME/matplotlib/matplotlibrc</span></code>) if you’ve customized
your environment.</li>
<li>On other platforms, it looks in <code class="file docutils literal"><span class="pre">.matplotlib/matplotlibrc</span></code>.</li>
</ul>
<p>See <a class="reference internal" href="../faq/troubleshooting_faq.html#locating-matplotlib-config-dir"><span class="std std-ref">matplotlib configuration and cache directory locations</span></a>.</p>
</li>
<li><p class="first"><code class="file docutils literal"><em><span class="pre">INSTALL</span></em><span class="pre">/matplotlib/mpl-data/matplotlibrc</span></code>, where
<code class="file docutils literal"><em><span class="pre">INSTALL</span></em></code> is something like
<code class="file docutils literal"><span class="pre">/usr/lib/python3.5/site-packages</span></code> on Linux, and maybe
<code class="file docutils literal"><span class="pre">C:\Python35\Lib\site-packages</span></code> 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.</p>
</li>
</ol>
<p>To display where the currently active <code class="file docutils literal"><span class="pre">matplotlibrc</span></code> file was
loaded from, one can do the following:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="gp">>>> </span><span class="n">matplotlib</span><span class="o">.</span><span class="n">matplotlib_fname</span><span class="p">()</span>
<span class="go">'/home/foo/.config/matplotlib/matplotlibrc'</span>
</pre></div>
</div>
<p>See below for a sample <a class="reference internal" href="#matplotlibrc-sample"><span class="std std-ref">matplotlibrc file</span></a>.</p>
<div class="section" id="a-sample-matplotlibrc-file">
<span id="matplotlibrc-sample"></span><h4>A sample matplotlibrc file<a class="headerlink" href="#a-sample-matplotlibrc-file" title="Permalink to this headline">¶</a></h4>
<a class="reference external" href="../_static/matplotlibrc">(download)</a><div class="highlight-default"><div class="highlight"><pre><span></span><span class="c1">### MATPLOTLIBRC FORMAT</span>
<span class="c1"># This is a sample matplotlib configuration file - you can find a copy</span>
<span class="c1"># of it on your system in</span>
<span class="c1"># site-packages/matplotlib/mpl-data/matplotlibrc. If you edit it</span>
<span class="c1"># there, please note that it will be overwritten in your next install.</span>
<span class="c1"># If you want to keep a permanent local copy that will not be</span>
<span class="c1"># overwritten, place it in the following location:</span>
<span class="c1"># unix/linux:</span>
<span class="c1"># $HOME/.config/matplotlib/matplotlibrc or</span>
<span class="c1"># $XDG_CONFIG_HOME/matplotlib/matplotlibrc (if $XDG_CONFIG_HOME is set)</span>
<span class="c1"># other platforms:</span>
<span class="c1"># $HOME/.matplotlib/matplotlibrc</span>
<span class="c1">#</span>
<span class="c1"># See http://matplotlib.org/users/customizing.html#the-matplotlibrc-file for</span>
<span class="c1"># more details on the paths which are checked for the configuration file.</span>
<span class="c1">#</span>
<span class="c1"># This file is best viewed in a editor which supports python mode</span>
<span class="c1"># syntax highlighting. Blank lines, or lines starting with a comment</span>
<span class="c1"># symbol, are ignored, as are trailing comments. Other lines must</span>
<span class="c1"># have the format</span>
<span class="c1"># key : val # optional comment</span>
<span class="c1">#</span>
<span class="c1"># Colors: for the color values below, you can either use - a</span>
<span class="c1"># matplotlib color string, such as r, k, or b - an rgb tuple, such as</span>
<span class="c1"># (1.0, 0.5, 0.0) - a hex string, such as ff00ff - a scalar</span>
<span class="c1"># grayscale intensity such as 0.75 - a legal html color name, e.g., red,</span>
<span class="c1"># blue, darkslategray</span>
<span class="c1">#### CONFIGURATION BEGINS HERE</span>
<span class="c1"># The default backend; one of GTK GTKAgg GTKCairo GTK3Agg GTK3Cairo</span>
<span class="c1"># MacOSX Qt4Agg Qt5Agg TkAgg WX WXAgg Agg Cairo GDK PS PDF SVG</span>
<span class="c1"># Template.</span>
<span class="c1"># You can also deploy your own backend outside of matplotlib by</span>
<span class="c1"># referring to the module name (which must be in the PYTHONPATH) as</span>
<span class="c1"># 'module://my_backend'.</span>
<span class="n">backend</span> <span class="p">:</span> <span class="n">TkAgg</span>
<span class="c1"># If you are using the Qt4Agg backend, you can choose here</span>
<span class="c1"># to use the PyQt4 bindings or the newer PySide bindings to</span>
<span class="c1"># the underlying Qt4 toolkit.</span>
<span class="c1">#backend.qt4 : PyQt4 # PyQt4 | PySide</span>
<span class="c1"># Note that this can be overridden by the environment variable</span>
<span class="c1"># QT_API used by Enthought Tool Suite (ETS); valid values are</span>
<span class="c1"># "pyqt" and "pyside". The "pyqt" setting has the side effect of</span>
<span class="c1"># forcing the use of Version 2 API for QString and QVariant.</span>
<span class="c1"># The port to use for the web server in the WebAgg backend.</span>
<span class="c1"># webagg.port : 8888</span>
<span class="c1"># If webagg.port is unavailable, a number of other random ports will</span>
<span class="c1"># be tried until one that is available is found.</span>
<span class="c1"># webagg.port_retries : 50</span>
<span class="c1"># When True, open the webbrowser to the plot that is shown</span>
<span class="c1"># webagg.open_in_browser : True</span>
<span class="c1"># When True, the figures rendered in the nbagg backend are created with</span>
<span class="c1"># a transparent background.</span>
<span class="c1"># nbagg.transparent : False</span>
<span class="c1"># if you are running pyplot inside a GUI and your backend choice</span>
<span class="c1"># conflicts, we will automatically try to find a compatible one for</span>
<span class="c1"># you if backend_fallback is True</span>
<span class="c1">#backend_fallback: True</span>
<span class="c1">#interactive : False</span>
<span class="c1">#toolbar : toolbar2 # None | toolbar2 ("classic" is deprecated)</span>
<span class="c1">#timezone : UTC # a pytz timezone string, e.g., US/Central or Europe/Paris</span>
<span class="c1"># Where your matplotlib data lives if you installed to a non-default</span>
<span class="c1"># location. This is where the matplotlib fonts, bitmaps, etc reside</span>
<span class="c1">#datapath : /home/jdhunter/mpldata</span>
<span class="c1">### LINES</span>
<span class="c1"># See http://matplotlib.org/api/artist_api.html#module-matplotlib.lines for more</span>
<span class="c1"># information on line properties.</span>
<span class="c1">#lines.linewidth : 1.5 # line width in points</span>
<span class="c1">#lines.linestyle : - # solid line</span>
<span class="c1">#lines.color : C0 # has no affect on plot(); see axes.prop_cycle</span>
<span class="c1">#lines.marker : None # the default marker</span>
<span class="c1">#lines.markeredgewidth : 1.0 # the line width around the marker symbol</span>
<span class="c1">#lines.markersize : 6 # markersize, in points</span>
<span class="c1">#lines.dash_joinstyle : miter # miter|round|bevel</span>
<span class="c1">#lines.dash_capstyle : butt # butt|round|projecting</span>
<span class="c1">#lines.solid_joinstyle : miter # miter|round|bevel</span>
<span class="c1">#lines.solid_capstyle : projecting # butt|round|projecting</span>
<span class="c1">#lines.antialiased : True # render lines in antialiased (no jaggies)</span>
<span class="c1"># The three standard dash patterns. These are scaled by the linewidth.</span>
<span class="c1">#lines.dashed_pattern : 2.8, 1.2</span>
<span class="c1">#lines.dashdot_pattern : 4.8, 1.2, 0.8, 1.2</span>
<span class="c1">#lines.dotted_pattern : 1.1, 1.1</span>
<span class="c1">#lines.scale_dashes : True</span>
<span class="c1">#markers.fillstyle: full # full|left|right|bottom|top|none</span>
<span class="c1">### PATCHES</span>
<span class="c1"># Patches are graphical objects that fill 2D space, like polygons or</span>
<span class="c1"># circles. See</span>
<span class="c1"># http://matplotlib.org/api/artist_api.html#module-matplotlib.patches</span>
<span class="c1"># information on patch properties</span>
<span class="c1">#patch.linewidth : 1 # edge width in points.</span>
<span class="c1">#patch.facecolor : C0</span>
<span class="c1">#patch.edgecolor : black # if forced, or patch is not filled</span>
<span class="c1">#patch.force_edgecolor : False # True to always use edgecolor</span>
<span class="c1">#patch.antialiased : True # render patches in antialiased (no jaggies)</span>
<span class="c1">### HATCHES</span>
<span class="c1">#hatch.color : k</span>
<span class="c1">#hatch.linewidth : 1.0</span>
<span class="c1">### Boxplot</span>
<span class="c1">#boxplot.notch : False</span>
<span class="c1">#boxplot.vertical : True</span>
<span class="c1">#boxplot.whiskers : 1.5</span>
<span class="c1">#boxplot.bootstrap : None</span>
<span class="c1">#boxplot.patchartist : False</span>
<span class="c1">#boxplot.showmeans : False</span>
<span class="c1">#boxplot.showcaps : True</span>
<span class="c1">#boxplot.showbox : True</span>
<span class="c1">#boxplot.showfliers : True</span>
<span class="c1">#boxplot.meanline : False</span>
<span class="c1">#boxplot.flierprops.color : 'k'</span>
<span class="c1">#boxplot.flierprops.marker : 'o'</span>
<span class="c1">#boxplot.flierprops.markerfacecolor : 'none'</span>
<span class="c1">#boxplot.flierprops.markeredgecolor : 'k'</span>
<span class="c1">#boxplot.flierprops.markersize : 6</span>
<span class="c1">#boxplot.flierprops.linestyle : 'none'</span>
<span class="c1">#boxplot.flierprops.linewidth : 1.0</span>
<span class="c1">#boxplot.boxprops.color : 'k'</span>
<span class="c1">#boxplot.boxprops.linewidth : 1.0</span>
<span class="c1">#boxplot.boxprops.linestyle : '-'</span>
<span class="c1">#boxplot.whiskerprops.color : 'k'</span>
<span class="c1">#boxplot.whiskerprops.linewidth : 1.0</span>
<span class="c1">#boxplot.whiskerprops.linestyle : '-'</span>
<span class="c1">#boxplot.capprops.color : 'k'</span>
<span class="c1">#boxplot.capprops.linewidth : 1.0</span>
<span class="c1">#boxplot.capprops.linestyle : '-'</span>
<span class="c1">#boxplot.medianprops.color : 'C1'</span>
<span class="c1">#boxplot.medianprops.linewidth : 1.0</span>
<span class="c1">#boxplot.medianprops.linestyle : '-'</span>
<span class="c1">#boxplot.meanprops.color : 'C2'</span>
<span class="c1">#boxplot.meanprops.marker : '^'</span>
<span class="c1">#boxplot.meanprops.markerfacecolor : 'C2'</span>
<span class="c1">#boxplot.meanprops.markeredgecolor : 'C2'</span>
<span class="c1">#boxplot.meanprops.markersize : 6</span>
<span class="c1">#boxplot.meanprops.linestyle : 'none'</span>
<span class="c1">#boxplot.meanprops.linewidth : 1.0</span>
<span class="c1">### FONT</span>
<span class="c1">#</span>
<span class="c1"># font properties used by text.Text. See</span>
<span class="c1"># http://matplotlib.org/api/font_manager_api.html for more</span>
<span class="c1"># information on font properties. The 6 font properties used for font</span>
<span class="c1"># matching are given below with their default values.</span>
<span class="c1">#</span>
<span class="c1"># The font.family property has five values: 'serif' (e.g., Times),</span>
<span class="c1"># 'sans-serif' (e.g., Helvetica), 'cursive' (e.g., Zapf-Chancery),</span>
<span class="c1"># 'fantasy' (e.g., Western), and 'monospace' (e.g., Courier). Each of</span>
<span class="c1"># these font families has a default list of font names in decreasing</span>
<span class="c1"># order of priority associated with them. When text.usetex is False,</span>
<span class="c1"># font.family may also be one or more concrete font names.</span>
<span class="c1">#</span>
<span class="c1"># The font.style property has three values: normal (or roman), italic</span>
<span class="c1"># or oblique. The oblique style will be used for italic, if it is not</span>
<span class="c1"># present.</span>
<span class="c1">#</span>
<span class="c1"># The font.variant property has two values: normal or small-caps. For</span>
<span class="c1"># TrueType fonts, which are scalable fonts, small-caps is equivalent</span>
<span class="c1"># to using a font size of 'smaller', or about 83%% of the current font</span>
<span class="c1"># size.</span>
<span class="c1">#</span>
<span class="c1"># The font.weight property has effectively 13 values: normal, bold,</span>
<span class="c1"># bolder, lighter, 100, 200, 300, ..., 900. Normal is the same as</span>
<span class="c1"># 400, and bold is 700. bolder and lighter are relative values with</span>
<span class="c1"># respect to the current weight.</span>
<span class="c1">#</span>
<span class="c1"># The font.stretch property has 11 values: ultra-condensed,</span>
<span class="c1"># extra-condensed, condensed, semi-condensed, normal, semi-expanded,</span>
<span class="c1"># expanded, extra-expanded, ultra-expanded, wider, and narrower. This</span>
<span class="c1"># property is not currently implemented.</span>
<span class="c1">#</span>
<span class="c1"># The font.size property is the default font size for text, given in pts.</span>
<span class="c1"># 10 pt is the standard value.</span>
<span class="c1">#</span>
<span class="c1">#font.family : sans-serif</span>
<span class="c1">#font.style : normal</span>
<span class="c1">#font.variant : normal</span>
<span class="c1">#font.weight : medium</span>
<span class="c1">#font.stretch : normal</span>
<span class="c1"># note that font.size controls default text sizes. To configure</span>
<span class="c1"># special text sizes tick labels, axes, labels, title, etc, see the rc</span>
<span class="c1"># settings for axes and ticks. Special text sizes can be defined</span>
<span class="c1"># relative to font.size, using the following values: xx-small, x-small,</span>
<span class="c1"># small, medium, large, x-large, xx-large, larger, or smaller</span>
<span class="c1">#font.size : 10.0</span>
<span class="c1">#font.serif : DejaVu Serif, Bitstream Vera Serif, New Century Schoolbook, Century Schoolbook L, Utopia, ITC Bookman, Bookman, Nimbus Roman No9 L, Times New Roman, Times, Palatino, Charter, serif</span>
<span class="c1">#font.sans-serif : DejaVu Sans, Bitstream Vera Sans, Lucida Grande, Verdana, Geneva, Lucid, Arial, Helvetica, Avant Garde, sans-serif</span>
<span class="c1">#font.cursive : Apple Chancery, Textile, Zapf Chancery, Sand, Script MT, Felipa, cursive</span>
<span class="c1">#font.fantasy : Comic Sans MS, Chicago, Charcoal, Impact, Western, Humor Sans, xkcd, fantasy</span>
<span class="c1">#font.monospace : DejaVu Sans Mono, Bitstream Vera Sans Mono, Andale Mono, Nimbus Mono L, Courier New, Courier, Fixed, Terminal, monospace</span>
<span class="c1">### TEXT</span>
<span class="c1"># text properties used by text.Text. See</span>
<span class="c1"># http://matplotlib.org/api/artist_api.html#module-matplotlib.text for more</span>
<span class="c1"># information on text properties</span>
<span class="c1">#text.color : black</span>
<span class="c1">### LaTeX customizations. See http://wiki.scipy.org/Cookbook/Matplotlib/UsingTex</span>
<span class="c1">#text.usetex : False # use latex for all text handling. The following fonts</span>
<span class="c1"># are supported through the usual rc parameter settings:</span>
<span class="c1"># new century schoolbook, bookman, times, palatino,</span>
<span class="c1"># zapf chancery, charter, serif, sans-serif, helvetica,</span>
<span class="c1"># avant garde, courier, monospace, computer modern roman,</span>
<span class="c1"># computer modern sans serif, computer modern typewriter</span>
<span class="c1"># If another font is desired which can loaded using the</span>
<span class="c1"># LaTeX \usepackage command, please inquire at the</span>
<span class="c1"># matplotlib mailing list</span>
<span class="c1">#text.latex.unicode : False # use "ucs" and "inputenc" LaTeX packages for handling</span>
<span class="c1"># unicode strings.</span>
<span class="c1">#text.latex.preamble : # IMPROPER USE OF THIS FEATURE WILL LEAD TO LATEX FAILURES</span>
<span class="c1"># AND IS THEREFORE UNSUPPORTED. PLEASE DO NOT ASK FOR HELP</span>
<span class="c1"># IF THIS FEATURE DOES NOT DO WHAT YOU EXPECT IT TO.</span>
<span class="c1"># preamble is a comma separated list of LaTeX statements</span>
<span class="c1"># that are included in the LaTeX document preamble.</span>
<span class="c1"># An example:</span>
<span class="c1"># text.latex.preamble : \usepackage{bm},\usepackage{euler}</span>
<span class="c1"># The following packages are always loaded with usetex, so</span>
<span class="c1"># beware of package collisions: color, geometry, graphicx,</span>
<span class="c1"># type1cm, textcomp. Adobe Postscript (PSSNFS) font packages</span>
<span class="c1"># may also be loaded, depending on your font settings</span>
<span class="c1">#text.dvipnghack : None # some versions of dvipng don't handle alpha</span>
<span class="c1"># channel properly. Use True to correct</span>
<span class="c1"># and flush ~/.matplotlib/tex.cache</span>
<span class="c1"># before testing and False to force</span>
<span class="c1"># correction off. None will try and</span>
<span class="c1"># guess based on your dvipng version</span>
<span class="c1">#text.hinting : auto # May be one of the following:</span>
<span class="c1"># 'none': Perform no hinting</span>
<span class="c1"># 'auto': Use FreeType's autohinter</span>
<span class="c1"># 'native': Use the hinting information in the</span>
<span class="c1"># font file, if available, and if your</span>
<span class="c1"># FreeType library supports it</span>
<span class="c1"># 'either': Use the native hinting information,</span>
<span class="c1"># or the autohinter if none is available.</span>
<span class="c1"># For backward compatibility, this value may also be</span>
<span class="c1"># True === 'auto' or False === 'none'.</span>
<span class="c1">#text.hinting_factor : 8 # Specifies the amount of softness for hinting in the</span>
<span class="c1"># horizontal direction. A value of 1 will hint to full</span>
<span class="c1"># pixels. A value of 2 will hint to half pixels etc.</span>
<span class="c1">#text.antialiased : True # If True (default), the text will be antialiased.</span>
<span class="c1"># This only affects the Agg backend.</span>
<span class="c1"># The following settings allow you to select the fonts in math mode.</span>
<span class="c1"># They map from a TeX font name to a fontconfig font pattern.</span>
<span class="c1"># These settings are only used if mathtext.fontset is 'custom'.</span>
<span class="c1"># Note that this "custom" mode is unsupported and may go away in the</span>
<span class="c1"># future.</span>
<span class="c1">#mathtext.cal : cursive</span>
<span class="c1">#mathtext.rm : serif</span>
<span class="c1">#mathtext.tt : monospace</span>
<span class="c1">#mathtext.it : serif:italic</span>
<span class="c1">#mathtext.bf : serif:bold</span>
<span class="c1">#mathtext.sf : sans</span>
<span class="c1">#mathtext.fontset : dejavusans # Should be 'dejavusans' (default),</span>
<span class="c1"># 'dejavuserif', 'cm' (Computer Modern), 'stix',</span>
<span class="c1"># 'stixsans' or 'custom'</span>
<span class="c1">#mathtext.fallback_to_cm : True # When True, use symbols from the Computer Modern</span>
<span class="c1"># fonts when a symbol can not be found in one of</span>
<span class="c1"># the custom math fonts.</span>
<span class="c1">#mathtext.default : it # The default font to use for math.</span>
<span class="c1"># Can be any of the LaTeX font names, including</span>
<span class="c1"># the special name "regular" for the same font</span>
<span class="c1"># used in regular text.</span>
<span class="c1">### AXES</span>
<span class="c1"># default face and edge color, default tick sizes,</span>
<span class="c1"># default fontsizes for ticklabels, and so on. See</span>
<span class="c1"># http://matplotlib.org/api/axes_api.html#module-matplotlib.axes</span>
<span class="c1">#axes.facecolor : white # axes background color</span>
<span class="c1">#axes.edgecolor : black # axes edge color</span>
<span class="c1">#axes.linewidth : 0.8 # edge linewidth</span>
<span class="c1">#axes.grid : False # display grid or not</span>
<span class="c1">#axes.titlesize : large # fontsize of the axes title</span>
<span class="c1">#axes.titlepad : 6.0 # pad between axes and title in points</span>
<span class="c1">#axes.labelsize : medium # fontsize of the x any y labels</span>
<span class="c1">#axes.labelpad : 4.0 # space between label and axis</span>
<span class="c1">#axes.labelweight : normal # weight of the x and y labels</span>
<span class="c1">#axes.labelcolor : black</span>
<span class="c1">#axes.axisbelow : 'line' # draw axis gridlines and ticks below</span>
<span class="c1"># patches (True); above patches but below</span>
<span class="c1"># lines ('line'); or above all (False)</span>
<span class="c1">#axes.formatter.limits : -7, 7 # use scientific notation if log10</span>
<span class="c1"># of the axis range is smaller than the</span>
<span class="c1"># first or larger than the second</span>
<span class="c1">#axes.formatter.use_locale : False # When True, format tick labels</span>
<span class="c1"># according to the user's locale.</span>
<span class="c1"># For example, use ',' as a decimal</span>
<span class="c1"># separator in the fr_FR locale.</span>
<span class="c1">#axes.formatter.use_mathtext : False # When True, use mathtext for scientific</span>
<span class="c1"># notation.</span>
<span class="c1">#axes.formatter.useoffset : True # If True, the tick label formatter</span>
<span class="c1"># will default to labeling ticks relative</span>
<span class="c1"># to an offset when the data range is</span>
<span class="c1"># small compared to the minimum absolute</span>
<span class="c1"># value of the data.</span>
<span class="c1">#axes.formatter.offset_threshold : 4 # When useoffset is True, the offset</span>
<span class="c1"># will be used when it can remove</span>
<span class="c1"># at least this number of significant</span>
<span class="c1"># digits from tick labels.</span>
<span class="c1"># axes.spines.left : True # display axis spines</span>
<span class="c1"># axes.spines.bottom : True</span>
<span class="c1"># axes.spines.top : True</span>
<span class="c1"># axes.spines.right : True</span>
<span class="c1">#axes.unicode_minus : True # use unicode for the minus symbol</span>
<span class="c1"># rather than hyphen. See</span>
<span class="c1"># http://en.wikipedia.org/wiki/Plus_and_minus_signs#Character_codes</span>
<span class="c1">#axes.prop_cycle : cycler('color',</span>
<span class="c1"># ['1f77b4', 'ff7f0e', '2ca02c', 'd62728',</span>
<span class="c1"># '9467bd', '8c564b', 'e377c2', '7f7f7f',</span>
<span class="c1"># 'bcbd22', '17becf'])</span>
<span class="c1"># color cycle for plot lines</span>
<span class="c1"># as list of string colorspecs:</span>
<span class="c1"># single letter, long name, or</span>
<span class="c1"># web-style hex</span>
<span class="c1">#axes.autolimit_mode : data # How to scale axes limits to the data.</span>
<span class="c1"># Use "data" to use data limits, plus some margin</span>
<span class="c1"># Use "round_number" move to the nearest "round" number</span>
<span class="c1">#axes.xmargin : .05 # x margin. See `axes.Axes.margins`</span>
<span class="c1">#axes.ymargin : .05 # y margin See `axes.Axes.margins`</span>
<span class="c1">#polaraxes.grid : True # display grid on polar axes</span>
<span class="c1">#axes3d.grid : True # display grid on 3d axes</span>
<span class="c1">### DATES</span>
<span class="c1"># These control the default format strings used in AutoDateFormatter.</span>
<span class="c1"># Any valid format datetime format string can be used (see the python</span>
<span class="c1"># `datetime` for details). For example using '%%x' will use the locale date representation</span>
<span class="c1"># '%%X' will use the locale time representation and '%%c' will use the full locale datetime</span>
<span class="c1"># representation.</span>
<span class="c1"># These values map to the scales:</span>
<span class="c1"># {'year': 365, 'month': 30, 'day': 1, 'hour': 1/24, 'minute': 1 / (24 * 60)}</span>
<span class="c1"># date.autoformatter.year : %Y</span>
<span class="c1"># date.autoformatter.month : %Y-%m</span>
<span class="c1"># date.autoformatter.day : %Y-%m-%d</span>
<span class="c1"># date.autoformatter.hour : %m-%d %H</span>
<span class="c1"># date.autoformatter.minute : %d %H:%M</span>
<span class="c1"># date.autoformatter.second : %H:%M:%S</span>
<span class="c1"># date.autoformatter.microsecond : %M:%S.%f</span>
<span class="c1">### TICKS</span>
<span class="c1"># see http://matplotlib.org/api/axis_api.html#matplotlib.axis.Tick</span>
<span class="c1">#xtick.top : False # draw ticks on the top side</span>
<span class="c1">#xtick.bottom : True # draw ticks on the bottom side</span>
<span class="c1">#xtick.major.size : 3.5 # major tick size in points</span>
<span class="c1">#xtick.minor.size : 2 # minor tick size in points</span>
<span class="c1">#xtick.major.width : 0.8 # major tick width in points</span>
<span class="c1">#xtick.minor.width : 0.6 # minor tick width in points</span>
<span class="c1">#xtick.major.pad : 3.5 # distance to major tick label in points</span>
<span class="c1">#xtick.minor.pad : 3.4 # distance to the minor tick label in points</span>
<span class="c1">#xtick.color : k # color of the tick labels</span>
<span class="c1">#xtick.labelsize : medium # fontsize of the tick labels</span>
<span class="c1">#xtick.direction : out # direction: in, out, or inout</span>
<span class="c1">#xtick.minor.visible : False # visibility of minor ticks on x-axis</span>
<span class="c1">#xtick.major.top : True # draw x axis top major ticks</span>
<span class="c1">#xtick.major.bottom : True # draw x axis bottom major ticks</span>
<span class="c1">#xtick.minor.top : True # draw x axis top minor ticks</span>
<span class="c1">#xtick.minor.bottom : True # draw x axis bottom minor ticks</span>
<span class="c1">#ytick.left : True # draw ticks on the left side</span>
<span class="c1">#ytick.right : False # draw ticks on the right side</span>
<span class="c1">#ytick.major.size : 3.5 # major tick size in points</span>
<span class="c1">#ytick.minor.size : 2 # minor tick size in points</span>
<span class="c1">#ytick.major.width : 0.8 # major tick width in points</span>
<span class="c1">#ytick.minor.width : 0.6 # minor tick width in points</span>
<span class="c1">#ytick.major.pad : 3.5 # distance to major tick label in points</span>
<span class="c1">#ytick.minor.pad : 3.4 # distance to the minor tick label in points</span>
<span class="c1">#ytick.color : k # color of the tick labels</span>
<span class="c1">#ytick.labelsize : medium # fontsize of the tick labels</span>
<span class="c1">#ytick.direction : out # direction: in, out, or inout</span>
<span class="c1">#ytick.minor.visible : False # visibility of minor ticks on y-axis</span>
<span class="c1">#ytick.major.left : True # draw y axis left major ticks</span>
<span class="c1">#ytick.major.right : True # draw y axis right major ticks</span>
<span class="c1">#ytick.minor.left : True # draw y axis left minor ticks</span>
<span class="c1">#ytick.minor.right : True # draw y axis right minor ticks</span>
<span class="c1">### GRIDS</span>
<span class="c1">#grid.color : b0b0b0 # grid color</span>
<span class="c1">#grid.linestyle : - # solid</span>
<span class="c1">#grid.linewidth : 0.8 # in points</span>
<span class="c1">#grid.alpha : 1.0 # transparency, between 0.0 and 1.0</span>
<span class="c1">### Legend</span>
<span class="c1">#legend.loc : best</span>
<span class="c1">#legend.frameon : True # if True, draw the legend on a background patch</span>
<span class="c1">#legend.framealpha : 0.8 # legend patch transparency</span>
<span class="c1">#legend.facecolor : inherit # inherit from axes.facecolor; or color spec</span>
<span class="c1">#legend.edgecolor : 0.8 # background patch boundary color</span>
<span class="c1">#legend.fancybox : True # if True, use a rounded box for the</span>
<span class="c1"># legend background, else a rectangle</span>
<span class="c1">#legend.shadow : False # if True, give background a shadow effect</span>
<span class="c1">#legend.numpoints : 1 # the number of marker points in the legend line</span>
<span class="c1">#legend.scatterpoints : 1 # number of scatter points</span>
<span class="c1">#legend.markerscale : 1.0 # the relative size of legend markers vs. original</span>
<span class="c1">#legend.fontsize : medium</span>
<span class="c1"># Dimensions as fraction of fontsize:</span>
<span class="c1">#legend.borderpad : 0.4 # border whitespace</span>
<span class="c1">#legend.labelspacing : 0.5 # the vertical space between the legend entries</span>
<span class="c1">#legend.handlelength : 2.0 # the length of the legend lines</span>
<span class="c1">#legend.handleheight : 0.7 # the height of the legend handle</span>
<span class="c1">#legend.handletextpad : 0.8 # the space between the legend line and legend text</span>
<span class="c1">#legend.borderaxespad : 0.5 # the border between the axes and legend edge</span>
<span class="c1">#legend.columnspacing : 2.0 # column separation</span>
<span class="c1">### FIGURE</span>
<span class="c1"># See http://matplotlib.org/api/figure_api.html#matplotlib.figure.Figure</span>
<span class="c1">#figure.titlesize : large # size of the figure title (Figure.suptitle())</span>
<span class="c1">#figure.titleweight : normal # weight of the figure title</span>
<span class="c1">#figure.figsize : 6.4, 4.8 # figure size in inches</span>
<span class="c1">#figure.dpi : 100 # figure dots per inch</span>
<span class="c1">#figure.facecolor : white # figure facecolor; 0.75 is scalar gray</span>
<span class="c1">#figure.edgecolor : white # figure edgecolor</span>
<span class="c1">#figure.autolayout : False # When True, automatically adjust subplot</span>
<span class="c1"># parameters to make the plot fit the figure</span>
<span class="c1">#figure.max_open_warning : 20 # The maximum number of figures to open through</span>
<span class="c1"># the pyplot interface before emitting a warning.</span>
<span class="c1"># If less than one this feature is disabled.</span>
<span class="c1"># The figure subplot parameters. All dimensions are a fraction of the</span>
<span class="c1">#figure.subplot.left : 0.125 # the left side of the subplots of the figure</span>
<span class="c1">#figure.subplot.right : 0.9 # the right side of the subplots of the figure</span>
<span class="c1">#figure.subplot.bottom : 0.11 # the bottom of the subplots of the figure</span>
<span class="c1">#figure.subplot.top : 0.88 # the top of the subplots of the figure</span>
<span class="c1">#figure.subplot.wspace : 0.2 # the amount of width reserved for blank space between subplots,</span>
<span class="c1"># expressed as a fraction of the average axis width</span>
<span class="c1">#figure.subplot.hspace : 0.2 # the amount of height reserved for white space between subplots,</span>
<span class="c1"># expressed as a fraction of the average axis height</span>
<span class="c1">### IMAGES</span>
<span class="c1">#image.aspect : equal # equal | auto | a number</span>
<span class="c1">#image.interpolation : nearest # see help(imshow) for options</span>
<span class="c1">#image.cmap : viridis # A colormap name, gray etc...</span>
<span class="c1">#image.lut : 256 # the size of the colormap lookup table</span>
<span class="c1">#image.origin : upper # lower | upper</span>
<span class="c1">#image.resample : True</span>
<span class="c1">#image.composite_image : True # When True, all the images on a set of axes are</span>
<span class="c1"># combined into a single composite image before</span>
<span class="c1"># saving a figure as a vector graphics file,</span>
<span class="c1"># such as a PDF.</span>
<span class="c1">### CONTOUR PLOTS</span>
<span class="c1">#contour.negative_linestyle : dashed # dashed | solid</span>
<span class="c1">#contour.corner_mask : True # True | False | legacy</span>
<span class="c1">### ERRORBAR PLOTS</span>
<span class="c1">#errorbar.capsize : 0 # length of end cap on error bars in pixels</span>
<span class="c1">### HISTOGRAM PLOTS</span>
<span class="c1">#hist.bins : 10 # The default number of histogram bins.</span>
<span class="c1"># If Numpy 1.11 or later is</span>
<span class="c1"># installed, may also be `auto`</span>
<span class="c1">### SCATTER PLOTS</span>
<span class="c1">#scatter.marker : o # The default marker type for scatter plots.</span>
<span class="c1">### Agg rendering</span>
<span class="c1">### Warning: experimental, 2008/10/10</span>
<span class="c1">#agg.path.chunksize : 0 # 0 to disable; values in the range</span>
<span class="c1"># 10000 to 100000 can improve speed slightly</span>
<span class="c1"># and prevent an Agg rendering failure</span>
<span class="c1"># when plotting very large data sets,</span>
<span class="c1"># especially if they are very gappy.</span>
<span class="c1"># It may cause minor artifacts, though.</span>
<span class="c1"># A value of 20000 is probably a good</span>
<span class="c1"># starting point.</span>
<span class="c1">### SAVING FIGURES</span>
<span class="c1">#path.simplify : True # When True, simplify paths by removing "invisible"</span>
<span class="c1"># points to reduce file size and increase rendering</span>
<span class="c1"># speed</span>
<span class="c1">#path.simplify_threshold : 0.1 # The threshold of similarity below which</span>
<span class="c1"># vertices will be removed in the simplification</span>
<span class="c1"># process</span>
<span class="c1">#path.snap : True # When True, rectilinear axis-aligned paths will be snapped to</span>
<span class="c1"># the nearest pixel when certain criteria are met. When False,</span>
<span class="c1"># paths will never be snapped.</span>
<span class="c1">#path.sketch : None # May be none, or a 3-tuple of the form (scale, length,</span>
<span class="c1"># randomness).</span>
<span class="c1"># *scale* is the amplitude of the wiggle</span>
<span class="c1"># perpendicular to the line (in pixels). *length*</span>
<span class="c1"># is the length of the wiggle along the line (in</span>
<span class="c1"># pixels). *randomness* is the factor by which</span>
<span class="c1"># the length is randomly scaled.</span>
<span class="c1"># the default savefig params can be different from the display params</span>
<span class="c1"># e.g., you may want a higher resolution, or to make the figure</span>
<span class="c1"># background white</span>
<span class="c1">#savefig.dpi : figure # figure dots per inch or 'figure'</span>
<span class="c1">#savefig.facecolor : white # figure facecolor when saving</span>
<span class="c1">#savefig.edgecolor : white # figure edgecolor when saving</span>
<span class="c1">#savefig.format : png # png, ps, pdf, svg</span>
<span class="c1">#savefig.bbox : standard # 'tight' or 'standard'.</span>
<span class="c1"># 'tight' is incompatible with pipe-based animation</span>
<span class="c1"># backends but will workd with temporary file based ones:</span>
<span class="c1"># e.g. setting animation.writer to ffmpeg will not work,</span>
<span class="c1"># use ffmpeg_file instead</span>
<span class="c1">#savefig.pad_inches : 0.1 # Padding to be used when bbox is set to 'tight'</span>
<span class="c1">#savefig.jpeg_quality: 95 # when a jpeg is saved, the default quality parameter.</span>
<span class="c1">#savefig.directory : ~ # default directory in savefig dialog box,</span>
<span class="c1"># leave empty to always use current working directory</span>
<span class="c1">#savefig.transparent : False # setting that controls whether figures are saved with a</span>
<span class="c1"># transparent background by default</span>
<span class="c1"># tk backend params</span>
<span class="c1">#tk.window_focus : False # Maintain shell focus for TkAgg</span>
<span class="c1"># ps backend params</span>
<span class="c1">#ps.papersize : letter # auto, letter, legal, ledger, A0-A10, B0-B10</span>
<span class="c1">#ps.useafm : False # use of afm fonts, results in small files</span>
<span class="c1">#ps.usedistiller : False # can be: None, ghostscript or xpdf</span>
<span class="c1"># Experimental: may produce smaller files.</span>
<span class="c1"># xpdf intended for production of publication quality files,</span>
<span class="c1"># but requires ghostscript, xpdf and ps2eps</span>
<span class="c1">#ps.distiller.res : 6000 # dpi</span>
<span class="c1">#ps.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType)</span>
<span class="c1"># pdf backend params</span>
<span class="c1">#pdf.compression : 6 # integer from 0 to 9</span>
<span class="c1"># 0 disables compression (good for debugging)</span>
<span class="c1">#pdf.fonttype : 3 # Output Type 3 (Type3) or Type 42 (TrueType)</span>
<span class="c1"># svg backend params</span>
<span class="c1">#svg.image_inline : True # write raster image data directly into the svg file</span>
<span class="c1">#svg.fonttype : 'path' # How to handle SVG fonts:</span>
<span class="c1"># 'none': Assume fonts are installed on the machine where the SVG will be viewed.</span>
<span class="c1"># 'path': Embed characters as paths -- supported by most SVG renderers</span>
<span class="c1"># 'svgfont': Embed characters as SVG fonts -- supported only by Chrome,</span>
<span class="c1"># Opera and Safari</span>
<span class="c1">#svg.hashsalt : None # if not None, use this string as hash salt</span>
<span class="c1"># instead of uuid4</span>
<span class="c1"># docstring params</span>
<span class="c1">#docstring.hardcopy = False # set this when you want to generate hardcopy docstring</span>
<span class="c1"># Set the verbose flags. This controls how much information</span>
<span class="c1"># matplotlib gives you at runtime and where it goes. The verbosity</span>
<span class="c1"># levels are: silent, helpful, debug, debug-annoying. Any level is</span>
<span class="c1"># inclusive of all the levels below it. If your setting is "debug",</span>
<span class="c1"># you'll get all the debug and helpful messages. When submitting</span>
<span class="c1"># problems to the mailing-list, please set verbose to "helpful" or "debug"</span>
<span class="c1"># and paste the output into your report.</span>
<span class="c1">#</span>
<span class="c1"># The "fileo" gives the destination for any calls to verbose.report.</span>
<span class="c1"># These objects can a filename, or a filehandle like sys.stdout.</span>
<span class="c1">#</span>
<span class="c1"># You can override the rc default verbosity from the command line by</span>
<span class="c1"># giving the flags --verbose-LEVEL where LEVEL is one of the legal</span>
<span class="c1"># levels, e.g., --verbose-helpful.</span>
<span class="c1">#</span>
<span class="c1"># You can access the verbose instance in your code</span>
<span class="c1"># from matplotlib import verbose.</span>
<span class="c1">#verbose.level : silent # one of silent, helpful, debug, debug-annoying</span>
<span class="c1">#verbose.fileo : sys.stdout # a log filename, sys.stdout or sys.stderr</span>
<span class="c1"># Event keys to interact with figures/plots via keyboard.</span>
<span class="c1"># Customize these settings according to your needs.</span>
<span class="c1"># Leave the field(s) empty if you don't need a key-map. (i.e., fullscreen : '')</span>
<span class="c1">#keymap.fullscreen : f, ctrl+f # toggling</span>
<span class="c1">#keymap.home : h, r, home # home or reset mnemonic</span>
<span class="c1">#keymap.back : left, c, backspace # forward / backward keys to enable</span>
<span class="c1">#keymap.forward : right, v # left handed quick navigation</span>
<span class="c1">#keymap.pan : p # pan mnemonic</span>
<span class="c1">#keymap.zoom : o # zoom mnemonic</span>
<span class="c1">#keymap.save : s # saving current figure</span>
<span class="c1">#keymap.quit : ctrl+w, cmd+w # close the current figure</span>
<span class="c1">#keymap.grid : g # switching on/off a grid in current axes</span>
<span class="c1">#keymap.yscale : l # toggle scaling of y-axes ('log'/'linear')</span>
<span class="c1">#keymap.xscale : L, k # toggle scaling of x-axes ('log'/'linear')</span>
<span class="c1">#keymap.all_axes : a # enable all axes</span>
<span class="c1"># Control location of examples data files</span>
<span class="c1">#examples.directory : '' # directory to look in for custom installation</span>
<span class="c1">###ANIMATION settings</span>
<span class="c1">#animation.html : 'none' # How to display the animation as HTML in</span>
<span class="c1"># the IPython notebook. 'html5' uses</span>
<span class="c1"># HTML5 video tag.</span>
<span class="c1">#animation.writer : ffmpeg # MovieWriter 'backend' to use</span>
<span class="c1">#animation.codec : h264 # Codec to use for writing movie</span>
<span class="c1">#animation.bitrate: -1 # Controls size/quality tradeoff for movie.</span>
<span class="c1"># -1 implies let utility auto-determine</span>
<span class="c1">#animation.frame_format: 'png' # Controls frame format used by temp files</span>
<span class="c1">#animation.ffmpeg_path: 'ffmpeg' # Path to ffmpeg binary. Without full path</span>
<span class="c1"># $PATH is searched</span>
<span class="c1">#animation.ffmpeg_args: '' # Additional arguments to pass to ffmpeg</span>
<span class="c1">#animation.avconv_path: 'avconv' # Path to avconv binary. Without full path</span>
<span class="c1"># $PATH is searched</span>
<span class="c1">#animation.avconv_args: '' # Additional arguments to pass to avconv</span>
<span class="c1">#animation.mencoder_path: 'mencoder'</span>
<span class="c1"># Path to mencoder binary. Without full path</span>
<span class="c1"># $PATH is searched</span>
<span class="c1">#animation.mencoder_args: '' # Additional arguments to pass to mencoder</span>
<span class="c1">#animation.convert_path: 'convert' # Path to ImageMagick's convert binary.</span>
<span class="c1"># On Windows use the full path since convert</span>
<span class="c1"># is also the name of a system tool.</span>
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