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<li><a class="reference internal" href="#">Artist tutorial</a><ul>
<li><a class="reference internal" href="#customizing-your-objects">Customizing your objects</a></li>
<li><a class="reference internal" href="#object-containers">Object containers</a></li>
<li><a class="reference internal" href="#figure-container">Figure container</a></li>
<li><a class="reference internal" href="#axes-container">Axes container</a></li>
<li><a class="reference internal" href="#axis-containers">Axis containers</a></li>
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  <div class="section" id="artist-tutorial">
<span id="id1"></span><h1>Artist tutorial<a class="headerlink" href="#artist-tutorial" title="Permalink to this headline">¶</a></h1>
<p>There are three layers to the matplotlib API.  The
<code class="xref py py-class docutils literal"><span class="pre">matplotlib.backend_bases.FigureCanvas</span></code> is the area onto which
the figure is drawn, the <code class="xref py py-class docutils literal"><span class="pre">matplotlib.backend_bases.Renderer</span></code> is
the object which knows how to draw on the
<code class="xref py py-class docutils literal"><span class="pre">FigureCanvas</span></code>, and the
<a class="reference internal" href="../api/artist_api.html#matplotlib.artist.Artist" title="matplotlib.artist.Artist"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.artist.Artist</span></code></a> is the object that knows how to use
a renderer to paint onto the canvas.  The
<code class="xref py py-class docutils literal"><span class="pre">FigureCanvas</span></code> and
<code class="xref py py-class docutils literal"><span class="pre">Renderer</span></code> handle all the details of
talking to user interface toolkits like <a class="reference external" href="http://www.wxpython.org">wxPython</a> or drawing languages like PostScript®, and
the <code class="docutils literal"><span class="pre">Artist</span></code> handles all the high level constructs like representing
and laying out the figure, text, and lines.  The typical user will
spend 95% of his time working with the <code class="docutils literal"><span class="pre">Artists</span></code>.</p>
<p>There are two types of <code class="docutils literal"><span class="pre">Artists</span></code>: primitives and containers.  The primitives
represent the standard graphical objects we want to paint onto our canvas:
<a class="reference internal" href="../api/lines_api.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-class docutils literal"><span class="pre">Line2D</span></code></a>, <a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal"><span class="pre">Rectangle</span></code></a>,
<a class="reference internal" href="../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-class docutils literal"><span class="pre">Text</span></code></a>, <a class="reference internal" href="../api/image_api.html#matplotlib.image.AxesImage" title="matplotlib.image.AxesImage"><code class="xref py py-class docutils literal"><span class="pre">AxesImage</span></code></a>, etc., and
the containers are places to put them (<a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-class docutils literal"><span class="pre">Axis</span></code></a>,
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> and <a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal"><span class="pre">Figure</span></code></a>).  The
standard use is to create a <a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal"><span class="pre">Figure</span></code></a> instance, use
the <code class="docutils literal"><span class="pre">Figure</span></code> to create one or more <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> or
<code class="xref py py-class docutils literal"><span class="pre">Subplot</span></code> instances, and use the <code class="docutils literal"><span class="pre">Axes</span></code> instance
helper methods to create the primitives.  In the example below, we create a
<code class="docutils literal"><span class="pre">Figure</span></code> instance using <a class="reference internal" href="../api/pyplot_api.html#matplotlib.pyplot.figure" title="matplotlib.pyplot.figure"><code class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.figure()</span></code></a>, which is a
convenience method for instantiating <code class="docutils literal"><span class="pre">Figure</span></code> instances and connecting them
with your user interface or drawing toolkit <code class="docutils literal"><span class="pre">FigureCanvas</span></code>.  As we will
discuss below, this is not necessary &#8211; you can work directly with PostScript,
PDF Gtk+, or wxPython <code class="docutils literal"><span class="pre">FigureCanvas</span></code> instances, instantiate your <code class="docutils literal"><span class="pre">Figures</span></code>
directly and connect them yourselves &#8211; but since we are focusing here on the
<code class="docutils literal"><span class="pre">Artist</span></code> API we&#8217;ll let <a class="reference internal" href="../api/pyplot_api.html#module-matplotlib.pyplot" title="matplotlib.pyplot"><code class="xref py py-mod docutils literal"><span class="pre">pyplot</span></code></a> handle some of those details
for us:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> <span class="c1"># two rows, one column, first plot</span>
</pre></div>
<p>The <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> is probably the most important
class in the matplotlib API, and the one you will be working with most
of the time.  This is because the <code class="docutils literal"><span class="pre">Axes</span></code> is the plotting area into
which most of the objects go, and the <code class="docutils literal"><span class="pre">Axes</span></code> has many special helper
methods (<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.plot" title="matplotlib.axes.Axes.plot"><code class="xref py py-meth docutils literal"><span class="pre">plot()</span></code></a>,
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.text" title="matplotlib.axes.Axes.text"><code class="xref py py-meth docutils literal"><span class="pre">text()</span></code></a>,
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.hist" title="matplotlib.axes.Axes.hist"><code class="xref py py-meth docutils literal"><span class="pre">hist()</span></code></a>,
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.imshow" title="matplotlib.axes.Axes.imshow"><code class="xref py py-meth docutils literal"><span class="pre">imshow()</span></code></a>) to create the most common
graphics primitives (<a class="reference internal" href="../api/lines_api.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-class docutils literal"><span class="pre">Line2D</span></code></a>,
<a class="reference internal" href="../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-class docutils literal"><span class="pre">Text</span></code></a>,
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal"><span class="pre">Rectangle</span></code></a>,
<code class="xref py py-class docutils literal"><span class="pre">Image</span></code>, respectively).  These helper methods
will take your data (e.g., <code class="docutils literal"><span class="pre">numpy</span></code> arrays and strings) and create
primitive <code class="docutils literal"><span class="pre">Artist</span></code> instances as needed (e.g., <code class="docutils literal"><span class="pre">Line2D</span></code>), add them to
the relevant containers, and draw them when requested.  Most of you
are probably familiar with the <code class="xref py py-class docutils literal"><span class="pre">Subplot</span></code>,
which is just a special case of an <code class="docutils literal"><span class="pre">Axes</span></code> that lives on a regular
rows by columns grid of <code class="docutils literal"><span class="pre">Subplot</span></code> instances.  If you want to create
an <code class="docutils literal"><span class="pre">Axes</span></code> at an arbitrary location, simply use the
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.add_axes" title="matplotlib.figure.Figure.add_axes"><code class="xref py py-meth docutils literal"><span class="pre">add_axes()</span></code></a> method which takes a list
of <code class="docutils literal"><span class="pre">[left,</span> <span class="pre">bottom,</span> <span class="pre">width,</span> <span class="pre">height]</span></code> values in 0-1 relative figure
coordinates:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">fig2</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">ax2</span> <span class="o">=</span> <span class="n">fig2</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.15</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.7</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">])</span>
</pre></div>
<p>Continuing with our example:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">,</span> <span class="mf">0.01</span><span class="p">)</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</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="o">*</span><span class="n">t</span><span class="p">)</span>
<span class="n">line</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">s</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span> <span class="n">lw</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<p>In this example, <code class="docutils literal"><span class="pre">ax</span></code> is the <code class="docutils literal"><span class="pre">Axes</span></code> instance created by the
<code class="docutils literal"><span class="pre">fig.add_subplot</span></code> call above (remember <code class="docutils literal"><span class="pre">Subplot</span></code> is just a
subclass of <code class="docutils literal"><span class="pre">Axes</span></code>) and when you call <code class="docutils literal"><span class="pre">ax.plot</span></code>, it creates a
<code class="docutils literal"><span class="pre">Line2D</span></code> instance and adds it to the <code class="xref py py-attr docutils literal"><span class="pre">Axes.lines</span></code> list.  In the interactive <a class="reference external" href="http://ipython.org/">ipython</a> session below, you can see that the
<code class="docutils literal"><span class="pre">Axes.lines</span></code> list is length one and contains the same line that was
returned by the <code class="docutils literal"><span class="pre">line,</span> <span class="pre">=</span> <span class="pre">ax.plot...</span></code> call:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [101]: </span><span class="n">ax</span><span class="o">.</span><span class="n">lines</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="gh">Out[101]: </span><span class="go">&lt;matplotlib.lines.Line2D instance at 0x19a95710&gt;</span>
<span class="gp">In [102]: </span><span class="n">line</span>
<span class="gh">Out[102]: </span><span class="go">&lt;matplotlib.lines.Line2D instance at 0x19a95710&gt;</span>
</pre></div>
<p>If you make subsequent calls to <code class="docutils literal"><span class="pre">ax.plot</span></code> (and the hold state is &#8220;on&#8221;
which is the default) then additional lines will be added to the list.
You can remove lines later simply by calling the list methods; either
of these will work:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">del</span> <span class="n">ax</span><span class="o">.</span><span class="n">lines</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="n">ax</span><span class="o">.</span><span class="n">lines</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="n">line</span><span class="p">)</span>  <span class="c1"># one or the other, not both!</span>
</pre></div>
<p>The Axes also has helper methods to configure and decorate the x-axis
and y-axis tick, tick labels and axis labels:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">xtext</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;my xdata&#39;</span><span class="p">)</span> <span class="c1"># returns a Text instance</span>
<span class="n">ytext</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;my ydata&#39;</span><span class="p">)</span>
</pre></div>
<p>When you call <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.set_xlabel" title="matplotlib.axes.Axes.set_xlabel"><code class="xref py py-meth docutils literal"><span class="pre">ax.set_xlabel</span></code></a>,
it passes the information on the <a class="reference internal" href="../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-class docutils literal"><span class="pre">Text</span></code></a>
instance of the <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.XAxis" title="matplotlib.axis.XAxis"><code class="xref py py-class docutils literal"><span class="pre">XAxis</span></code></a>.  Each <code class="docutils literal"><span class="pre">Axes</span></code>
instance contains an <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.XAxis" title="matplotlib.axis.XAxis"><code class="xref py py-class docutils literal"><span class="pre">XAxis</span></code></a> and a
<a class="reference internal" href="../api/axis_api.html#matplotlib.axis.YAxis" title="matplotlib.axis.YAxis"><code class="xref py py-class docutils literal"><span class="pre">YAxis</span></code></a> instance, which handle the layout and
drawing of the ticks, tick labels and axis labels.</p>
<p>Try creating the figure below.</p>
<p>(<a class="reference external" href="../pyplots/fig_axes_labels_simple.py">Source code</a>, <a class="reference external" href="../pyplots/fig_axes_labels_simple.png">png</a>, <a class="reference external" href="../pyplots/fig_axes_labels_simple.hires.png">hires.png</a>, <a class="reference external" href="../pyplots/fig_axes_labels_simple.pdf">pdf</a>)</p>
<div class="figure">
<img alt="../_images/fig_axes_labels_simple.png" src="../_images/fig_axes_labels_simple.png" />
<div class="section" id="customizing-your-objects">
<span id="customizing-artists"></span><h2>Customizing your objects<a class="headerlink" href="#customizing-your-objects" title="Permalink to this headline">¶</a></h2>
<p>Every element in the figure is represented by a matplotlib
<a class="reference internal" href="../api/artist_api.html#matplotlib.artist.Artist" title="matplotlib.artist.Artist"><code class="xref py py-class docutils literal"><span class="pre">Artist</span></code></a>, and each has an extensive list of
properties to configure its appearance.  The figure itself contains a
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal"><span class="pre">Rectangle</span></code></a> exactly the size of the figure,
which you can use to set the background color and transparency of the
figures.  Likewise, each <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> bounding box
(the standard white box with black edges in the typical matplotlib
plot, has a <code class="docutils literal"><span class="pre">Rectangle</span></code> instance that determines the color,
transparency, and other properties of the Axes.  These instances are
stored as member variables <code class="xref py py-attr docutils literal"><span class="pre">Figure.patch</span></code> and <code class="xref py py-attr docutils literal"><span class="pre">Axes.patch</span></code> (&#8220;Patch&#8221; is a name inherited from
MATLAB, and is a 2D &#8220;patch&#8221; of color on the figure, e.g., rectangles,
circles and polygons).  Every matplotlib <code class="docutils literal"><span class="pre">Artist</span></code> has the following
properties</p>
<table border="1" class="docutils">
<col width="11%" />
<col width="89%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Property</th>
<th class="head">Description</th>
<tbody valign="top">
<tr class="row-even"><td>alpha</td>
<td>The transparency - a scalar from 0-1</td>
<tr class="row-odd"><td>animated</td>
<td>A boolean that is used to facilitate animated drawing</td>
<tr class="row-even"><td>axes</td>
<td>The axes that the Artist lives in, possibly None</td>
<tr class="row-odd"><td>clip_box</td>
<td>The bounding box that clips the Artist</td>
<tr class="row-even"><td>clip_on</td>
<td>Whether clipping is enabled</td>
<tr class="row-odd"><td>clip_path</td>
<td>The path the artist is clipped to</td>
<tr class="row-even"><td>contains</td>
<td>A picking function to test whether the artist contains the pick point</td>
<tr class="row-odd"><td>figure</td>
<td>The figure instance the artist lives in, possibly None</td>
<tr class="row-even"><td>label</td>
<td>A text label (e.g., for auto-labeling)</td>
<tr class="row-odd"><td>picker</td>
<td>A python object that controls object picking</td>
<tr class="row-even"><td>transform</td>
<td>The transformation</td>
<tr class="row-odd"><td>visible</td>
<td>A boolean whether the artist should be drawn</td>
<tr class="row-even"><td>zorder</td>
<td>A number which determines the drawing order</td>
<tr class="row-odd"><td>rasterized</td>
<td>Boolean; Turns vectors into rastergraphics: (for compression &amp; eps transparency)</td>
<p>Each of the properties is accessed with an old-fashioned setter or
getter (yes we know this irritates Pythonistas and we plan to support
direct access via properties or traits but it hasn&#8217;t been done yet).
For example, to multiply the current alpha by a half:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">a</span> <span class="o">=</span> <span class="n">o</span><span class="o">.</span><span class="n">get_alpha</span><span class="p">()</span>
<span class="n">o</span><span class="o">.</span><span class="n">set_alpha</span><span class="p">(</span><span class="mf">0.5</span><span class="o">*</span><span class="n">a</span><span class="p">)</span>
</pre></div>
<p>If you want to set a number of properties at once, you can also use
the <code class="docutils literal"><span class="pre">set</span></code> method with keyword arguments.  For example:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">o</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">,</span> <span class="n">zorder</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<p>If you are working interactively at the python shell, a handy way to
inspect the <code class="docutils literal"><span class="pre">Artist</span></code> properties is to use the
<a class="reference internal" href="../api/artist_api.html#matplotlib.artist.getp" title="matplotlib.artist.getp"><code class="xref py py-func docutils literal"><span class="pre">matplotlib.artist.getp()</span></code></a> function (simply
<code class="xref py py-func docutils literal"><span class="pre">getp()</span></code> in pylab), which lists the properties
and their values.  This works for classes derived from <code class="docutils literal"><span class="pre">Artist</span></code> as
well, e.g., <code class="docutils literal"><span class="pre">Figure</span></code> and <code class="docutils literal"><span class="pre">Rectangle</span></code>.  Here are the <code class="docutils literal"><span class="pre">Figure</span></code> rectangle
properties mentioned above:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [149]: </span><span class="n">matplotlib</span><span class="o">.</span><span class="n">artist</span><span class="o">.</span><span class="n">getp</span><span class="p">(</span><span class="n">fig</span><span class="o">.</span><span class="n">patch</span><span class="p">)</span>
<span class="go">    alpha = 1.0</span>
<span class="go">    animated = False</span>
<span class="go">    antialiased or aa = True</span>
<span class="go">    axes = None</span>
<span class="go">    clip_box = None</span>
<span class="go">    clip_on = False</span>
<span class="go">    clip_path = None</span>
<span class="go">    contains = None</span>
<span class="go">    edgecolor or ec = w</span>
<span class="go">    facecolor or fc = 0.75</span>
<span class="go">    figure = Figure(8.125x6.125)</span>
<span class="go">    fill = 1</span>
<span class="go">    hatch = None</span>
<span class="go">    height = 1</span>
<span class="go">    label =</span>
<span class="go">    linewidth or lw = 1.0</span>
<span class="go">    picker = None</span>
<span class="go">    transform = &lt;Affine object at 0x134cca84&gt;</span>
<span class="go">    verts = ((0, 0), (0, 1), (1, 1), (1, 0))</span>
<span class="go">    visible = True</span>
<span class="go">    width = 1</span>
<span class="go">    window_extent = &lt;Bbox object at 0x134acbcc&gt;</span>
<span class="go">    x = 0</span>
<span class="go">    y = 0</span>
<span class="go">    zorder = 1</span>
</pre></div>
<p>The docstrings for all of the classes also contain the <code class="docutils literal"><span class="pre">Artist</span></code>
properties, so you can consult the interactive &#8220;help&#8221; or the
<a class="reference internal" href="../api/artist_api.html#artist-api"><span>artists</span></a> for a listing of properties for a given object.</p>
<div class="section" id="object-containers">
<span id="id2"></span><h2>Object containers<a class="headerlink" href="#object-containers" title="Permalink to this headline">¶</a></h2>
<p>Now that we know how to inspect and set the properties of a given
object we want to configure, we need to now how to get at that object.
As mentioned in the introduction, there are two kinds of objects:
primitives and containers.  The primitives are usually the things you
want to configure (the font of a <a class="reference internal" href="../api/text_api.html#matplotlib.text.Text" title="matplotlib.text.Text"><code class="xref py py-class docutils literal"><span class="pre">Text</span></code></a>
instance, the width of a <a class="reference internal" href="../api/lines_api.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-class docutils literal"><span class="pre">Line2D</span></code></a>) although
the containers also have some properties as well &#8211; for example the
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> <a class="reference internal" href="../api/artist_api.html#matplotlib.artist.Artist" title="matplotlib.artist.Artist"><code class="xref py py-class docutils literal"><span class="pre">Artist</span></code></a> is a
container that contains many of the primitives in your plot, but it
also has properties like the <code class="docutils literal"><span class="pre">xscale</span></code> to control whether the xaxis
is &#8216;linear&#8217; or &#8216;log&#8217;.  In this section we&#8217;ll review where the various
container objects store the <code class="docutils literal"><span class="pre">Artists</span></code> that you want to get at.</p>
<div class="section" id="figure-container">
<span id="id3"></span><h2>Figure container<a class="headerlink" href="#figure-container" title="Permalink to this headline">¶</a></h2>
<p>The top level container <code class="docutils literal"><span class="pre">Artist</span></code> is the
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.figure.Figure</span></code></a>, and it contains everything in the
figure.  The background of the figure is a
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal"><span class="pre">Rectangle</span></code></a> which is stored in
<code class="xref py py-attr docutils literal"><span class="pre">Figure.patch</span></code>.  As
you add subplots (<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.add_subplot" title="matplotlib.figure.Figure.add_subplot"><code class="xref py py-meth docutils literal"><span class="pre">add_subplot()</span></code></a>) and
axes (<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.add_axes" title="matplotlib.figure.Figure.add_axes"><code class="xref py py-meth docutils literal"><span class="pre">add_axes()</span></code></a>) to the figure
these will be appended to the <a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.axes" title="matplotlib.figure.Figure.axes"><code class="xref py py-attr docutils literal"><span class="pre">Figure.axes</span></code></a>.  These are also returned by the
methods that create them:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [156]: </span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="gp">In [157]: </span><span class="n">ax1</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">211</span><span class="p">)</span>
<span class="gp">In [158]: </span><span class="n">ax2</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.7</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">])</span>
<span class="gp">In [159]: </span><span class="n">ax1</span>
<span class="gh">Out[159]: </span><span class="go">&lt;matplotlib.axes.Subplot instance at 0xd54b26c&gt;</span>
<span class="gp">In [160]: </span><span class="k">print</span> <span class="n">fig</span><span class="o">.</span><span class="n">axes</span>
<span class="go">[&lt;matplotlib.axes.Subplot instance at 0xd54b26c&gt;, &lt;matplotlib.axes.Axes instance at 0xd3f0b2c&gt;]</span>
</pre></div>
<p>Because the figure maintains the concept of the &#8220;current axes&#8221; (see
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.gca" title="matplotlib.figure.Figure.gca"><code class="xref py py-meth docutils literal"><span class="pre">Figure.gca</span></code></a> and
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.sca" title="matplotlib.figure.Figure.sca"><code class="xref py py-meth docutils literal"><span class="pre">Figure.sca</span></code></a>) to support the
pylab/pyplot state machine, you should not insert or remove axes
directly from the axes list, but rather use the
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.add_subplot" title="matplotlib.figure.Figure.add_subplot"><code class="xref py py-meth docutils literal"><span class="pre">add_subplot()</span></code></a> and
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.add_axes" title="matplotlib.figure.Figure.add_axes"><code class="xref py py-meth docutils literal"><span class="pre">add_axes()</span></code></a> methods to insert, and the
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure.delaxes" title="matplotlib.figure.Figure.delaxes"><code class="xref py py-meth docutils literal"><span class="pre">delaxes()</span></code></a> method to delete.  You are
free however, to iterate over the list of axes or index into it to get
access to <code class="docutils literal"><span class="pre">Axes</span></code> instances you want to customize.  Here is an
example which turns all the axes grids on:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">for</span> <span class="n">ax</span> <span class="ow">in</span> <span class="n">fig</span><span class="o">.</span><span class="n">axes</span><span class="p">:</span>
    <span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="bp">True</span><span class="p">)</span>
</pre></div>
<p>The figure also has its own text, lines, patches and images, which you
can use to add primitives directly.  The default coordinate system for
the <code class="docutils literal"><span class="pre">Figure</span></code> will simply be in pixels (which is not usually what you
want) but you can control this by setting the transform property of
the <code class="docutils literal"><span class="pre">Artist</span></code> you are adding to the figure.</p>
<p>More useful is &#8220;figure coordinates&#8221; where (0, 0) is the bottom-left of
the figure and (1, 1) is the top-right of the figure which you can
obtain by setting the <code class="docutils literal"><span class="pre">Artist</span></code> transform to <code class="xref py py-attr docutils literal"><span class="pre">fig.transFigure</span></code>:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [191]: </span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="gp">In [192]: </span><span class="n">l1</span> <span class="o">=</span> <span class="n">matplotlib</span><span class="o">.</span><span class="n">lines</span><span class="o">.</span><span class="n">Line2D</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span>
<span class="go">           transform=fig.transFigure, figure=fig)</span>
<span class="gp">In [193]: </span><span class="n">l2</span> <span class="o">=</span> <span class="n">matplotlib</span><span class="o">.</span><span class="n">lines</span><span class="o">.</span><span class="n">Line2D</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
<span class="go">           transform=fig.transFigure, figure=fig)</span>
<span class="gp">In [194]: </span><span class="n">fig</span><span class="o">.</span><span class="n">lines</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">l1</span><span class="p">,</span> <span class="n">l2</span><span class="p">])</span>
<span class="gp">In [195]: </span><span class="n">fig</span><span class="o">.</span><span class="n">canvas</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
</pre></div>
<p>(<a class="reference external" href="../pyplots/fig_x.py">Source code</a>, <a class="reference external" href="../pyplots/fig_x.png">png</a>, <a class="reference external" href="../pyplots/fig_x.hires.png">hires.png</a>, <a class="reference external" href="../pyplots/fig_x.pdf">pdf</a>)</p>
<div class="figure">
<img alt="../_images/fig_x.png" src="../_images/fig_x.png" />
<p>Here is a summary of the Artists the figure contains</p>
<table border="1" class="docutils">
<col width="20%" />
<col width="80%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Figure attribute</th>
<th class="head">Description</th>
<tbody valign="top">
<tr class="row-even"><td>axes</td>
<td>A list of Axes instances (includes Subplot)</td>
<tr class="row-odd"><td>patch</td>
<td>The Rectangle background</td>
<tr class="row-even"><td>images</td>
<td>A list of FigureImages patches - useful for raw pixel display</td>
<tr class="row-odd"><td>legends</td>
<td>A list of Figure Legend instances (different from Axes.legends)</td>
<tr class="row-even"><td>lines</td>
<td>A list of Figure Line2D instances (rarely used, see Axes.lines)</td>
<tr class="row-odd"><td>patches</td>
<td>A list of Figure patches (rarely used, see Axes.patches)</td>
<tr class="row-even"><td>texts</td>
<td>A list Figure Text instances</td>
<div class="section" id="axes-container">
<span id="id4"></span><h2>Axes container<a class="headerlink" href="#axes-container" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.axes.Axes</span></code></a> is the center of the matplotlib
universe &#8211; it contains the vast majority of all the <code class="docutils literal"><span class="pre">Artists</span></code> used
in a figure with many helper methods to create and add these
<code class="docutils literal"><span class="pre">Artists</span></code> to itself, as well as helper methods to access and
customize the <code class="docutils literal"><span class="pre">Artists</span></code> it contains.  Like the
<a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal"><span class="pre">Figure</span></code></a>, it contains a
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Patch" title="matplotlib.patches.Patch"><code class="xref py py-class docutils literal"><span class="pre">Patch</span></code></a>
<code class="xref py py-attr docutils literal"><span class="pre">patch</span></code> which is a
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Rectangle" title="matplotlib.patches.Rectangle"><code class="xref py py-class docutils literal"><span class="pre">Rectangle</span></code></a> for Cartesian coordinates and a
<a class="reference internal" href="../api/patches_api.html#matplotlib.patches.Circle" title="matplotlib.patches.Circle"><code class="xref py py-class docutils literal"><span class="pre">Circle</span></code></a> for polar coordinates; this patch
determines the shape, background and border of the plotting region:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="n">rect</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">patch</span>  <span class="c1"># a Rectangle instance</span>
<span class="n">rect</span><span class="o">.</span><span class="n">set_facecolor</span><span class="p">(</span><span class="s1">&#39;green&#39;</span><span class="p">)</span>
</pre></div>
<p>When you call a plotting method, e.g., the canonical
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.plot" title="matplotlib.axes.Axes.plot"><code class="xref py py-meth docutils literal"><span class="pre">plot()</span></code></a> and pass in arrays or lists of
values, the method will create a <a class="reference internal" href="../api/lines_api.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-meth docutils literal"><span class="pre">matplotlib.lines.Line2D()</span></code></a>
instance, update the line with all the <code class="docutils literal"><span class="pre">Line2D</span></code> properties passed as
keyword arguments, add the line to the <code class="xref py py-attr docutils literal"><span class="pre">Axes.lines</span></code> container, and returns it to you:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [213]: </span><span class="n">x</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span>
<span class="gp">In [214]: </span><span class="n">line</span><span class="p">,</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
</pre></div>
<p><code class="docutils literal"><span class="pre">plot</span></code> returns a list of lines because you can pass in multiple x, y
pairs to plot, and we are unpacking the first element of the length
one list into the line variable.  The line has been added to the
<code class="docutils literal"><span class="pre">Axes.lines</span></code> list:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [229]: </span><span class="k">print</span> <span class="n">ax</span><span class="o">.</span><span class="n">lines</span>
<span class="go">[&lt;matplotlib.lines.Line2D instance at 0xd378b0c&gt;]</span>
</pre></div>
<p>Similarly, methods that create patches, like
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.bar" title="matplotlib.axes.Axes.bar"><code class="xref py py-meth docutils literal"><span class="pre">bar()</span></code></a> creates a list of rectangles, will
add the patches to the <code class="xref py py-attr docutils literal"><span class="pre">Axes.patches</span></code> list:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [233]: </span><span class="n">n</span><span class="p">,</span> <span class="n">bins</span><span class="p">,</span> <span class="n">rectangles</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">1000</span><span class="p">),</span> <span class="mi">50</span><span class="p">,</span> <span class="n">facecolor</span><span class="o">=</span><span class="s1">&#39;yellow&#39;</span><span class="p">)</span>
<span class="gp">In [234]: </span><span class="n">rectangles</span>
<span class="gh">Out[234]: </span><span class="go">&lt;a list of 50 Patch objects&gt;</span>
<span class="gp">In [235]: </span><span class="k">print</span> <span class="nb">len</span><span class="p">(</span><span class="n">ax</span><span class="o">.</span><span class="n">patches</span><span class="p">)</span>
</pre></div>
<p>You should not add objects directly to the <code class="docutils literal"><span class="pre">Axes.lines</span></code> or
<code class="docutils literal"><span class="pre">Axes.patches</span></code> lists unless you know exactly what you are doing,
because the <code class="docutils literal"><span class="pre">Axes</span></code> needs to do a few things when it creates and adds
an object.  It sets the figure and axes property of the <code class="docutils literal"><span class="pre">Artist</span></code>, as
well as the default <code class="docutils literal"><span class="pre">Axes</span></code> transformation (unless a transformation
is set).  It also inspects the data contained in the <code class="docutils literal"><span class="pre">Artist</span></code> to
update the data structures controlling auto-scaling, so that the view
limits can be adjusted to contain the plotted data.  You can,
nonetheless, create objects yourself and add them directly to the
<code class="docutils literal"><span class="pre">Axes</span></code> using helper methods like
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.add_line" title="matplotlib.axes.Axes.add_line"><code class="xref py py-meth docutils literal"><span class="pre">add_line()</span></code></a> and
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes.add_patch" title="matplotlib.axes.Axes.add_patch"><code class="xref py py-meth docutils literal"><span class="pre">add_patch()</span></code></a>.  Here is an annotated
interactive session illustrating what is going on:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [261]: </span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="gp">In [262]: </span><span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="go"># create a rectangle instance</span>
<span class="gp">In [263]: </span><span class="n">rect</span> <span class="o">=</span> <span class="n">matplotlib</span><span class="o">.</span><span class="n">patches</span><span class="o">.</span><span class="n">Rectangle</span><span class="p">(</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">),</span> <span class="n">width</span><span class="o">=</span><span class="mi">5</span><span class="p">,</span> <span class="n">height</span><span class="o">=</span><span class="mi">12</span><span class="p">)</span>
<span class="go"># by default the axes instance is None</span>
<span class="gp">In [264]: </span><span class="k">print</span> <span class="n">rect</span><span class="o">.</span><span class="n">get_axes</span><span class="p">()</span>
<span class="go">None</span>
<span class="go"># and the transformation instance is set to the &quot;identity transform&quot;</span>
<span class="gp">In [265]: </span><span class="k">print</span> <span class="n">rect</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()</span>
<span class="go">&lt;Affine object at 0x13695544&gt;</span>
<span class="go"># now we add the Rectangle to the Axes</span>
<span class="gp">In [266]: </span><span class="n">ax</span><span class="o">.</span><span class="n">add_patch</span><span class="p">(</span><span class="n">rect</span><span class="p">)</span>
<span class="go"># and notice that the ax.add_patch method has set the axes</span>
<span class="go"># instance</span>
<span class="gp">In [267]: </span><span class="k">print</span> <span class="n">rect</span><span class="o">.</span><span class="n">get_axes</span><span class="p">()</span>
<span class="go">Axes(0.125,0.1;0.775x0.8)</span>
<span class="go"># and the transformation has been set too</span>
<span class="gp">In [268]: </span><span class="k">print</span> <span class="n">rect</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()</span>
<span class="go">&lt;Affine object at 0x15009ca4&gt;</span>
<span class="go"># the default axes transformation is ax.transData</span>
<span class="gp">In [269]: </span><span class="k">print</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span>
<span class="go">&lt;Affine object at 0x15009ca4&gt;</span>
<span class="go"># notice that the xlimits of the Axes have not been changed</span>
<span class="gp">In [270]: </span><span class="k">print</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_xlim</span><span class="p">()</span>
<span class="go">(0.0, 1.0)</span>
<span class="go"># but the data limits have been updated to encompass the rectangle</span>
<span class="gp">In [271]: </span><span class="k">print</span> <span class="n">ax</span><span class="o">.</span><span class="n">dataLim</span><span class="o">.</span><span class="n">bounds</span>
<span class="go">(1.0, 1.0, 5.0, 12.0)</span>
<span class="go"># we can manually invoke the auto-scaling machinery</span>
<span class="gp">In [272]: </span><span class="n">ax</span><span class="o">.</span><span class="n">autoscale_view</span><span class="p">()</span>
<span class="go"># and now the xlim are updated to encompass the rectangle</span>
<span class="gp">In [273]: </span><span class="k">print</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_xlim</span><span class="p">()</span>
<span class="go">(1.0, 6.0)</span>
<span class="go"># we have to manually force a figure draw</span>
<span class="gp">In [274]: </span><span class="n">ax</span><span class="o">.</span><span class="n">figure</span><span class="o">.</span><span class="n">canvas</span><span class="o">.</span><span class="n">draw</span><span class="p">()</span>
</pre></div>
<p>There are many, many <code class="docutils literal"><span class="pre">Axes</span></code> helper methods for creating primitive
<code class="docutils literal"><span class="pre">Artists</span></code> and adding them to their respective containers.  The table
below summarizes a small sampling of them, the kinds of <code class="docutils literal"><span class="pre">Artist</span></code> they
create, and where they store them</p>
<table border="1" class="docutils">
<col width="41%" />
<col width="27%" />
<col width="32%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Helper method</th>
<th class="head">Artist</th>
<th class="head">Container</th>
<tbody valign="top">
<tr class="row-even"><td>ax.annotate - text annotations</td>
<td>Annotate</td>
<td>ax.texts</td>
<tr class="row-odd"><td>ax.bar  - bar charts</td>
<td>Rectangle</td>
<td>ax.patches</td>
<tr class="row-even"><td>ax.errorbar - error bar plots</td>
<td>Line2D and Rectangle</td>
<td>ax.lines and ax.patches</td>
<tr class="row-odd"><td>ax.fill - shared area</td>
<td>Polygon</td>
<td>ax.patches</td>
<tr class="row-even"><td>ax.hist - histograms</td>
<td>Rectangle</td>
<td>ax.patches</td>
<tr class="row-odd"><td>ax.imshow - image data</td>
<td>AxesImage</td>
<td>ax.images</td>
<tr class="row-even"><td>ax.legend - axes legends</td>
<td>Legend</td>
<td>ax.legends</td>
<tr class="row-odd"><td>ax.plot - xy plots</td>
<td>Line2D</td>
<td>ax.lines</td>
<tr class="row-even"><td>ax.scatter - scatter charts</td>
<td>PolygonCollection</td>
<td>ax.collections</td>
<tr class="row-odd"><td>ax.text - text</td>
<td>Text</td>
<td>ax.texts</td>
<p>In addition to all of these <code class="docutils literal"><span class="pre">Artists</span></code>, the <code class="docutils literal"><span class="pre">Axes</span></code> contains two
important <code class="docutils literal"><span class="pre">Artist</span></code> containers: the <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.XAxis" title="matplotlib.axis.XAxis"><code class="xref py py-class docutils literal"><span class="pre">XAxis</span></code></a>
and <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.YAxis" title="matplotlib.axis.YAxis"><code class="xref py py-class docutils literal"><span class="pre">YAxis</span></code></a>, which handle the drawing of the
ticks and labels.  These are stored as instance variables
<code class="xref py py-attr docutils literal"><span class="pre">xaxis</span></code> and
<code class="xref py py-attr docutils literal"><span class="pre">yaxis</span></code>.  The <code class="docutils literal"><span class="pre">XAxis</span></code> and <code class="docutils literal"><span class="pre">YAxis</span></code>
containers will be detailed below, but note that the <code class="docutils literal"><span class="pre">Axes</span></code> contains
many helper methods which forward calls on to the
<a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-class docutils literal"><span class="pre">Axis</span></code></a> instances so you often do not need to
work with them directly unless you want to.  For example, you can set
the font size of the <code class="docutils literal"><span class="pre">XAxis</span></code> ticklabels using the <code class="docutils literal"><span class="pre">Axes</span></code> helper
method:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_xticklabels</span><span class="p">():</span>
    <span class="n">label</span><span class="o">.</span><span class="n">set_color</span><span class="p">(</span><span class="s1">&#39;orange&#39;</span><span class="p">)</span>
</pre></div>
<p>Below is a summary of the Artists that the Axes contains</p>
<table border="1" class="docutils">
<col width="27%" />
<col width="73%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Axes attribute</th>
<th class="head">Description</th>
<tbody valign="top">
<tr class="row-even"><td>artists</td>
<td>A list of Artist instances</td>
<tr class="row-odd"><td>patch</td>
<td>Rectangle instance for Axes background</td>
<tr class="row-even"><td>collections</td>
<td>A list of Collection instances</td>
<tr class="row-odd"><td>images</td>
<td>A list of AxesImage</td>
<tr class="row-even"><td>legends</td>
<td>A list of Legend instances</td>
<tr class="row-odd"><td>lines</td>
<td>A list of Line2D instances</td>
<tr class="row-even"><td>patches</td>
<td>A list of Patch instances</td>
<tr class="row-odd"><td>texts</td>
<td>A list of Text instances</td>
<tr class="row-even"><td>xaxis</td>
<td>matplotlib.axis.XAxis instance</td>
<tr class="row-odd"><td>yaxis</td>
<td>matplotlib.axis.YAxis instance</td>
<div class="section" id="axis-containers">
<span id="axis-container"></span><h2>Axis containers<a class="headerlink" href="#axis-containers" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.axis.Axis</span></code></a> instances handle the drawing of the
tick lines, the grid lines, the tick labels and the axis label.  You
can configure the left and right ticks separately for the y-axis, and
the upper and lower ticks separately for the x-axis.  The <code class="docutils literal"><span class="pre">Axis</span></code>
also stores the data and view intervals used in auto-scaling, panning
and zooming, as well as the <a class="reference internal" href="../api/ticker_api.html#matplotlib.ticker.Locator" title="matplotlib.ticker.Locator"><code class="xref py py-class docutils literal"><span class="pre">Locator</span></code></a> and
<a class="reference internal" href="../api/ticker_api.html#matplotlib.ticker.Formatter" title="matplotlib.ticker.Formatter"><code class="xref py py-class docutils literal"><span class="pre">Formatter</span></code></a> instances which control where
the ticks are placed and how they are represented as strings.</p>
<p>Each <code class="docutils literal"><span class="pre">Axis</span></code> object contains a <code class="xref py py-attr docutils literal"><span class="pre">label</span></code> attribute
(this is what <code class="xref py py-mod docutils literal"><span class="pre">pylab</span></code> modifies in calls to
<code class="xref py py-func docutils literal"><span class="pre">xlabel()</span></code> and <code class="xref py py-func docutils literal"><span class="pre">ylabel()</span></code>) as well
as a list of major and minor ticks.  The ticks are
<a class="reference internal" href="../api/axis_api.html#matplotlib.axis.XTick" title="matplotlib.axis.XTick"><code class="xref py py-class docutils literal"><span class="pre">XTick</span></code></a> and <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.YTick" title="matplotlib.axis.YTick"><code class="xref py py-class docutils literal"><span class="pre">YTick</span></code></a> instances,
which contain the actual line and text primitives that render the ticks and
ticklabels.  Because the ticks are dynamically created as needed (e.g., when
panning and zooming), you should access the lists of major and minor ticks
through their accessor methods <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis.get_major_ticks" title="matplotlib.axis.Axis.get_major_ticks"><code class="xref py py-meth docutils literal"><span class="pre">get_major_ticks()</span></code></a>
and <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis.get_minor_ticks" title="matplotlib.axis.Axis.get_minor_ticks"><code class="xref py py-meth docutils literal"><span class="pre">get_minor_ticks()</span></code></a>.  Although the ticks contain
all the primitives and will be covered below, the <code class="docutils literal"><span class="pre">Axis</span></code> methods contain
accessor methods to return the tick lines, tick labels, tick locations etc.:</p>
<div class="highlight-ipython"><div class="highlight"><pre><span class="gp">In [285]: </span><span class="n">axis</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span>
<span class="gp">In [286]: </span><span class="n">axis</span><span class="o">.</span><span class="n">get_ticklocs</span><span class="p">()</span>
<span class="gh">Out[286]: </span><span class="go">array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9.])</span>
<span class="gp">In [287]: </span><span class="n">axis</span><span class="o">.</span><span class="n">get_ticklabels</span><span class="p">()</span>
<span class="gh">Out[287]: </span><span class="go">&lt;a list of 10 Text major ticklabel objects&gt;</span>
<span class="go"># note there are twice as many ticklines as labels because by</span>
<span class="go">#  default there are tick lines at the top and bottom but only tick</span>
<span class="go">#  labels below the xaxis; this can be customized</span>
<span class="gp">In [288]: </span><span class="n">axis</span><span class="o">.</span><span class="n">get_ticklines</span><span class="p">()</span>
<span class="gh">Out[288]: </span><span class="go">&lt;a list of 20 Line2D ticklines objects&gt;</span>
<span class="go"># by default you get the major ticks back</span>
<span class="gp">In [291]: </span><span class="n">axis</span><span class="o">.</span><span class="n">get_ticklines</span><span class="p">()</span>
<span class="gh">Out[291]: </span><span class="go">&lt;a list of 20 Line2D ticklines objects&gt;</span>
<span class="go"># but you can also ask for the minor ticks</span>
<span class="gp">In [292]: </span><span class="n">axis</span><span class="o">.</span><span class="n">get_ticklines</span><span class="p">(</span><span class="n">minor</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gh">Out[292]: </span><span class="go">&lt;a list of 0 Line2D ticklines objects&gt;</span>
</pre></div>
<p>Here is a summary of some of the useful accessor methods of the <code class="docutils literal"><span class="pre">Axis</span></code>
(these have corresponding setters where useful, such as
set_major_formatter)</p>
<table border="1" class="docutils">
<col width="28%" />
<col width="72%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Accessor method</th>
<th class="head">Description</th>
<tbody valign="top">
<tr class="row-even"><td>get_scale</td>
<td>The scale of the axis, e.g., &#8216;log&#8217; or &#8216;linear&#8217;</td>
<tr class="row-odd"><td>get_view_interval</td>
<td>The interval instance of the axis view limits</td>
<tr class="row-even"><td>get_data_interval</td>
<td>The interval instance of the axis data limits</td>
<tr class="row-odd"><td>get_gridlines</td>
<td>A list of grid lines for the Axis</td>
<tr class="row-even"><td>get_label</td>
<td>The axis label - a Text instance</td>
<tr class="row-odd"><td>get_ticklabels</td>
<td>A list of Text instances - keyword minor=True|False</td>
<tr class="row-even"><td>get_ticklines</td>
<td>A list of Line2D instances - keyword minor=True|False</td>
<tr class="row-odd"><td>get_ticklocs</td>
<td>A list of Tick locations - keyword minor=True|False</td>
<tr class="row-even"><td>get_major_locator</td>
<td>The matplotlib.ticker.Locator instance for major ticks</td>
<tr class="row-odd"><td>get_major_formatter</td>
<td>The matplotlib.ticker.Formatter instance for major ticks</td>
<tr class="row-even"><td>get_minor_locator</td>
<td>The matplotlib.ticker.Locator instance for minor ticks</td>
<tr class="row-odd"><td>get_minor_formatter</td>
<td>The matplotlib.ticker.Formatter instance for minor ticks</td>
<tr class="row-even"><td>get_major_ticks</td>
<td>A list of Tick instances for major ticks</td>
<tr class="row-odd"><td>get_minor_ticks</td>
<td>A list of Tick instances for minor ticks</td>
<tr class="row-even"><td>grid</td>
<td>Turn the grid on or off for the major or minor ticks</td>
<p>Here is an example, not recommended for its beauty, which customizes
the axes and tick properties</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="c1"># plt.figure creates a matplotlib.figure.Figure instance</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">rect</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">patch</span> <span class="c1"># a rectangle instance</span>
<span class="n">rect</span><span class="o">.</span><span class="n">set_facecolor</span><span class="p">(</span><span class="s1">&#39;lightgoldenrodyellow&#39;</span><span class="p">)</span>
<span class="n">ax1</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.4</span><span class="p">,</span> <span class="mf">0.4</span><span class="p">])</span>
<span class="n">rect</span> <span class="o">=</span> <span class="n">ax1</span><span class="o">.</span><span class="n">patch</span>
<span class="n">rect</span><span class="o">.</span><span class="n">set_facecolor</span><span class="p">(</span><span class="s1">&#39;lightslategray&#39;</span><span class="p">)</span>
<span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">ax1</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">get_ticklabels</span><span class="p">():</span>
    <span class="c1"># label is a Text instance</span>
    <span class="n">label</span><span class="o">.</span><span class="n">set_color</span><span class="p">(</span><span class="s1">&#39;red&#39;</span><span class="p">)</span>
    <span class="n">label</span><span class="o">.</span><span class="n">set_rotation</span><span class="p">(</span><span class="mi">45</span><span class="p">)</span>
    <span class="n">label</span><span class="o">.</span><span class="n">set_fontsize</span><span class="p">(</span><span class="mi">16</span><span class="p">)</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">ax1</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">get_ticklines</span><span class="p">():</span>
    <span class="c1"># line is a Line2D instance</span>
    <span class="n">line</span><span class="o">.</span><span class="n">set_color</span><span class="p">(</span><span class="s1">&#39;green&#39;</span><span class="p">)</span>
    <span class="n">line</span><span class="o">.</span><span class="n">set_markersize</span><span class="p">(</span><span class="mi">25</span><span class="p">)</span>
    <span class="n">line</span><span class="o">.</span><span class="n">set_markeredgewidth</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
</pre></div>
<p>(<a class="reference external" href="../pyplots/fig_axes_customize_simple.py">Source code</a>, <a class="reference external" href="../pyplots/fig_axes_customize_simple.png">png</a>, <a class="reference external" href="../pyplots/fig_axes_customize_simple.hires.png">hires.png</a>, <a class="reference external" href="../pyplots/fig_axes_customize_simple.pdf">pdf</a>)</p>
<div class="figure">
<img alt="../_images/fig_axes_customize_simple.png" src="../_images/fig_axes_customize_simple.png" />
<div class="section" id="tick-containers">
<span id="tick-container"></span><h2>Tick containers<a class="headerlink" href="#tick-containers" title="Permalink to this headline">¶</a></h2>
<p>The <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Tick" title="matplotlib.axis.Tick"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.axis.Tick</span></code></a> is the final container object in our
descent from the <a class="reference internal" href="../api/figure_api.html#matplotlib.figure.Figure" title="matplotlib.figure.Figure"><code class="xref py py-class docutils literal"><span class="pre">Figure</span></code></a> to the
<a class="reference internal" href="../api/axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><code class="xref py py-class docutils literal"><span class="pre">Axes</span></code></a> to the <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-class docutils literal"><span class="pre">Axis</span></code></a>
to the <a class="reference internal" href="../api/axis_api.html#matplotlib.axis.Tick" title="matplotlib.axis.Tick"><code class="xref py py-class docutils literal"><span class="pre">Tick</span></code></a>.  The <code class="docutils literal"><span class="pre">Tick</span></code> contains the tick
and grid line instances, as well as the label instances for the upper
and lower ticks.  Each of these is accessible directly as an attribute
of the <code class="docutils literal"><span class="pre">Tick</span></code>.  In addition, there are boolean variables that determine
whether the upper labels and ticks are on for the x-axis and whether
the right labels and ticks are on for the y-axis.</p>
<table border="1" class="docutils">
<col width="19%" />
<col width="81%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Tick attribute</th>
<th class="head">Description</th>
<tbody valign="top">
<tr class="row-even"><td>tick1line</td>
<td>Line2D instance</td>
<tr class="row-odd"><td>tick2line</td>
<td>Line2D instance</td>
<tr class="row-even"><td>gridline</td>
<td>Line2D instance</td>
<tr class="row-odd"><td>label1</td>
<td>Text instance</td>
<tr class="row-even"><td>label2</td>
<td>Text instance</td>
<tr class="row-odd"><td>gridOn</td>
<td>boolean which determines whether to draw the tickline</td>
<tr class="row-even"><td>tick1On</td>
<td>boolean which determines whether to draw the 1st tickline</td>
<tr class="row-odd"><td>tick2On</td>
<td>boolean which determines whether to draw the 2nd tickline</td>
<tr class="row-even"><td>label1On</td>
<td>boolean which determines whether to draw tick label</td>
<tr class="row-odd"><td>label2On</td>
<td>boolean which determines whether to draw tick label</td>
<p>Here is an example which sets the formatter for the right side ticks with
dollar signs and colors them green on the right side of the yaxis</p>
<div class="highlight-python"><div class="highlight"><pre><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.ticker</span> <span class="kn">as</span> <span class="nn">ticker</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="mi">100</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">20</span><span class="p">))</span>
<span class="n">formatter</span> <span class="o">=</span> <span class="n">ticker</span><span class="o">.</span><span class="n">FormatStrFormatter</span><span class="p">(</span><span class="s1">&#39;$</span><span class="si">%1.2f</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">set_major_formatter</span><span class="p">(</span><span class="n">formatter</span><span class="p">)</span>
<span class="k">for</span> <span class="n">tick</span> <span class="ow">in</span> <span class="n">ax</span><span class="o">.</span><span class="n">yaxis</span><span class="o">.</span><span class="n">get_major_ticks</span><span class="p">():</span>
    <span class="n">tick</span><span class="o">.</span><span class="n">label1On</span> <span class="o">=</span> <span class="bp">False</span>
    <span class="n">tick</span><span class="o">.</span><span class="n">label2On</span> <span class="o">=</span> <span class="bp">True</span>
    <span class="n">tick</span><span class="o">.</span><span class="n">label2</span><span class="o">.</span><span class="n">set_color</span><span class="p">(</span><span class="s1">&#39;green&#39;</span><span class="p">)</span>
</pre></div>
<p>(<a class="reference external" href="../pyplots/dollar_ticks.py">Source code</a>, <a class="reference external" href="../pyplots/dollar_ticks.png">png</a>, <a class="reference external" href="../pyplots/dollar_ticks.hires.png">hires.png</a>, <a class="reference external" href="../pyplots/dollar_ticks.pdf">pdf</a>)</p>
<div class="figure">
<img alt="../_images/dollar_ticks.png" src="../_images/dollar_ticks.png" />
          </div>
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        &copy; Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the matplotlib development team; 2012 - 2014 The matplotlib development team.
      Last updated on Jun 18, 2016.
      Created using <a
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