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<div class="section" id="working-with-transformations">
<h1>Working with transformations<a class="headerlink" href="#working-with-transformations" title="Permalink to this headline">¶</a></h1>
<img src="../_images/inheritance-eafd5ed19d2f8badee138776b0306812a48917f9.png" alt="Inheritance diagram of matplotlib.transforms, matplotlib.path" usemap="#inheritancedbde0cb62f" class="inheritance"/>
<map id="inheritancedbde0cb62f" name="inheritancedbde0cb62f">
<area shape="rect" id="node1" href="#matplotlib.transforms.Affine2D" target="_top" title="A mutable 2D affine transformation." alt="" coords="531,4,583,20"/>
<area shape="rect" id="node2" href="#matplotlib.transforms.Affine2DBase" target="_top" title="The base class of all 2D affine transformations." alt="" coords="402,118,475,135"/>
<area shape="rect" id="node8" href="#matplotlib.transforms.BboxTransform" target="_top" title=":class:`BboxTransform` linearly transforms points from one" alt="" coords="517,36,596,53"/>
<area shape="rect" id="node9" href="#matplotlib.transforms.BboxTransformFrom" target="_top" title=":class:`BboxTransformFrom` linearly transforms points from a given" alt="" coords="506,69,607,85"/>
<area shape="rect" id="node10" href="#matplotlib.transforms.BboxTransformTo" target="_top" title=":class:`BboxTransformTo` is a transformation that linearly" alt="" coords="512,101,601,118"/>
<area shape="rect" id="node12" href="#matplotlib.transforms.BlendedAffine2D" target="_top" title="A "blended" transform uses one transform for the *x*-direction, and" alt="" coords="513,134,600,151"/>
<area shape="rect" id="node14" href="#matplotlib.transforms.CompositeAffine2D" target="_top" title="A composite transform formed by applying transform *a* then transform *b*." alt="" coords="508,166,606,183"/>
<area shape="rect" id="node16" href="#matplotlib.transforms.IdentityTransform" target="_top" title="A special class that does one thing, the identity transform, in a" alt="" coords="511,199,602,216"/>
<area shape="rect" id="node19" href="#matplotlib.transforms.ScaledTranslation" target="_top" title="A transformation that translates by *xt* and *yt*, after *xt* and *yt*" alt="" coords="512,232,602,248"/>
<area shape="rect" id="node3" href="#matplotlib.transforms.AffineBase" target="_top" title="The base class of all affine transformations of any number of" alt="" coords="271,118,332,135"/>
<area shape="rect" id="node4" href="#matplotlib.transforms.Transform" target="_top" title="The base class of all :class:`TransformNode` instances that" alt="" coords="130,183,187,200"/>
<area shape="rect" id="node13" href="#matplotlib.transforms.BlendedGenericTransform" target="_top" title="A "blended" transform uses one transform for the *x*-direction, and" alt="" coords="239,151,365,167"/>
<area shape="rect" id="node15" href="#matplotlib.transforms.CompositeGenericTransform" target="_top" title="A composite transform formed by applying transform *a* then" alt="" coords="233,183,370,200"/>
<area shape="rect" id="node20" href="#matplotlib.transforms.TransformWrapper" target="_top" title="A helper class that holds a single child transform and acts" alt="" coords="255,216,348,233"/>
<area shape="rect" id="node5" href="#matplotlib.transforms.Bbox" target="_top" title="A mutable bounding box." alt="" coords="278,248,325,265"/>
<area shape="rect" id="node6" href="#matplotlib.transforms.BboxBase" target="_top" title="This is the base class of all bounding boxes, and provides" alt="" coords="130,281,187,298"/>
<area shape="rect" id="node17" href="#matplotlib.transforms.LockableBbox" target="_top" title="A :class:`Bbox` where some elements may be locked at certain values." alt="" coords="264,281,339,298"/>
<area shape="rect" id="node21" href="#matplotlib.transforms.TransformedBbox" target="_top" title="A :class:`Bbox` that is automatically transformed by a given" alt="" coords="257,314,347,330"/>
<area shape="rect" id="node7" href="#matplotlib.transforms.TransformNode" target="_top" title=":class:`TransformNode` is the base class for anything that" alt="" coords="4,281,84,298"/>
<area shape="rect" id="node23" href="#matplotlib.transforms.TransformedPath" target="_top" title="A :class:`TransformedPath` caches a non-affine transformed copy of" alt="" coords="115,329,202,346"/>
<area shape="rect" id="node11" href="#matplotlib.transforms.BboxTransformToMaxOnly" target="_top" title=":class:`BboxTransformTo` is a transformation that linearly" alt="" coords="639,101,764,118"/>
<area shape="rect" id="node18" href="path_api.html#matplotlib.path.Path" target="_top" title=":class:`Path` represents a series of possibly disconnected," alt="" coords="20,248,67,265"/>
<area shape="rect" id="node22" href="#matplotlib.transforms.TransformedPatchPath" target="_top" title="A :class:`TransformedPatchPath` caches a non-affine transformed copy of" alt="" coords="247,346,357,363"/>
</map><div class="section" id="module-matplotlib.transforms">
<span id="matplotlib-transforms"></span><h2><a class="reference internal" href="#module-matplotlib.transforms" title="matplotlib.transforms"><code class="xref py py-mod docutils literal"><span class="pre">matplotlib.transforms</span></code></a><a class="headerlink" href="#module-matplotlib.transforms" title="Permalink to this headline">¶</a></h2>
<p>matplotlib includes a framework for arbitrary geometric
transformations that is used determine the final position of all
elements drawn on the canvas.</p>
<p>Transforms are composed into trees of <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><code class="xref py py-class docutils literal"><span class="pre">TransformNode</span></code></a> objects
whose actual value depends on their children. When the contents of
children change, their parents are automatically invalidated. The
next time an invalidated transform is accessed, it is recomputed to
reflect those changes. This invalidation/caching approach prevents
unnecessary recomputations of transforms, and contributes to better
interactive performance.</p>
<p>For example, here is a graph of the transform tree used to plot data
to the graph:</p>
<img alt="../_images/transforms.png" src="../_images/transforms.png" />
<p>The framework can be used for both affine and non-affine
transformations. However, for speed, we want use the backend
renderers to perform affine transformations whenever possible.
Therefore, it is possible to perform just the affine or non-affine
part of a transformation on a set of data. The affine is always
assumed to occur after the non-affine. For any transform:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">full</span> <span class="n">transform</span> <span class="o">==</span> <span class="n">non</span><span class="o">-</span><span class="n">affine</span> <span class="n">part</span> <span class="o">+</span> <span class="n">affine</span> <span class="n">part</span>
</pre></div>
</div>
<p>The backends are not expected to handle non-affine transformations
themselves.</p>
<dl class="class">
<dt id="matplotlib.transforms.Affine2D">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">Affine2D</code><span class="sig-paren">(</span><em>matrix=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></code></a></p>
<p>A mutable 2D affine transformation.</p>
<p>Initialize an Affine transform from a 3x3 numpy float array:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
<p>If <em>matrix</em> is None, initialize with the identity transform.</p>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.clear">
<code class="descname">clear</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.clear" title="Permalink to this definition">¶</a></dt>
<dd><p>Reset the underlying matrix to the identity transform.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2D.from_values">
<em class="property">static </em><code class="descname">from_values</code><span class="sig-paren">(</span><em>a</em>, <em>b</em>, <em>c</em>, <em>d</em>, <em>e</em>, <em>f</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.from_values" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new Affine2D instance from the given
values:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
<p>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.get_matrix">
<code class="descname">get_matrix</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a 3x3 numpy array:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
<p>.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2D.identity">
<em class="property">static </em><code class="descname">identity</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.identity" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Return a new <a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><code class="xref py py-class docutils literal"><span class="pre">Affine2D</span></code></a> object that is
the identity transform.</p>
<p>Unless this transform will be mutated later on, consider using
the faster <a class="reference internal" href="#matplotlib.transforms.IdentityTransform" title="matplotlib.transforms.IdentityTransform"><code class="xref py py-class docutils literal"><span class="pre">IdentityTransform</span></code></a> class instead.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Affine2D.is_separable">
<code class="descname">is_separable</code><a class="headerlink" href="#matplotlib.transforms.Affine2D.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate">
<code class="descname">rotate</code><span class="sig-paren">(</span><em>theta</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in radians) to this transform in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_around">
<code class="descname">rotate_around</code><span class="sig-paren">(</span><em>x</em>, <em>y</em>, <em>theta</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_around" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in radians) around the point (x, y) in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg">
<code class="descname">rotate_deg</code><span class="sig-paren">(</span><em>degrees</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_deg" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in degrees) to this transform in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg_around">
<code class="descname">rotate_deg_around</code><span class="sig-paren">(</span><em>x</em>, <em>y</em>, <em>degrees</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_deg_around" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in degrees) around the point (x, y) in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.scale">
<code class="descname">scale</code><span class="sig-paren">(</span><em>sx</em>, <em>sy=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a scale in place.</p>
<p>If <em>sy</em> is None, the same scale is applied in both the <em>x</em>- and
<em>y</em>-directions.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.set">
<code class="descname">set</code><span class="sig-paren">(</span><em>other</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Set this transformation from the frozen copy of another
<a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><code class="xref py py-class docutils literal"><span class="pre">Affine2DBase</span></code></a> object.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.set_matrix">
<code class="descname">set_matrix</code><span class="sig-paren">(</span><em>mtx</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.set_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the underlying transformation matrix from a 3x3 numpy array:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
<p>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.skew">
<code class="descname">skew</code><span class="sig-paren">(</span><em>xShear</em>, <em>yShear</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.skew" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a skew in place.</p>
<p><em>xShear</em> and <em>yShear</em> are the shear angles along the <em>x</em>- and
<em>y</em>-axes, respectively, in radians.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.skew_deg">
<code class="descname">skew_deg</code><span class="sig-paren">(</span><em>xShear</em>, <em>yShear</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.skew_deg" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a skew in place.</p>
<p><em>xShear</em> and <em>yShear</em> are the shear angles along the <em>x</em>- and
<em>y</em>-axes, respectively, in degrees.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.translate">
<code class="descname">translate</code><span class="sig-paren">(</span><em>tx</em>, <em>ty</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.translate" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a translation in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><code class="xref py py-meth docutils literal"><span class="pre">rotate()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><code class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><code class="xref py py-meth docutils literal"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Affine2DBase">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">Affine2DBase</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.AffineBase" title="matplotlib.transforms.AffineBase"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.AffineBase</span></code></a></p>
<p>The base class of all 2D affine transformations.</p>
<p>2D affine transformations are performed using a 3x3 numpy array:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
<p>This class provides the read-only interface. For a mutable 2D
affine transformation, use <a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><code class="xref py py-class docutils literal"><span class="pre">Affine2D</span></code></a>.</p>
<p>Subclasses of this class will generally only need to override a
constructor and <code class="xref py py-meth docutils literal"><span class="pre">get_matrix()</span></code> that generates a custom 3x3 matrix.</p>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.frozen">
<code class="descname">frozen</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a frozen copy of this transform node. The frozen copy
will not update when its children change. Useful for storing
a previously known state of a transform where
<code class="docutils literal"><span class="pre">copy.deepcopy()</span></code> might normally be used.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Affine2DBase.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Affine2DBase.input_dims">
<code class="descname">input_dims</code><em class="property"> = 2</em><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><code class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code></p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Affine2DBase.is_separable">
<code class="descname">is_separable</code><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2DBase.matrix_from_values">
<em class="property">static </em><code class="descname">matrix_from_values</code><span class="sig-paren">(</span><em>a</em>, <em>b</em>, <em>c</em>, <em>d</em>, <em>e</em>, <em>f</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.matrix_from_values" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new transformation matrix as a 3x3
numpy array of the form:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="n">a</span> <span class="n">c</span> <span class="n">e</span>
<span class="n">b</span> <span class="n">d</span> <span class="n">f</span>
<span class="mi">0</span> <span class="mi">0</span> <span class="mi">1</span>
</pre></div>
</div>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Affine2DBase.output_dims">
<code class="descname">output_dims</code><em class="property"> = 2</em><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.to_values">
<code class="descname">to_values</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.to_values" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the values of the matrix as a sequence (a,b,c,d,e,f)</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.transform_affine">
<code class="descname">transform_affine</code><span class="sig-paren">(</span><em>points</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><code class="docutils literal"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<code class="docutils literal"><span class="pre">transform(values)</span></code>.</p>
<p>Accepts a numpy array of shape (N x <a class="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code></a>) and
returns a numpy array of shape (N x <a class="reference internal" href="#matplotlib.transforms.Affine2DBase.output_dims" title="matplotlib.transforms.Affine2DBase.output_dims"><code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code></a>).</p>
<p>Alternatively, accepts a numpy array of length <a class="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code></a>
and returns a numpy array of length <a class="reference internal" href="#matplotlib.transforms.Affine2DBase.output_dims" title="matplotlib.transforms.Affine2DBase.output_dims"><code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.transform_point">
<code class="descname">transform_point</code><span class="sig-paren">(</span><em>point</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_point" title="Permalink to this definition">¶</a></dt>
<dd><p>A convenience function that returns the transformed copy of a
single point.</p>
<p>The point is given as a sequence of length <a class="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code></a>.
The transformed point is returned as a sequence of length
<a class="reference internal" href="#matplotlib.transforms.Affine2DBase.output_dims" title="matplotlib.transforms.Affine2DBase.output_dims"><code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code></a>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.AffineBase">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">AffineBase</code><span class="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<p>The base class of all affine transformations of any number of
dimensions.</p>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.get_affine">
<code class="descname">get_affine</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.AffineBase.is_affine">
<code class="descname">is_affine</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.transforms.AffineBase.is_affine" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform">
<code class="descname">transform</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs the transformation on the given array of values.</p>
<p>Accepts a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>) and
returns a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>).</p>
<p>Alternatively, accepts a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>
and returns a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_affine">
<code class="descname">transform_affine</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><code class="docutils literal"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<code class="docutils literal"><span class="pre">transform(values)</span></code>.</p>
<p>Accepts a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>) and
returns a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>).</p>
<p>Alternatively, accepts a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>
and returns a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em>points</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><code class="docutils literal"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>) and
returns a numpy array of shape (N x <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>).</p>
<p>Alternatively, accepts a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code>
and returns a numpy array of length <code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_path">
<code class="descname">transform_path</code><span class="sig-paren">(</span><em>path</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a transformed path.</p>
<p><em>path</em>: a <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-class docutils literal"><span class="pre">Path</span></code></a> instance.</p>
<p>In some cases, this transform may insert curves into the path
that began as line segments.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_path_affine">
<code class="descname">transform_path_affine</code><span class="sig-paren">(</span><em>path</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a path, transformed only by the affine part of
this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-class docutils literal"><span class="pre">Path</span></code></a> instance.</p>
<p><code class="docutils literal"><span class="pre">transform_path(path)</span></code> is equivalent to
<code class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></code>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_path_non_affine">
<code class="descname">transform_path_non_affine</code><span class="sig-paren">(</span><em>path</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-class docutils literal"><span class="pre">Path</span></code></a> instance.</p>
<p><code class="docutils literal"><span class="pre">transform_path(path)</span></code> is equivalent to
<code class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></code>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Bbox">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">Bbox</code><span class="sig-paren">(</span><em>points</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.BboxBase</span></code></a></p>
<p>A mutable bounding box.</p>
<p><em>points</em>: a 2x2 numpy array of the form [[x0, y0], [x1, y1]]</p>
<p>If you need to create a <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> object from another form
of data, consider the static methods <a class="reference internal" href="#matplotlib.transforms.Bbox.unit" title="matplotlib.transforms.Bbox.unit"><code class="xref py py-meth docutils literal"><span class="pre">unit()</span></code></a>,
<a class="reference internal" href="#matplotlib.transforms.Bbox.from_bounds" title="matplotlib.transforms.Bbox.from_bounds"><code class="xref py py-meth docutils literal"><span class="pre">from_bounds()</span></code></a> and <a class="reference internal" href="#matplotlib.transforms.Bbox.from_extents" title="matplotlib.transforms.Bbox.from_extents"><code class="xref py py-meth docutils literal"><span class="pre">from_extents()</span></code></a>.</p>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.bounds">
<code class="descname">bounds</code><a class="headerlink" href="#matplotlib.transforms.Bbox.bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) Returns (<a class="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>, <code class="xref py py-attr docutils literal"><span class="pre">width</span></code>,
<code class="xref py py-attr docutils literal"><span class="pre">height</span></code>).</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.from_bounds">
<em class="property">static </em><code class="descname">from_bounds</code><span class="sig-paren">(</span><em>x0</em>, <em>y0</em>, <em>width</em>, <em>height</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.from_bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> from <em>x0</em>, <em>y0</em>,
<em>width</em> and <em>height</em>.</p>
<p><em>width</em> and <em>height</em> may be negative.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.from_extents">
<em class="property">static </em><code class="descname">from_extents</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.from_extents" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new Bbox from <em>left</em>, <em>bottom</em>,
<em>right</em> and <em>top</em>.</p>
<p>The <em>y</em>-axis increases upwards.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.get_points">
<code class="descname">get_points</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.get_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the points of the bounding box directly as a numpy array
of the form: [[x0, y0], [x1, y1]].</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.ignore">
<code class="descname">ignore</code><span class="sig-paren">(</span><em>value</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.ignore" title="Permalink to this definition">¶</a></dt>
<dd><p>Set whether the existing bounds of the box should be ignored
by subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="matplotlib.transforms.Bbox.update_from_data_xy"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data_xy()</span></code></a>.</p>
<p><em>value</em>:</p>
<blockquote>
<div><ul class="simple">
<li>When True, subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="matplotlib.transforms.Bbox.update_from_data_xy"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data_xy()</span></code></a>
will ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>When False, subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="matplotlib.transforms.Bbox.update_from_data_xy"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data_xy()</span></code></a>
will include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
</ul>
</div></blockquote>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.intervalx">
<code class="descname">intervalx</code><a class="headerlink" href="#matplotlib.transforms.Bbox.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.intervalx" title="matplotlib.transforms.Bbox.intervalx"><code class="xref py py-attr docutils literal"><span class="pre">intervalx</span></code></a> is the pair of <em>x</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from left to right.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.intervaly">
<code class="descname">intervaly</code><a class="headerlink" href="#matplotlib.transforms.Bbox.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.intervaly" title="matplotlib.transforms.Bbox.intervaly"><code class="xref py py-attr docutils literal"><span class="pre">intervaly</span></code></a> is the pair of <em>y</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from bottom to
top.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.minpos">
<code class="descname">minpos</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minpos" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.minposx">
<code class="descname">minposx</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minposx" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.minposy">
<code class="descname">minposy</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minposy" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutated">
<code class="descname">mutated</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.mutated" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the bbox has changed since init</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutatedx">
<code class="descname">mutatedx</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.mutatedx" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the x-limits have changed since init</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutatedy">
<code class="descname">mutatedy</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.mutatedy" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the y-limits have changed since init</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.null">
<em class="property">static </em><code class="descname">null</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.null" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new null <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> from (inf, inf) to
(-inf, -inf).</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.p0">
<code class="descname">p0</code><a class="headerlink" href="#matplotlib.transforms.Bbox.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.p0" title="matplotlib.transforms.Bbox.p0"><code class="xref py py-attr docutils literal"><span class="pre">p0</span></code></a> is the first pair of (<em>x</em>, <em>y</em>) coordinates that
define the bounding box. It is not guaranteed to be the bottom-left
corner. For that, use <code class="xref py py-attr docutils literal"><span class="pre">min</span></code>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.p1">
<code class="descname">p1</code><a class="headerlink" href="#matplotlib.transforms.Bbox.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.p1" title="matplotlib.transforms.Bbox.p1"><code class="xref py py-attr docutils literal"><span class="pre">p1</span></code></a> is the second pair of (<em>x</em>, <em>y</em>) coordinates that
define the bounding box. It is not guaranteed to be the top-right
corner. For that, use <code class="xref py py-attr docutils literal"><span class="pre">max</span></code>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.set">
<code class="descname">set</code><span class="sig-paren">(</span><em>other</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Set this bounding box from the “frozen” bounds of another
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.set_points">
<code class="descname">set_points</code><span class="sig-paren">(</span><em>points</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.set_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the points of the bounding box directly from a numpy array
of the form: [[x0, y0], [x1, y1]]. No error checking is
performed, as this method is mainly for internal use.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.unit">
<em class="property">static </em><code class="descname">unit</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.unit" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new unit <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> from (0, 0) to
(1, 1).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_data">
<code class="descname">update_from_data</code><span class="sig-paren">(</span><em>x</em>, <em>y</em>, <em>ignore=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_data" title="Permalink to this definition">¶</a></dt>
<dd><div class="deprecated">
<p><span class="versionmodified">Deprecated since version 2.0: </span>The update_from_data function was deprecated in version 2.0. Use update_from_data_xy instead.</p>
</div>
<p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>x</em>: a numpy array of <em>x</em>-values</p>
<p><em>y</em>: a numpy array of <em>y</em>-values</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><code class="xref py py-meth docutils literal"><span class="pre">ignore()</span></code></a>.</li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_data_xy">
<code class="descname">update_from_data_xy</code><span class="sig-paren">(</span><em>xy</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>xy</em>: a numpy array of 2D points</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><code class="xref py py-meth docutils literal"><span class="pre">ignore()</span></code></a>.</li>
</ul>
</dd>
</dl>
<p><em>updatex</em>: when True, update the x values</p>
<p><em>updatey</em>: when True, update the y values</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_path">
<code class="descname">update_from_path</code><span class="sig-paren">(</span><em>path</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>path</em>: a <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-class docutils literal"><span class="pre">Path</span></code></a> instance</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><code class="xref py py-meth docutils literal"><span class="pre">ignore()</span></code></a>.</li>
</ul>
</dd>
</dl>
<p><em>updatex</em>: when True, update the x values</p>
<p><em>updatey</em>: when True, update the y values</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.x0">
<code class="descname">x0</code><a class="headerlink" href="#matplotlib.transforms.Bbox.x0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a> is the first of the pair of <em>x</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a> is not guaranteed to be less than
<a class="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a>. If you require that, use <code class="xref py py-attr docutils literal"><span class="pre">xmin</span></code>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.x1">
<code class="descname">x1</code><a class="headerlink" href="#matplotlib.transforms.Bbox.x1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a> is the second of the pair of <em>x</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a> is not guaranteed to be greater
than <a class="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>. If you require that, use <code class="xref py py-attr docutils literal"><span class="pre">xmax</span></code>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.y0">
<code class="descname">y0</code><a class="headerlink" href="#matplotlib.transforms.Bbox.y0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a> is the first of the pair of <em>y</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a> is not guaranteed to be less than
<a class="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a>. If you require that, use <code class="xref py py-attr docutils literal"><span class="pre">ymin</span></code>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Bbox.y1">
<code class="descname">y1</code><a class="headerlink" href="#matplotlib.transforms.Bbox.y1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a> is the second of the pair of <em>y</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a> is not guaranteed to be greater
than <a class="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>. If you require that, use <code class="xref py py-attr docutils literal"><span class="pre">ymax</span></code>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BboxBase">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">BboxBase</code><span class="sig-paren">(</span><em>shorthand_name=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.TransformNode</span></code></a></p>
<p>This is the base class of all bounding boxes, and provides
read-only access to its data. A mutable bounding box is provided
by the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> class.</p>
<p>The canonical representation is as two points, with no
restrictions on their ordering. Convenience properties are
provided to get the left, bottom, right and top edges and width
and height, but these are not stored explicitly.</p>
<p>Creates a new <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><code class="xref py py-class docutils literal"><span class="pre">TransformNode</span></code></a>.</p>
<dl class="docutils">
<dt><strong>shorthand_name</strong> - a string representing the “name” of this</dt>
<dd>transform. The name carries no significance
other than to improve the readability of
<code class="docutils literal"><span class="pre">str(transform)</span></code> when DEBUG=True.</dd>
</dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.anchored">
<code class="descname">anchored</code><span class="sig-paren">(</span><em>c</em>, <em>container=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.anchored" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>, shifted to position <em>c</em>
within a container.</p>
<p><em>c</em>: may be either:</p>
<blockquote>
<div><ul class="simple">
<li>a sequence (<em>cx</em>, <em>cy</em>) where <em>cx</em> and <em>cy</em> range from 0
to 1, where 0 is left or bottom and 1 is right or top</li>
<li>a string:
- ‘C’ for centered
- ‘S’ for bottom-center
- ‘SE’ for bottom-left
- ‘E’ for left
- etc.</li>
</ul>
</div></blockquote>
<p>Optional argument <em>container</em> is the box within which the
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> is positioned; it defaults to the initial
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.bounds">
<code class="descname">bounds</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) Returns (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.width" title="matplotlib.transforms.BboxBase.width"><code class="xref py py-attr docutils literal"><span class="pre">width</span></code></a>,
<a class="reference internal" href="#matplotlib.transforms.BboxBase.height" title="matplotlib.transforms.BboxBase.height"><code class="xref py py-attr docutils literal"><span class="pre">height</span></code></a>).</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.coefs">
<code class="descname">coefs</code><em class="property"> = {'C': (0.5, 0.5), 'E': (1.0, 0.5), 'N': (0.5, 1.0), 'NE': (1.0, 1.0), 'NW': (0, 1.0), 'S': (0.5, 0), 'SE': (1.0, 0), 'SW': (0, 0), 'W': (0, 0.5)}</em><a class="headerlink" href="#matplotlib.transforms.BboxBase.coefs" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.contains">
<code class="descname">contains</code><span class="sig-paren">(</span><em>x</em>, <em>y</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">x,</span> <span class="pre">y</span></code> is in the bounding box or on its edge.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.containsx">
<code class="descname">containsx</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">x</span></code> is in the closed (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a>) interval.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.containsy">
<code class="descname">containsy</code><span class="sig-paren">(</span><em>y</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">y</span></code> is in the closed (<a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a>) interval.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.corners">
<code class="descname">corners</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.corners" title="Permalink to this definition">¶</a></dt>
<dd><p>Return an array of points which are the four corners of this
rectangle. For example, if this <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> is defined by
the points (<em>a</em>, <em>b</em>) and (<em>c</em>, <em>d</em>), <a class="reference internal" href="#matplotlib.transforms.BboxBase.corners" title="matplotlib.transforms.BboxBase.corners"><code class="xref py py-meth docutils literal"><span class="pre">corners()</span></code></a> returns
(<em>a</em>, <em>b</em>), (<em>a</em>, <em>d</em>), (<em>c</em>, <em>b</em>) and (<em>c</em>, <em>d</em>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.count_contains">
<code class="descname">count_contains</code><span class="sig-paren">(</span><em>vertices</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.count_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Count the number of vertices contained in the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>.
Any vertices with a non-finite x or y value are ignored.</p>
<p><em>vertices</em> is a Nx2 Numpy array.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.count_overlaps">
<code class="descname">count_overlaps</code><span class="sig-paren">(</span><em>bboxes</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.count_overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Count the number of bounding boxes that overlap this one.</p>
<p>bboxes is a sequence of <a class="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><code class="xref py py-class docutils literal"><span class="pre">BboxBase</span></code></a> objects</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.expanded">
<code class="descname">expanded</code><span class="sig-paren">(</span><em>sw</em>, <em>sh</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.expanded" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> which is this <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a>
expanded around its center by the given factors <em>sw</em> and
<em>sh</em>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.extents">
<code class="descname">extents</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.extents" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) Returns (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a>,
<a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.frozen">
<code class="descname">frozen</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p><a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><code class="xref py py-class docutils literal"><span class="pre">TransformNode</span></code></a> is the base class for anything that
participates in the transform tree and needs to invalidate its
parents or be invalidated. This includes classes that are not
really transforms, such as bounding boxes, since some transforms
depend on bounding boxes to compute their values.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_contains">
<code class="descname">fully_contains</code><span class="sig-paren">(</span><em>x</em>, <em>y</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">x,</span> <span class="pre">y</span></code> is in the bounding box, but not on its edge.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_containsx">
<code class="descname">fully_containsx</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">x</span></code> is in the open (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><code class="xref py py-attr docutils literal"><span class="pre">x1</span></code></a>) interval.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_containsy">
<code class="descname">fully_containsy</code><span class="sig-paren">(</span><em>y</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <code class="xref py py-obj docutils literal"><span class="pre">y</span></code> is in the open (<a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a>) interval.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_overlaps">
<code class="descname">fully_overlaps</code><span class="sig-paren">(</span><em>other</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether this bounding box overlaps with the other bounding box,
not including the edges.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.get_points">
<code class="descname">get_points</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.get_points" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.height">
<code class="descname">height</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.height" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The height of the bounding box. It may be negative if
<a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><code class="xref py py-attr docutils literal"><span class="pre">y1</span></code></a> < <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><code class="xref py py-attr docutils literal"><span class="pre">y0</span></code></a>.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.BboxBase.intersection">
<em class="property">static </em><code class="descname">intersection</code><span class="sig-paren">(</span><em>bbox1</em>, <em>bbox2</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.intersection" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the intersection of the two bboxes or None
if they do not intersect.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.intervalx">
<code class="descname">intervalx</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.intervalx" title="matplotlib.transforms.BboxBase.intervalx"><code class="xref py py-attr docutils literal"><span class="pre">intervalx</span></code></a> is the pair of <em>x</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from left to right.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.intervaly">
<code class="descname">intervaly</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.intervaly" title="matplotlib.transforms.BboxBase.intervaly"><code class="xref py py-attr docutils literal"><span class="pre">intervaly</span></code></a> is the pair of <em>y</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from bottom to
top.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.inverse_transformed">
<code class="descname">inverse_transformed</code><span class="sig-paren">(</span><em>transform</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.inverse_transformed" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> object, statically transformed by
the inverse of the given transform.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.is_affine">
<code class="descname">is_affine</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.transforms.BboxBase.is_affine" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.is_bbox">
<code class="descname">is_bbox</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.transforms.BboxBase.is_bbox" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.is_unit">
<code class="descname">is_unit</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.is_unit" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-class docutils literal"><span class="pre">Bbox</span></code></a> is the unit bounding box
from (0, 0) to (1, 1).</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.max">
<code class="descname">max</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.max" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.max" title="matplotlib.transforms.BboxBase.max"><code class="xref py py-attr docutils literal"><span class="pre">max</span></code></a> is the top-right corner of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.min">
<code class="descname">min</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.min" title="Permalink to this definition">¶</a></dt>