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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>
<p class="graphviz">
<img src="../_images/inheritance-1f7a63972b94b74326d18d29408661a69a6a3811.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="533,4,584,21"/>
<area shape="rect" id="node2" href="#matplotlib.transforms.Affine2DBase" target="_top" title="The base class of all 2D affine transformations." alt="" coords="403,120,476,137"/>
<area shape="rect" id="node8" href="#matplotlib.transforms.BboxTransform" target="_top" title=":class:`BboxTransform` linearly transforms points from one" alt="" coords="519,37,598,54"/>
<area shape="rect" id="node9" href="#matplotlib.transforms.BboxTransformFrom" target="_top" title=":class:`BboxTransformFrom` linearly transforms points from a given" alt="" coords="508,70,608,87"/>
<area shape="rect" id="node10" href="#matplotlib.transforms.BboxTransformTo" target="_top" title=":class:`BboxTransformTo` is a transformation that linearly" alt="" coords="514,103,602,120"/>
<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="515,136,601,153"/>
<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="509,169,607,186"/>
<area shape="rect" id="node16" href="#matplotlib.transforms.IdentityTransform" target="_top" title="A special class that does on thing, the identity transform, in a" alt="" coords="514,203,603,220"/>
<area shape="rect" id="node18" href="#matplotlib.transforms.ScaledTranslation" target="_top" title="A transformation that translates by *xt* and *yt*, after *xt* and *yt*" alt="" coords="513,236,603,253"/>
<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="272,120,333,137"/>
<area shape="rect" id="node4" href="#matplotlib.transforms.Transform" target="_top" title="The base class of all :class:`TransformNode` instances that" alt="" coords="130,186,188,203"/>
<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="240,153,366,170"/>
<area shape="rect" id="node15" href="#matplotlib.transforms.CompositeGenericTransform" target="_top" title="A composite transform formed by applying transform *a* then" alt="" coords="235,186,371,203"/>
<area shape="rect" id="node19" href="#matplotlib.transforms.TransformWrapper" target="_top" title="A helper class that holds a single child transform and acts" alt="" coords="257,220,349,237"/>
<area shape="rect" id="node5" href="#matplotlib.transforms.Bbox" target="_top" title="A mutable bounding box." alt="" coords="279,253,327,270"/>
<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="130,253,188,270"/>
<area shape="rect" id="node20" href="#matplotlib.transforms.TransformedBbox" target="_top" title="A :class:`Bbox` that is automatically transformed by a given" alt="" coords="258,286,348,303"/>
<area shape="rect" id="node7" href="#matplotlib.transforms.TransformNode" target="_top" title=":class:`TransformNode` is the base class for anything that" alt="" coords="4,253,83,270"/>
<area shape="rect" id="node21" href="#matplotlib.transforms.TransformedPath" target="_top" title="A :class:`TransformedPath` caches a non-affine transformed copy of" alt="" coords="116,286,203,303"/>
<area shape="rect" id="node11" title=":class:`BboxTransformTo` is a transformation that linearly" alt="" coords="641,103,764,120"/>
<area shape="rect" id="node17" href="../api/path_api.html#matplotlib.path.Path" target="_top" title=":class:`Path` represents a series of possibly disconnected," alt="" coords="19,220,68,237"/>
</map>
</p>
<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-python"><div class="highlight"><pre>full transform == non-affine part + affine part
</pre></div>
</div>
<p>The backends are not expected to handle non-affine transformations
themselves.</p>
<dl class="class">
<dt id="matplotlib.transforms.TransformNode">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">TransformNode</code><span class="sig-paren">(</span><em>shorthand_name=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformNode" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <code class="xref py py-class docutils literal"><span class="pre">object</span></code></p>
<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>
<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.TransformNode.frozen">
<code class="descname">frozen</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformNode.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="method">
<dt id="matplotlib.transforms.TransformNode.invalidate">
<code class="descname">invalidate</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformNode.invalidate" title="Permalink to this definition">¶</a></dt>
<dd><p>Invalidate this <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> and triggers an
invalidation of its ancestors. Should be called any
time the transform changes.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.TransformNode.pass_through">
<code class="descname">pass_through</code><em class="property"> = False</em><a class="headerlink" href="#matplotlib.transforms.TransformNode.pass_through" title="Permalink to this definition">¶</a></dt>
<dd><p>If pass_through is True, all ancestors will always be
invalidated, even if ‘self’ is already invalid.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformNode.set_children">
<code class="descname">set_children</code><span class="sig-paren">(</span><em>*children</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformNode.set_children" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the children of the transform, to let the invalidation
system know which transforms can invalidate this transform.
Should be called from the constructor of any transforms that
depend on other transforms.</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="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 <em>True</em> if (<em>x</em>, <em>y</em>) is a coordinate inside 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 True if <em>x</em> is between or equal to <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> and
<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>.</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 True if <em>y</em> is between or equal to <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> and
<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.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>.</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 True if (<em>x</em>, <em>y</em>) is a coordinate inside 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 True if <em>x</em> is between but not equal to <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> and
<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>.</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 True if <em>y</em> is between but not equal to <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> and
<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.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 True if this bounding box overlaps with the given
bounding box <em>other</em>, but not on its edge alone.</p>
</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>
<p>Implements the algorithm described at:</p>
<blockquote>
<div><a class="reference external" href="http://www.tekpool.com/node/2687">http://www.tekpool.com/node/2687</a></div></blockquote>
</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="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>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><code class="xref py py-attr docutils literal"><span class="pre">min</span></code></a> is the bottom-left corner of the bounding
box.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.overlaps">
<code class="descname">overlaps</code><span class="sig-paren">(</span><em>other</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if this bounding box overlaps with the given
bounding box <em>other</em>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.p0">
<code class="descname">p0</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.p0" title="matplotlib.transforms.BboxBase.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 <a class="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><code class="xref py py-attr docutils literal"><span class="pre">min</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.p1">
<code class="descname">p1</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.p1" title="matplotlib.transforms.BboxBase.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 <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>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.padded">
<code class="descname">padded</code><span class="sig-paren">(</span><em>p</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.padded" 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> that is padded on all four sides by
the given value.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.rotated">
<code class="descname">rotated</code><span class="sig-paren">(</span><em>radians</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.rotated" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new bounding box that bounds a rotated version of
this bounding box by the given radians. The new bounding box
is still aligned with the axes, of course.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.shrunk">
<code class="descname">shrunk</code><span class="sig-paren">(</span><em>mx</em>, <em>my</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.shrunk" 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>, shrunk by the factor <em>mx</em>
in the <em>x</em> direction and the factor <em>my</em> in the <em>y</em> direction.
The lower left corner of the box remains unchanged. Normally
<em>mx</em> and <em>my</em> will be less than 1, but this is not enforced.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.shrunk_to_aspect">
<code class="descname">shrunk_to_aspect</code><span class="sig-paren">(</span><em>box_aspect</em>, <em>container=None</em>, <em>fig_aspect=1.0</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.shrunk_to_aspect" 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>, shrunk so that it is as
large as it can be while having the desired aspect ratio,
<em>box_aspect</em>. If the box coordinates are relative—that
is, fractions of a larger box such as a figure—then the
physical aspect ratio of that figure is specified with
<em>fig_aspect</em>, so that <em>box_aspect</em> can also be given as a
ratio of the absolute dimensions, not the relative dimensions.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.size">
<code class="descname">size</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.size" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width and height of the bounding box. May be negative,
in the same way as <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> and <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="method">
<dt id="matplotlib.transforms.BboxBase.splitx">
<code class="descname">splitx</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.splitx" title="Permalink to this definition">¶</a></dt>
<dd><p>e.g., <code class="docutils literal"><span class="pre">bbox.splitx(f1,</span> <span class="pre">f2,</span> <span class="pre">...)</span></code></p>
<p>Returns a list of 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> objects formed by
splitting the original one with vertical lines at fractional
positions <em>f1</em>, <em>f2</em>, ...</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.splity">
<code class="descname">splity</code><span class="sig-paren">(</span><em>*args</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.splity" title="Permalink to this definition">¶</a></dt>
<dd><p>e.g., <code class="docutils literal"><span class="pre">bbox.splitx(f1,</span> <span class="pre">f2,</span> <span class="pre">...)</span></code></p>
<p>Returns a list of 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> objects formed by
splitting the original one with horizontal lines at fractional
positions <em>f1</em>, <em>f2</em>, ...</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.transformed">
<code class="descname">transformed</code><span class="sig-paren">(</span><em>transform</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.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 given transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.translated">
<code class="descname">translated</code><span class="sig-paren">(</span><em>tx</em>, <em>ty</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.translated" 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>, statically translated by
<em>tx</em> and <em>ty</em>.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.BboxBase.union">
<em class="property">static </em><code class="descname">union</code><span class="sig-paren">(</span><em>bboxes</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.BboxBase.union" title="Permalink to this definition">¶</a></dt>
<dd><p>Return 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> that contains all of the given bboxes.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.width">
<code class="descname">width</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.width" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width of the bounding box. It may be negative if
<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.x0" title="matplotlib.transforms.BboxBase.x0"><code class="xref py py-attr docutils literal"><span class="pre">x0</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.x0">
<code class="descname">x0</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.x0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the first of the pair of <em>x</em> coordinates that
define the bounding box. <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> is not guaranteed to be
less than <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>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><code class="xref py py-attr docutils literal"><span class="pre">xmin</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.x1">
<code class="descname">x1</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.x1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the second of the pair of <em>x</em> coordinates
that define the bounding box. <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> is not guaranteed to be
greater than <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>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><code class="xref py py-attr docutils literal"><span class="pre">xmax</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.xmax">
<code class="descname">xmax</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.xmax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><code class="xref py py-attr docutils literal"><span class="pre">xmax</span></code></a> is the right edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.xmin">
<code class="descname">xmin</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.xmin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><code class="xref py py-attr docutils literal"><span class="pre">xmin</span></code></a> is the left edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.y0">
<code class="descname">y0</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.y0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the first of the pair of <em>y</em> coordinates that
define the bounding box. <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> is not guaranteed to be
less than <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>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><code class="xref py py-attr docutils literal"><span class="pre">ymin</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.y1">
<code class="descname">y1</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.y1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the second of the pair of <em>y</em> coordinates
that define the bounding box. <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> is not guaranteed to be
greater than <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>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><code class="xref py py-attr docutils literal"><span class="pre">ymax</span></code></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.ymax">
<code class="descname">ymax</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.ymax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><code class="xref py py-attr docutils literal"><span class="pre">ymax</span></code></a> is the top edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.ymin">
<code class="descname">ymin</code><a class="headerlink" href="#matplotlib.transforms.BboxBase.ymin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><code class="xref py py-attr docutils literal"><span class="pre">ymin</span></code></a> is the bottom edge of the bounding box.</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="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" title="matplotlib.transforms.Bbox.update_from_data"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data()</span></code></a> or
<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" title="matplotlib.transforms.Bbox.update_from_data"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data()</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" title="matplotlib.transforms.Bbox.update_from_data"><code class="xref py py-meth docutils literal"><span class="pre">update_from_data()</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="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="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><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="../api/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>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.TransformedBbox">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">TransformedBbox</code><span class="sig-paren">(</span><em>bbox</em>, <em>transform</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformedBbox" 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 <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> that is automatically transformed by a given
transform. When either the child bounding box or transform
changes, the bounds of this bbox will update accordingly.</p>
<p><em>bbox</em>: a child <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>
<p><em>transform</em>: a 2D <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal"><span class="pre">Transform</span></code></a></p>
<dl class="method">
<dt id="matplotlib.transforms.TransformedBbox.get_points">
<code class="descname">get_points</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.TransformedBbox.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>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Transform">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">Transform</code><span class="sig-paren">(</span><em>shorthand_name=None</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform" 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>The base class of all <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> instances that
actually perform a transformation.</p>
<p>All non-affine transformations should be subclasses of this class.
New affine transformations should be subclasses of
<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 should override the following members (at
minimum):</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference internal" href="#matplotlib.transforms.Transform.input_dims" title="matplotlib.transforms.Transform.input_dims"><code class="xref py py-attr docutils literal"><span class="pre">input_dims</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.output_dims" title="matplotlib.transforms.Transform.output_dims"><code class="xref py py-attr docutils literal"><span class="pre">output_dims</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.transform" title="matplotlib.transforms.Transform.transform"><code class="xref py py-meth docutils literal"><span class="pre">transform()</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.is_separable" title="matplotlib.transforms.Transform.is_separable"><code class="xref py py-attr docutils literal"><span class="pre">is_separable</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.has_inverse" title="matplotlib.transforms.Transform.has_inverse"><code class="xref py py-attr docutils literal"><span class="pre">has_inverse</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.inverted" title="matplotlib.transforms.Transform.inverted"><code class="xref py py-meth docutils literal"><span class="pre">inverted()</span></code></a> (if <a class="reference internal" href="#matplotlib.transforms.Transform.has_inverse" title="matplotlib.transforms.Transform.has_inverse"><code class="xref py py-attr docutils literal"><span class="pre">has_inverse</span></code></a> is True)</li>
</ul>
</div></blockquote>
<p>If the transform needs to do something non-standard with
<a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-class docutils literal"><span class="pre">matplotlib.path.Path</span></code></a> objects, such as adding curves
where there were once line segments, it should override:</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference internal" href="#matplotlib.transforms.Transform.transform_path" title="matplotlib.transforms.Transform.transform_path"><code class="xref py py-meth docutils literal"><span class="pre">transform_path()</span></code></a></li>
</ul>
</div></blockquote>
<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.Transform.contains_branch">
<code class="descname">contains_branch</code><span class="sig-paren">(</span><em>other</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.contains_branch" title="Permalink to this definition">¶</a></dt>
<dd><p>Return whether the given transform is a sub-tree of this transform.</p>
<p>This routine uses transform equality to identify sub-trees, therefore
in many situations it is object id which will be used.</p>
<p>For the case where the given transform represents the whole
of this transform, returns True.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.contains_branch_seperately">
<code class="descname">contains_branch_seperately</code><span class="sig-paren">(</span><em>other_transform</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.contains_branch_seperately" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether the given branch is a sub-tree of this transform on
each seperate dimension.</p>
<p>A common use for this method is to identify if a transform is a blended
transform containing an axes’ data transform. e.g.:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">x_isdata</span><span class="p">,</span> <span class="n">y_isdata</span> <span class="o">=</span> <span class="n">trans</span><span class="o">.</span><span class="n">contains_branch_seperately</span><span class="p">(</span><span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">)</span>
</pre></div>
</div>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Transform.depth">
<code class="descname">depth</code><a class="headerlink" href="#matplotlib.transforms.Transform.depth" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns the number of transforms which have been chained
together to form this Transform instance.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">For the special case of a Composite transform, the maximum depth
of the two is returned.</p>
</div>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.get_affine">
<code class="descname">get_affine</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.get_matrix">
<code class="descname">get_matrix</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the Affine transformation array for the affine part
of this transform.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Transform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = False</em><a class="headerlink" href="#matplotlib.transforms.Transform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd><p>True if this transform has a corresponding inverse transform.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Transform.input_dims">
<code class="descname">input_dims</code><em class="property"> = None</em><a class="headerlink" href="#matplotlib.transforms.Transform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd><p>The number of input dimensions of this transform.
Must be overridden (with integers) in the subclass.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.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.Transform.is_separable">
<code class="descname">is_separable</code><em class="property"> = False</em><a class="headerlink" href="#matplotlib.transforms.Transform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd><p>True if this transform is separable in the x- and y- dimensions.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.Transform.output_dims">
<code class="descname">output_dims</code><em class="property"> = None</em><a class="headerlink" href="#matplotlib.transforms.Transform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd><p>The number of output dimensions of this transform.
Must be overridden (with integers) in the subclass.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.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.Transform.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 <a class="reference internal" href="#matplotlib.transforms.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.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.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.transform_angles">
<code class="descname">transform_angles</code><span class="sig-paren">(</span><em>angles</em>, <em>pts</em>, <em>radians=False</em>, <em>pushoff=1e-05</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.transform_angles" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs transformation on a set of angles anchored at
specific locations.</p>
<p>The <em>angles</em> must be a column vector (i.e., numpy array).</p>
<p>The <em>pts</em> must be a two-column numpy array of x,y positions
(angle transforms currently only work in 2D). This array must
have the same number of rows as <em>angles</em>.</p>
<dl class="docutils">
<dt><em>radians</em> indicates whether or not input angles are given in</dt>
<dd>radians (True) or degrees (False; the default).</dd>
<dt><em>pushoff</em> is the distance to move away from <em>pts</em> for</dt>
<dd>determining transformed angles (see discussion of method
below).</dd>
</dl>
<p>The transformed angles are returned in an array with the same
size as <em>angles</em>.</p>
<p>The generic version of this method uses a very generic
algorithm that transforms <em>pts</em>, as well as locations very
close to <em>pts</em>, to find the angle in the transformed system.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_bbox">
<code class="descname">transform_bbox</code><span class="sig-paren">(</span><em>bbox</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.transform_bbox" title="Permalink to this definition">¶</a></dt>
<dd><p>Transform the given bounding box.</p>
<p>Note, for smarter transforms including caching (a common
requirement for matplotlib figures), see <a class="reference internal" href="#matplotlib.transforms.TransformedBbox" title="matplotlib.transforms.TransformedBbox"><code class="xref py py-class docutils literal"><span class="pre">TransformedBbox</span></code></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em>values</em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Transform.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 <a class="reference internal" href="#matplotlib.transforms.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.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.Transform.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="../api/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>