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<div class="section" id="matplotlib-transforms">
<h1><code class="docutils literal notranslate"><span class="pre">matplotlib.transforms</span></code><a class="headerlink" href="#matplotlib-transforms" title="Permalink to this headline">¶</a></h1>
<div class="graphviz"><img src="../_images/inheritance-d2d4004311b41ca985cc56b00adff14efcf92f07.png" alt="Inheritance diagram of matplotlib.transforms, matplotlib.path" usemap="#inheritancedbde0cb62f" class="inheritance graphviz" /></div>
<map id="inheritancedbde0cb62f" name="inheritancedbde0cb62f">
<area shape="rect" id="node1" href="#matplotlib.transforms.Affine2D" target="_top" title="A mutable 2D affine transformation." alt="" coords="524,2,576,18"/>
<area shape="rect" id="node2" href="#matplotlib.transforms.Affine2DBase" target="_top" title="The base class of all 2D affine transformations." alt="" coords="395,110,472,126"/>
<area shape="rect" id="node5" href="#matplotlib.transforms.AffineDeltaTransform" target="_top" title="A transform wrapper for transforming displacements between pairs of points." alt="" coords="493,29,607,45"/>
<area shape="rect" id="node9" href="#matplotlib.transforms.BboxTransform" target="_top" title="`BboxTransform` linearly transforms points from one `Bbox` to another." alt="" coords="508,56,592,72"/>
<area shape="rect" id="node10" href="#matplotlib.transforms.BboxTransformFrom" target="_top" title="`BboxTransformFrom` linearly transforms points from a given `Bbox` to the" alt="" coords="496,83,604,99"/>
<area shape="rect" id="node11" href="#matplotlib.transforms.BboxTransformTo" target="_top" title="`BboxTransformTo` is a transformation that linearly transforms points from" alt="" coords="503,110,597,126"/>
<area shape="rect" id="node13" href="#matplotlib.transforms.BlendedAffine2D" target="_top" title="A "blended" transform uses one transform for the *x*-direction, and" alt="" coords="504,137,597,153"/>
<area shape="rect" id="node15" href="#matplotlib.transforms.CompositeAffine2D" target="_top" title="A composite transform formed by applying transform *a* then transform *b*." alt="" coords="498,163,603,179"/>
<area shape="rect" id="node17" href="#matplotlib.transforms.IdentityTransform" target="_top" title="A special class that does one thing, the identity transform, in a" alt="" coords="502,190,598,206"/>
<area shape="rect" id="node20" href="#matplotlib.transforms.ScaledTranslation" target="_top" title="A transformation that translates by *xt* and *yt*, after *xt* and *yt*" alt="" coords="502,217,598,233"/>
<area shape="rect" id="node3" href="#matplotlib.transforms.AffineBase" target="_top" title="The base class of all affine transformations of any number of dimensions." alt="" coords="267,110,330,126"/>
<area shape="rect" id="node4" href="#matplotlib.transforms.Transform" target="_top" title="The base class of all `TransformNode` instances that" alt="" coords="126,163,185,179"/>
<area shape="rect" id="node14" href="#matplotlib.transforms.BlendedGenericTransform" target="_top" title="A "blended" transform uses one transform for the *x*-direction, and" alt="" coords="229,137,368,153"/>
<area shape="rect" id="node16" href="#matplotlib.transforms.CompositeGenericTransform" target="_top" title="A composite transform formed by applying transform *a* then" alt="" coords="224,163,373,179"/>
<area shape="rect" id="node21" href="#matplotlib.transforms.TransformWrapper" target="_top" title="A helper class that holds a single child transform and acts" alt="" coords="248,190,349,206"/>
<area shape="rect" id="node6" href="#matplotlib.transforms.Bbox" target="_top" title="A mutable bounding box." alt="" coords="281,217,316,233"/>
<area shape="rect" id="node7" href="#matplotlib.transforms.BboxBase" target="_top" title="The base class of all bounding boxes." alt="" coords="126,244,185,260"/>
<area shape="rect" id="node18" href="#matplotlib.transforms.LockableBbox" target="_top" title="A `Bbox` where some elements may be locked at certain values." alt="" coords="260,244,338,260"/>
<area shape="rect" id="node22" href="#matplotlib.transforms.TransformedBbox" target="_top" title="A `Bbox` that is automatically transformed by a given" alt="" coords="250,271,347,287"/>
<area shape="rect" id="node8" href="#matplotlib.transforms.TransformNode" target="_top" title="The base class for anything that participates in the transform tree" alt="" coords="2,244,87,260"/>
<area shape="rect" id="node24" href="#matplotlib.transforms.TransformedPath" target="_top" title="A `TransformedPath` caches a non-affine transformed copy of the" alt="" coords="109,284,202,300"/>
<area shape="rect" id="node12" href="#matplotlib.transforms.BboxTransformToMaxOnly" target="_top" title="`BboxTransformTo` is a transformation that linearly transforms points from" alt="" coords="629,110,766,126"/>
<area shape="rect" id="node19" href="path_api.html#matplotlib.path.Path" target="_top" title="A series of possibly disconnected, possibly closed, line and curve" alt="" coords="28,217,61,233"/>
<area shape="rect" id="node23" href="#matplotlib.transforms.TransformedPatchPath" target="_top" title="A `TransformedPatchPath` caches a non-affine transformed copy of the" alt="" coords="239,298,359,314"/>
</map><span class="target" id="module-matplotlib.transforms"></span><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-obj docutils literal notranslate"><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 notranslate"><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="py 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><span class="n">matrix</span><span class="o">=</span><span class="default_value">None</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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="py method">
<dt id="matplotlib.transforms.Affine2D.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">matrix</span><span class="o">=</span><span class="default_value">None</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.__init__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.__init__" title="Permalink to this definition">¶</a></dt>
<dd><p>Initialize an Affine transform from a 3x3 numpy float array:</p>
<div class="highlight-default notranslate"><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>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.transforms.Affine2D.__module__">
<code class="descname">__module__</code><em class="property"> = 'matplotlib.transforms'</em><a class="headerlink" href="#matplotlib.transforms.Affine2D.__module__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.__str__">
<code class="descname">__str__</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.Affine2D.__str__" title="Permalink to this definition">¶</a></dt>
<dd><p>Return str(self).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.clear">
<code class="descname">clear</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.clear"><span class="viewcode-link">[source]</span></a><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="py method">
<dt id="matplotlib.transforms.Affine2D.from_values">
<em class="property">static </em><code class="descname">from_values</code><span class="sig-paren">(</span><em><span class="n">a</span></em>, <em><span class="n">b</span></em>, <em><span class="n">c</span></em>, <em><span class="n">d</span></em>, <em><span class="n">e</span></em>, <em><span class="n">f</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.from_values"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.from_values" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new Affine2D instance from the given values:</p>
<div class="highlight-default notranslate"><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="py method">
<dt id="matplotlib.transforms.Affine2D.get_matrix">
<code class="descname">get_matrix</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.get_matrix"><span class="viewcode-link">[source]</span></a><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 notranslate"><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="py method">
<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="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.identity"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.identity" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><code class="xref py py-obj docutils literal notranslate"><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-obj docutils literal notranslate"><span class="pre">IdentityTransform</span></code></a> class instead.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.rotate">
<code class="descname">rotate</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">theta</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.rotate"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.rotate_around">
<code class="descname">rotate_around</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">x</span></em>, <em><span class="n">y</span></em>, <em><span class="n">theta</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.rotate_around"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg">
<code class="descname">rotate_deg</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">degrees</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.rotate_deg"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg_around">
<code class="descname">rotate_deg_around</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">x</span></em>, <em><span class="n">y</span></em>, <em><span class="n">degrees</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.rotate_deg_around"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.scale">
<code class="descname">scale</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">sx</span></em>, <em><span class="n">sy</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.scale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Add 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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.set">
<code class="descname">set</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">other</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.set"><span class="viewcode-link">[source]</span></a><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-obj docutils literal notranslate"><span class="pre">Affine2DBase</span></code></a> object.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.set_matrix">
<code class="descname">set_matrix</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">mtx</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.set_matrix"><span class="viewcode-link">[source]</span></a><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 notranslate"><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="py method">
<dt id="matplotlib.transforms.Affine2D.skew">
<code class="descname">skew</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">xShear</span></em>, <em><span class="n">yShear</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.skew"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.skew" title="Permalink to this definition">¶</a></dt>
<dd><p>Add 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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.skew_deg">
<code class="descname">skew_deg</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">xShear</span></em>, <em><span class="n">yShear</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.skew_deg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.skew_deg" title="Permalink to this definition">¶</a></dt>
<dd><p>Add 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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2D.translate">
<code class="descname">translate</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">tx</span></em>, <em><span class="n">ty</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2D.translate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2D.translate" title="Permalink to this definition">¶</a></dt>
<dd><p>Add 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 notranslate"><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 notranslate"><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 notranslate"><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 notranslate"><span class="pre">scale()</span></code></a>.</p>
</dd></dl>
</dd></dl>
<dl class="py 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><span class="o">*</span><span class="n">args</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2DBase"><span class="viewcode-link">[source]</span></a><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 notranslate"><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 notranslate"><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-obj docutils literal notranslate"><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 notranslate"><span class="pre">get_matrix()</span></code> that generates a custom 3x3 matrix.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.transforms.Affine2DBase.__module__">
<code class="descname">__module__</code><em class="property"> = 'matplotlib.transforms'</em><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.__module__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2DBase.frozen">
<code class="descname">frozen</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2DBase.frozen"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a frozen copy of this transform node. The frozen copy will not
be updated when its children change. Useful for storing a previously
known state of a transform where <code class="docutils literal notranslate"><span class="pre">copy.deepcopy()</span></code> might normally be
used.</p>
</dd></dl>
<dl class="py 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="py 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="py method">
<dt id="matplotlib.transforms.Affine2DBase.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2DBase.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</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>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2DBase.is_separable">
<em class="property">property </em><code class="descname">is_separable</code><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.is_separable" title="Permalink to this definition">¶</a></dt>
<dd><p>bool(x) -> bool</p>
<p>Returns True when the argument x is true, False otherwise.
The builtins True and False are the only two instances of the class bool.
The class bool is a subclass of the class int, and cannot be subclassed.</p>
</dd></dl>
<dl class="py 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="py method">
<dt id="matplotlib.transforms.Affine2DBase.to_values">
<code class="descname">to_values</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2DBase.to_values"><span class="viewcode-link">[source]</span></a><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 an <code class="docutils literal notranslate"><span class="pre">(a,</span> <span class="pre">b,</span> <span class="pre">c,</span> <span class="pre">d,</span> <span class="pre">e,</span> <span class="pre">f)</span></code> tuple.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Affine2DBase.transform_affine">
<code class="descname">transform_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">points</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Affine2DBase.transform_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the affine part of this transformation on the
given array of values.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><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 notranslate"><span class="pre">transform(values)</span></code>.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as 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 notranslate"><span class="pre">input_dims</span></code></a> or
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 notranslate"><span class="pre">input_dims</span></code></a>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as 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 notranslate"><span class="pre">input_dims</span></code></a> or
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 notranslate"><span class="pre">output_dims</span></code></a>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="py 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><span class="o">*</span><span class="n">args</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase"><span class="viewcode-link">[source]</span></a><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 notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<p>The base class of all affine transformations of any number of dimensions.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.__array__">
<code class="descname">__array__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="o">*</span><span class="n">args</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.__array__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.__array__" title="Permalink to this definition">¶</a></dt>
<dd><p>Array interface to get at this Transform's affine matrix.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.__eq__">
<code class="descname">__eq__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">other</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.__eq__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.__eq__" title="Permalink to this definition">¶</a></dt>
<dd><p>Return self==value.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.transforms.AffineBase.__hash__">
<code class="descname">__hash__</code><em class="property"> = None</em><a class="headerlink" href="#matplotlib.transforms.AffineBase.__hash__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="o">*</span><span class="n">args</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.__init__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.__init__" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.transforms.AffineBase.__module__">
<code class="descname">__module__</code><em class="property"> = 'matplotlib.transforms'</em><a class="headerlink" href="#matplotlib.transforms.AffineBase.__module__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.get_affine">
<code class="descname">get_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.get_affine"><span class="viewcode-link">[source]</span></a><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="py 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="py method">
<dt id="matplotlib.transforms.AffineBase.transform">
<code class="descname">transform</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">values</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply this transformation on the given array of <em>values</em>.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.transform_affine">
<code class="descname">transform_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">values</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the affine part of this transformation on the
given array of values.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><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 notranslate"><span class="pre">transform(values)</span></code>.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">points</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><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 notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code> or
shape (N x <code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.transform_path">
<code class="descname">transform_path</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">path</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform_path"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transform to <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a> <em>path</em>, returning a new <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a>.</p>
<p>In some cases, this transform may insert curves into the path
that began as line segments.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.transform_path_affine">
<code class="descname">transform_path_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">path</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform_path_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the affine part of this transform to <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a> <em>path</em>, returning a
new <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a>.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform_path(path)</span></code> is equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></code>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineBase.transform_path_non_affine">
<code class="descname">transform_path_non_affine</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">path</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineBase.transform_path_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the non-affine part of this transform to <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a> <em>path</em>,
returning a new <a class="reference internal" href="path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Path</span></code></a>.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform_path(path)</span></code> is equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></code>.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.transforms.AffineDeltaTransform">
<em class="property">class </em><code class="descclassname">matplotlib.transforms.</code><code class="descname">AffineDeltaTransform</code><span class="sig-paren">(</span><em><span class="n">transform</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineDeltaTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineDeltaTransform" 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 notranslate"><span class="pre">matplotlib.transforms.Affine2DBase</span></code></a></p>
<p>A transform wrapper for transforming displacements between pairs of points.</p>
<p>This class is intended to be used to transform displacements ("position
deltas") between pairs of points (e.g., as the <code class="docutils literal notranslate"><span class="pre">offset_transform</span></code>
of <a class="reference internal" href="collections_api.html#matplotlib.collections.Collection" title="matplotlib.collections.Collection"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Collection</span></code></a>s): given a transform <code class="docutils literal notranslate"><span class="pre">t</span></code> such that <code class="docutils literal notranslate"><span class="pre">t</span> <span class="pre">=</span>
<span class="pre">AffineDeltaTransform(t)</span> <span class="pre">+</span> <span class="pre">offset</span></code>, <code class="docutils literal notranslate"><span class="pre">AffineDeltaTransform</span></code>
satisfies <code class="docutils literal notranslate"><span class="pre">AffineDeltaTransform(a</span> <span class="pre">-</span> <span class="pre">b)</span> <span class="pre">==</span> <span class="pre">AffineDeltaTransform(a)</span> <span class="pre">-</span>
<span class="pre">AffineDeltaTransform(b)</span></code>.</p>
<p>This is implemented by forcing the offset components of the transform
matrix to zero.</p>
<p>This class is experimental as of 3.3, and the API may change.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.transforms.AffineDeltaTransform.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">transform</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineDeltaTransform.__init__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineDeltaTransform.__init__" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.transforms.AffineDeltaTransform.__module__">
<code class="descname">__module__</code><em class="property"> = 'matplotlib.transforms'</em><a class="headerlink" href="#matplotlib.transforms.AffineDeltaTransform.__module__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineDeltaTransform.__str__">
<code class="descname">__str__</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="headerlink" href="#matplotlib.transforms.AffineDeltaTransform.__str__" title="Permalink to this definition">¶</a></dt>
<dd><p>Return str(self).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.AffineDeltaTransform.get_matrix">
<code class="descname">get_matrix</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#AffineDeltaTransform.get_matrix"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.AffineDeltaTransform.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the matrix for the affine part of this transform.</p>
</dd></dl>
</dd></dl>
<dl class="py 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><span class="n">points</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox"><span class="viewcode-link">[source]</span></a><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 notranslate"><span class="pre">matplotlib.transforms.BboxBase</span></code></a></p>
<p>A mutable bounding box.</p>
<p class="rubric">Examples</p>
<p><strong>Create from known bounds</strong></p>
<p>The default constructor takes the boundary "points" <code class="docutils literal notranslate"><span class="pre">[[xmin,</span> <span class="pre">ymin],</span>
<span class="pre">[xmax,</span> <span class="pre">ymax]]</span></code>.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">7</span><span class="p">]])</span>
<span class="go">Bbox([[1.0, 1.0], [3.0, 7.0]])</span>
</pre></div>
</div>
<p>Alternatively, a Bbox can be created from the flattened points array, the
so-called "extents" <code class="docutils literal notranslate"><span class="pre">(xmin,</span> <span class="pre">ymin,</span> <span class="pre">xmax,</span> <span class="pre">ymax)</span></code></p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">from_extents</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">7</span><span class="p">)</span>
<span class="go">Bbox([[1.0, 1.0], [3.0, 7.0]])</span>
</pre></div>
</div>
<p>or from the "bounds" <code class="docutils literal notranslate"><span class="pre">(xmin,</span> <span class="pre">ymin,</span> <span class="pre">width,</span> <span class="pre">height)</span></code>.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">from_bounds</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">6</span><span class="p">)</span>
<span class="go">Bbox([[1.0, 1.0], [3.0, 7.0]])</span>
</pre></div>
</div>
<p><strong>Create from collections of points</strong></p>
<p>The "empty" object for accumulating Bboxs is the null bbox, which is a
stand-in for the empty set.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">()</span>
<span class="go">Bbox([[inf, inf], [-inf, -inf]])</span>
</pre></div>
</div>
<p>Adding points to the null bbox will give you the bbox of those points.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">box</span> <span class="o">=</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">box</span><span class="o">.</span><span class="n">update_from_data_xy</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">box</span>
<span class="go">Bbox([[1.0, 1.0], [1.0, 1.0]])</span>
<span class="gp">>>> </span><span class="n">box</span><span class="o">.</span><span class="n">update_from_data_xy</span><span class="p">([[</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">]],</span> <span class="n">ignore</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">box</span>
<span class="go">Bbox([[1.0, 1.0], [3.0, 3.0]])</span>
</pre></div>
</div>
<p>Setting <code class="docutils literal notranslate"><span class="pre">ignore=True</span></code> is equivalent to starting over from a null bbox.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">box</span><span class="o">.</span><span class="n">update_from_data_xy</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">]],</span> <span class="n">ignore</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">box</span>
<span class="go">Bbox([[1.0, 1.0], [1.0, 1.0]])</span>
</pre></div>
</div>
<div class="admonition warning">
<p class="first admonition-title">Warning</p>
<p class="last">It is recommended to always specify <code class="docutils literal notranslate"><span class="pre">ignore</span></code> explicitly. If not, the
default value of <code class="docutils literal notranslate"><span class="pre">ignore</span></code> can be changed at any time by code with
access to your Bbox, for example using the method <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ignore</span></code></a>.</p>
</div>
<p><strong>Properties of the ``null`` bbox</strong></p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">The current behavior of <a class="reference internal" href="#matplotlib.transforms.Bbox.null" title="matplotlib.transforms.Bbox.null"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Bbox.null()</span></code></a> may be surprising as it does
not have all of the properties of the "empty set", and as such does
not behave like a "zero" object in the mathematical sense. We may
change that in the future (with a deprecation period).</p>
</div>
<p>The null bbox is the identity for intersections</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">Bbox</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">7</span><span class="p">]]),</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">())</span>
<span class="go">Bbox([[1.0, 1.0], [3.0, 7.0]])</span>
</pre></div>
</div>
<p>except with itself, where it returns the full space.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">intersection</span><span class="p">(</span><span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">(),</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">())</span>
<span class="go">Bbox([[-inf, -inf], [inf, inf]])</span>
</pre></div>
</div>
<p>A union containing null will always return the full space (not the other
set!)</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">Bbox</span><span class="o">.</span><span class="n">union</span><span class="p">([</span><span class="n">Bbox</span><span class="p">([[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]),</span> <span class="n">Bbox</span><span class="o">.</span><span class="n">null</span><span class="p">()])</span>
<span class="go">Bbox([[-inf, -inf], [inf, inf]])</span>
</pre></div>
</div>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>points</strong><span class="classifier">ndarray</span></dt><dd><p>A 2x2 numpy array of the form <code class="docutils literal notranslate"><span class="pre">[[x0,</span> <span class="pre">y0],</span> <span class="pre">[x1,</span> <span class="pre">y1]]</span></code>.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.__format__">
<code class="descname">__format__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">fmt</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.__format__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.__format__" title="Permalink to this definition">¶</a></dt>
<dd><p>Default object formatter.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.__init__">
<code class="descname">__init__</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">points</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.__init__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.__init__" title="Permalink to this definition">¶</a></dt>
<dd><table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>points</strong><span class="classifier">ndarray</span></dt><dd><p>A 2x2 numpy array of the form <code class="docutils literal notranslate"><span class="pre">[[x0,</span> <span class="pre">y0],</span> <span class="pre">[x1,</span> <span class="pre">y1]]</span></code>.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.transforms.Bbox.__module__">
<code class="descname">__module__</code><em class="property"> = 'matplotlib.transforms'</em><a class="headerlink" href="#matplotlib.transforms.Bbox.__module__" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.__repr__">
<code class="descname">__repr__</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.__repr__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.__repr__" title="Permalink to this definition">¶</a></dt>
<dd><p>Return repr(self).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.__str__">
<code class="descname">__str__</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.__str__"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.__str__" title="Permalink to this definition">¶</a></dt>
<dd><p>Return str(self).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.bounds">
<em class="property">property </em><code class="descname">bounds</code><a class="headerlink" href="#matplotlib.transforms.Bbox.bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>Return (<a class="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><code class="xref py py-attr docutils literal notranslate"><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 notranslate"><span class="pre">y0</span></code></a>, <code class="xref py py-attr docutils literal notranslate"><span class="pre">width</span></code>, <code class="xref py py-attr docutils literal notranslate"><span class="pre">height</span></code>).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.from_bounds">
<em class="property">static </em><code class="descname">from_bounds</code><span class="sig-paren">(</span><em><span class="n">x0</span></em>, <em><span class="n">y0</span></em>, <em><span class="n">width</span></em>, <em><span class="n">height</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.from_bounds"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.from_bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-obj docutils literal notranslate"><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="py method">
<dt id="matplotlib.transforms.Bbox.from_extents">
<em class="property">static </em><code class="descname">from_extents</code><span class="sig-paren">(</span><em><span class="o">*</span><span class="n">args</span></em>, <em><span class="n">minpos</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.from_extents"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.from_extents" title="Permalink to this definition">¶</a></dt>
<dd><p>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>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>left, bottom, right, top</strong><span class="classifier">float</span></dt><dd><p>The four extents of the bounding box.</p>
</dd>
<dt><strong>minpos</strong><span class="classifier">float or None</span></dt><dd><p>If this is supplied, the Bbox will have a minimum positive value
set. This is useful when dealing with logarithmic scales and other
scales where negative bounds result in floating point errors.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.get_points">
<code class="descname">get_points</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.get_points"><span class="viewcode-link">[source]</span></a><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: <code class="docutils literal notranslate"><span class="pre">[[x0,</span> <span class="pre">y0],</span> <span class="pre">[x1,</span> <span class="pre">y1]]</span></code>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.ignore">
<code class="descname">ignore</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">value</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.ignore"><span class="viewcode-link">[source]</span></a><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 notranslate"><span class="pre">update_from_data_xy()</span></code></a>.</p>
<dl class="docutils">
<dt>value<span class="classifier">bool</span></dt><dd><ul class="simple">
<li>When <code class="docutils literal notranslate"><span class="pre">True</span></code>, 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 notranslate"><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-obj docutils literal notranslate"><span class="pre">Bbox</span></code></a>.</li>
<li>When <code class="docutils literal notranslate"><span class="pre">False</span></code>, 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 notranslate"><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-obj docutils literal notranslate"><span class="pre">Bbox</span></code></a>.</li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.intervalx">
<em class="property">property </em><code class="descname">intervalx</code><a class="headerlink" href="#matplotlib.transforms.Bbox.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>The pair of <em>x</em> coordinates that define the bounding box.</p>
<p>This is not guaranteed to be sorted from left to right.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.intervaly">
<em class="property">property </em><code class="descname">intervaly</code><a class="headerlink" href="#matplotlib.transforms.Bbox.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>The pair of <em>y</em> coordinates that define the bounding box.</p>
<p>This is not guaranteed to be sorted from bottom to top.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.minpos">
<em class="property">property </em><code class="descname">minpos</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minpos" title="Permalink to this definition">¶</a></dt>
<dd><p>The minimum positive value in both directions within the Bbox.</p>
<p>This is useful when dealing with logarithmic scales and other scales
where negative bounds result in floating point errors, and will be used
as the minimum extent instead of <em>p0</em>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.minposx">
<em class="property">property </em><code class="descname">minposx</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minposx" title="Permalink to this definition">¶</a></dt>
<dd><p>The minimum positive value in the <em>x</em>-direction within the Bbox.</p>
<p>This is useful when dealing with logarithmic scales and other scales
where negative bounds result in floating point errors, and will be used
as the minimum <em>x</em>-extent instead of <em>x0</em>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.minposy">
<em class="property">property </em><code class="descname">minposy</code><a class="headerlink" href="#matplotlib.transforms.Bbox.minposy" title="Permalink to this definition">¶</a></dt>
<dd><p>The minimum positive value in the <em>y</em>-direction within the Bbox.</p>
<p>This is useful when dealing with logarithmic scales and other scales
where negative bounds result in floating point errors, and will be used
as the minimum <em>y</em>-extent instead of <em>y0</em>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.mutated">
<code class="descname">mutated</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.mutated"><span class="viewcode-link">[source]</span></a><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="py method">
<dt id="matplotlib.transforms.Bbox.mutatedx">
<code class="descname">mutatedx</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.mutatedx"><span class="viewcode-link">[source]</span></a><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="py method">
<dt id="matplotlib.transforms.Bbox.mutatedy">
<code class="descname">mutatedy</code><span class="sig-paren">(</span><em><span class="n">self</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.mutatedy"><span class="viewcode-link">[source]</span></a><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="py method">
<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="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.null"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.null" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new null <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Bbox</span></code></a> from (inf, inf) to (-inf, -inf).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.p0">
<em class="property">property </em><code class="descname">p0</code><a class="headerlink" href="#matplotlib.transforms.Bbox.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>The first pair of (<em>x</em>, <em>y</em>) coordinates that define the bounding box.</p>
<p>This is not guaranteed to be the bottom-left corner (for that, use
<code class="xref py py-attr docutils literal notranslate"><span class="pre">min</span></code>).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.p1">
<em class="property">property </em><code class="descname">p1</code><a class="headerlink" href="#matplotlib.transforms.Bbox.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>The second pair of (<em>x</em>, <em>y</em>) coordinates that define the bounding box.</p>
<p>This is not guaranteed to be the top-right corner (for that, use
<code class="xref py py-attr docutils literal notranslate"><span class="pre">max</span></code>).</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.set">
<code class="descname">set</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">other</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.set"><span class="viewcode-link">[source]</span></a><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-obj docutils literal notranslate"><span class="pre">Bbox</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.transforms.Bbox.set_points">
<code class="descname">set_points</code><span class="sig-paren">(</span><em><span class="n">self</span></em>, <em><span class="n">points</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.set_points"><span class="viewcode-link">[source]</span></a><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: <code class="docutils literal notranslate"><span class="pre">[[x0,</span> <span class="pre">y0],</span> <span class="pre">[x1,</span> <span class="pre">y1]]</span></code>. No error checking is
performed, as this method is mainly for internal use.</p>
</dd></dl>
<dl class="py method">
<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="reference internal" href="../_modules/matplotlib/transforms.html#Bbox.unit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.transforms.Bbox.unit" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new unit <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Bbox</span></code></a> from (0, 0) to (1, 1).</p>
</dd></dl>