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<divid="unreleased-message"> You are reading an old version of the documentation (v2.1.2). For the latest version see <ahref="https://matplotlib.org/stable/api/transformations.html">https://matplotlib.org/stable/api/transformations.html</a></div>
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<spanid="matplotlib-transforms"></span><h2><aclass="reference internal" href="#module-matplotlib.transforms" title="matplotlib.transforms"><codeclass="xref py py-mod docutils literal"><spanclass="pre">matplotlib.transforms</span></code></a><aclass="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 <aclass="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><codeclass="xref py py-class docutils literal"><spanclass="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
<p>The backends are not expected to handle non-affine transformations
themselves.</p>
<dlclass="class">
<dtid="matplotlib.transforms.Affine2D">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">Affine2D</code><spanclass="sig-paren">(</span><em>matrix=None</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D" title="Permalink to this definition">¶</a></dt>
<p>If <em>matrix</em> is None, initialize with the identity transform.</p>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.clear">
<codeclass="descname">clear</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.clear" title="Permalink to this definition">¶</a></dt>
<dd><p>Reset the underlying matrix to the identity transform.</p>
<codeclass="descname">get_matrix</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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>
<emclass="property">static </em><codeclass="descname">identity</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.identity" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Return a new <aclass="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><codeclass="xref py py-class docutils literal"><spanclass="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 <aclass="reference internal" href="#matplotlib.transforms.IdentityTransform" title="matplotlib.transforms.IdentityTransform"><codeclass="xref py py-class docutils literal"><spanclass="pre">IdentityTransform</span></code></a> class instead.</p>
<codeclass="descname">is_separable</code><aclass="headerlink" href="#matplotlib.transforms.Affine2D.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.rotate">
<codeclass="descname">rotate</code><spanclass="sig-paren">(</span><em>theta</em><spanclass="sig-paren">)</span><aclass="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
<codeclass="descname">rotate_around</code><spanclass="sig-paren">(</span><em>x</em>, <em>y</em>, <em>theta</em><spanclass="sig-paren">)</span><aclass="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
<codeclass="descname">rotate_deg</code><spanclass="sig-paren">(</span><em>degrees</em><spanclass="sig-paren">)</span><aclass="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
<codeclass="descname">rotate_deg_around</code><spanclass="sig-paren">(</span><em>x</em>, <em>y</em>, <em>degrees</em><spanclass="sig-paren">)</span><aclass="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
and <aclass="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><codeclass="xref py py-meth docutils literal"><spanclass="pre">scale()</span></code></a>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.scale">
<codeclass="descname">scale</code><spanclass="sig-paren">(</span><em>sx</em>, <em>sy=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a scale in place.</p>
<p>If <em>sy</em> is None, the same scale is applied in both the <em>x</em>- and
<em>y</em>-directions.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
and <aclass="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><codeclass="xref py py-meth docutils literal"><spanclass="pre">scale()</span></code></a>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.set">
<codeclass="descname">set</code><spanclass="sig-paren">(</span><em>other</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Set this transformation from the frozen copy of another
<codeclass="descname">set_matrix</code><spanclass="sig-paren">(</span><em>mtx</em><spanclass="sig-paren">)</span><aclass="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>
<codeclass="descname">skew</code><spanclass="sig-paren">(</span><em>xShear</em>, <em>yShear</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.skew" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a skew in place.</p>
<p><em>xShear</em> and <em>yShear</em> are the shear angles along the <em>x</em>- and
<em>y</em>-axes, respectively, in radians.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
and <aclass="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><codeclass="xref py py-meth docutils literal"><spanclass="pre">scale()</span></code></a>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.skew_deg">
<codeclass="descname">skew_deg</code><spanclass="sig-paren">(</span><em>xShear</em>, <em>yShear</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.skew_deg" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a skew in place.</p>
<p><em>xShear</em> and <em>yShear</em> are the shear angles along the <em>x</em>- and
<em>y</em>-axes, respectively, in degrees.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
and <aclass="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><codeclass="xref py py-meth docutils literal"><spanclass="pre">scale()</span></code></a>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Affine2D.translate">
<codeclass="descname">translate</code><spanclass="sig-paren">(</span><em>tx</em>, <em>ty</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2D.translate" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a translation in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
and <aclass="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><codeclass="xref py py-meth docutils literal"><spanclass="pre">scale()</span></code></a>.</p>
</dd></dl>
</dd></dl>
<dlclass="class">
<dtid="matplotlib.transforms.Affine2DBase">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">Affine2DBase</code><spanclass="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">frozen</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a frozen copy of this transform node. The frozen copy
will not update when its children change. Useful for storing
a previously known state of a transform where
<codeclass="docutils literal"><spanclass="pre">copy.deepcopy()</span></code> might normally be used.</p>
<codeclass="descname">has_inverse</code><emclass="property"> = True</em><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.has_inverse" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">input_dims</code><emclass="property"> = 2</em><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.input_dims" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">inverted</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
<codeclass="descname">is_separable</code><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.is_separable" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">output_dims</code><emclass="property"> = 2</em><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.output_dims" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">to_values</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.to_values" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the values of the matrix as a sequence (a,b,c,d,e,f)</p>
<codeclass="descname">transform_affine</code><spanclass="sig-paren">(</span><em>points</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><codeclass="docutils literal"><spanclass="pre">transform(values)</span></code> is always equivalent to
<p>Accepts a numpy array of shape (N x <aclass="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">input_dims</span></code></a>) and
returns a numpy array of shape (N x <aclass="reference internal" href="#matplotlib.transforms.Affine2DBase.output_dims" title="matplotlib.transforms.Affine2DBase.output_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code></a>).</p>
<p>Alternatively, accepts a numpy array of length <aclass="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">input_dims</span></code></a>
and returns a numpy array of length <aclass="reference internal" href="#matplotlib.transforms.Affine2DBase.output_dims" title="matplotlib.transforms.Affine2DBase.output_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code></a>.</p>
<codeclass="descname">transform_point</code><spanclass="sig-paren">(</span><em>point</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_point" title="Permalink to this definition">¶</a></dt>
<dd><p>A convenience function that returns the transformed copy of a
single point.</p>
<p>The point is given as a sequence of length <aclass="reference internal" href="#matplotlib.transforms.Affine2DBase.input_dims" title="matplotlib.transforms.Affine2DBase.input_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">input_dims</span></code></a>.
The transformed point is returned as a sequence of length
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">AffineBase</code><spanclass="sig-paren">(</span><em>*args</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_affine</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.get_affine" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">is_affine</code><emclass="property"> = True</em><aclass="headerlink" href="#matplotlib.transforms.AffineBase.is_affine" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">transform</code><spanclass="sig-paren">(</span><em>values</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs the transformation on the given array of values.</p>
<p>Accepts a numpy array of shape (N x <codeclass="xref py py-attr docutils literal"><spanclass="pre">input_dims</span></code>) and
returns a numpy array of shape (N x <codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code>).</p>
<p>Alternatively, accepts a numpy array of length <codeclass="xref py py-attr docutils literal"><spanclass="pre">input_dims</span></code>
and returns a numpy array of length <codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code>.</p>
<codeclass="descname">transform_affine</code><spanclass="sig-paren">(</span><em>values</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><codeclass="docutils literal"><spanclass="pre">transform(values)</span></code> is always equivalent to
<codeclass="descname">transform_non_affine</code><spanclass="sig-paren">(</span><em>points</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><codeclass="docutils literal"><spanclass="pre">transform(values)</span></code> is always equivalent to
<codeclass="descname">transform_path</code><spanclass="sig-paren">(</span><em>path</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform_path" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">transform_path_affine</code><spanclass="sig-paren">(</span><em>path</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a path, transformed only by the affine part of
<codeclass="descname">transform_path_non_affine</code><spanclass="sig-paren">(</span><em>path</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a path, transformed only by the non-affine
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">Bbox</code><spanclass="sig-paren">(</span><em>points</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox" title="Permalink to this definition">¶</a></dt>
<p><em>points</em>: a 2x2 numpy array of the form [[x0, y0], [x1, y1]]</p>
<p>If you need to create a <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> object from another form
of data, consider the static methods <aclass="reference internal" href="#matplotlib.transforms.Bbox.unit" title="matplotlib.transforms.Bbox.unit"><codeclass="xref py py-meth docutils literal"><spanclass="pre">unit()</span></code></a>,
<emclass="property">static </em><codeclass="descname">from_bounds</code><spanclass="sig-paren">(</span><em>x0</em>, <em>y0</em>, <em>width</em>, <em>height</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.from_bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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>
<dlclass="staticmethod">
<dtid="matplotlib.transforms.Bbox.from_extents">
<emclass="property">static </em><codeclass="descname">from_extents</code><spanclass="sig-paren">(</span><em>*args</em><spanclass="sig-paren">)</span><aclass="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>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.get_points">
<codeclass="descname">get_points</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.ignore">
<codeclass="descname">ignore</code><spanclass="sig-paren">(</span><em>value</em><spanclass="sig-paren">)</span><aclass="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 <aclass="reference internal" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="matplotlib.transforms.Bbox.update_from_data_xy"><codeclass="xref py py-meth docutils literal"><spanclass="pre">update_from_data_xy()</span></code></a>.</p>
will ignore the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
will include the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
</ul>
</div></blockquote>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.intervalx">
<codeclass="descname">intervalx</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.intervalx" title="matplotlib.transforms.Bbox.intervalx"><codeclass="xref py py-attr docutils literal"><spanclass="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>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.intervaly">
<codeclass="descname">intervaly</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.intervaly" title="matplotlib.transforms.Bbox.intervaly"><codeclass="xref py py-attr docutils literal"><spanclass="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>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.minpos">
<codeclass="descname">minpos</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.minpos" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.minposx">
<codeclass="descname">minposx</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.minposx" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.minposy">
<codeclass="descname">minposy</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.minposy" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.mutated">
<codeclass="descname">mutated</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.mutatedx">
<codeclass="descname">mutatedx</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.mutatedy">
<codeclass="descname">mutatedy</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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>
<dlclass="staticmethod">
<dtid="matplotlib.transforms.Bbox.null">
<emclass="property">static </em><codeclass="descname">null</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.null" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new null <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> from (inf, inf) to
(-inf, -inf).</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.p0">
<codeclass="descname">p0</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.p0" title="matplotlib.transforms.Bbox.p0"><codeclass="xref py py-attr docutils literal"><spanclass="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 <codeclass="xref py py-attr docutils literal"><spanclass="pre">min</span></code>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.p1">
<codeclass="descname">p1</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.p1" title="matplotlib.transforms.Bbox.p1"><codeclass="xref py py-attr docutils literal"><spanclass="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 <codeclass="xref py py-attr docutils literal"><spanclass="pre">max</span></code>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Bbox.set">
<codeclass="descname">set</code><spanclass="sig-paren">(</span><em>other</em><spanclass="sig-paren">)</span><aclass="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
<codeclass="descname">set_points</code><spanclass="sig-paren">(</span><em>points</em><spanclass="sig-paren">)</span><aclass="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>
<dlclass="staticmethod">
<dtid="matplotlib.transforms.Bbox.unit">
<emclass="property">static </em><codeclass="descname">unit</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.unit" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new unit <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> from (0, 0) to
<codeclass="descname">update_from_data</code><spanclass="sig-paren">(</span><em>x</em>, <em>y</em>, <em>ignore=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.update_from_data" title="Permalink to this definition">¶</a></dt>
<dd><divclass="deprecated">
<p><spanclass="versionmodified">Deprecated since version 2.0: </span>The update_from_data function was deprecated in version 2.0. Use update_from_data_xy instead.</p>
</div>
<p>Update the bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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>
<dlclass="docutils">
<dt><em>ignore</em>:</dt>
<dd><ulclass="first last simple">
<li>when True, ignore the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <aclass="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><codeclass="xref py py-meth docutils literal"><spanclass="pre">ignore()</span></code></a>.</li>
<codeclass="descname">update_from_data_xy</code><spanclass="sig-paren">(</span><em>xy</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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>
<dlclass="docutils">
<dt><em>ignore</em>:</dt>
<dd><ulclass="first last simple">
<li>when True, ignore the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <aclass="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><codeclass="xref py py-meth docutils literal"><spanclass="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>
<codeclass="descname">update_from_path</code><spanclass="sig-paren">(</span><em>path</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Bbox.update_from_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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>
<li>when True, ignore the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when False, include the existing bounds of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.</li>
<li>when None, use the last value passed to <aclass="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><codeclass="xref py py-meth docutils literal"><spanclass="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>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.x0">
<codeclass="descname">x0</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.x0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x0</span></code></a> is the first of the pair of <em>x</em> coordinates that
define the bounding box. <aclass="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x0</span></code></a> is not guaranteed to be less than
<aclass="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x1</span></code></a>. If you require that, use <codeclass="xref py py-attr docutils literal"><spanclass="pre">xmin</span></code>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.x1">
<codeclass="descname">x1</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.x1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x1</span></code></a> is the second of the pair of <em>x</em> coordinates that
define the bounding box. <aclass="reference internal" href="#matplotlib.transforms.Bbox.x1" title="matplotlib.transforms.Bbox.x1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x1</span></code></a> is not guaranteed to be greater
than <aclass="reference internal" href="#matplotlib.transforms.Bbox.x0" title="matplotlib.transforms.Bbox.x0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x0</span></code></a>. If you require that, use <codeclass="xref py py-attr docutils literal"><spanclass="pre">xmax</span></code>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.y0">
<codeclass="descname">y0</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.y0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y0</span></code></a> is the first of the pair of <em>y</em> coordinates that
define the bounding box. <aclass="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y0</span></code></a> is not guaranteed to be less than
<aclass="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y1</span></code></a>. If you require that, use <codeclass="xref py py-attr docutils literal"><spanclass="pre">ymin</span></code>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.Bbox.y1">
<codeclass="descname">y1</code><aclass="headerlink" href="#matplotlib.transforms.Bbox.y1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y1</span></code></a> is the second of the pair of <em>y</em> coordinates that
define the bounding box. <aclass="reference internal" href="#matplotlib.transforms.Bbox.y1" title="matplotlib.transforms.Bbox.y1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y1</span></code></a> is not guaranteed to be greater
than <aclass="reference internal" href="#matplotlib.transforms.Bbox.y0" title="matplotlib.transforms.Bbox.y0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y0</span></code></a>. If you require that, use <codeclass="xref py py-attr docutils literal"><spanclass="pre">ymax</span></code>.</p>
</dd></dl>
</dd></dl>
<dlclass="class">
<dtid="matplotlib.transforms.BboxBase">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">BboxBase</code><spanclass="sig-paren">(</span><em>shorthand_name=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase" title="Permalink to this definition">¶</a></dt>
<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 <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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 <aclass="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><codeclass="xref py py-class docutils literal"><spanclass="pre">TransformNode</span></code></a>.</p>
<dlclass="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
<codeclass="docutils literal"><spanclass="pre">str(transform)</span></code> when DEBUG=True.</dd>
</dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.anchored">
<codeclass="descname">anchored</code><spanclass="sig-paren">(</span><em>c</em>, <em>container=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.anchored" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="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><ulclass="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
<aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> is positioned; it defaults to the initial
<codeclass="descname">contains</code><spanclass="sig-paren">(</span><em>x</em>, <em>y</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">x,</span><spanclass="pre">y</span></code> is in the bounding box or on its edge.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.containsx">
<codeclass="descname">containsx</code><spanclass="sig-paren">(</span><em>x</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">x</span></code> is in the closed (<aclass="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x0</span></code></a>, <aclass="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x1</span></code></a>) interval.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.containsy">
<codeclass="descname">containsy</code><spanclass="sig-paren">(</span><em>y</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">y</span></code> is in the closed (<aclass="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y0</span></code></a>, <aclass="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y1</span></code></a>) interval.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.corners">
<codeclass="descname">corners</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="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 <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> is defined by
the points (<em>a</em>, <em>b</em>) and (<em>c</em>, <em>d</em>), <aclass="reference internal" href="#matplotlib.transforms.BboxBase.corners" title="matplotlib.transforms.BboxBase.corners"><codeclass="xref py py-meth docutils literal"><spanclass="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>
<codeclass="descname">count_contains</code><spanclass="sig-paren">(</span><em>vertices</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.count_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Count the number of vertices contained in the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>.
Any vertices with a non-finite x or y value are ignored.</p>
<codeclass="descname">count_overlaps</code><spanclass="sig-paren">(</span><em>bboxes</em><spanclass="sig-paren">)</span><aclass="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 <aclass="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><codeclass="xref py py-class docutils literal"><spanclass="pre">BboxBase</span></code></a> objects</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.expanded">
<codeclass="descname">expanded</code><spanclass="sig-paren">(</span><em>sw</em>, <em>sh</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.expanded" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> which is this <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a>
expanded around its center by the given factors <em>sw</em> and
<em>sh</em>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.extents">
<codeclass="descname">extents</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.extents" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">frozen</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p><aclass="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><codeclass="xref py py-class docutils literal"><spanclass="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>
<codeclass="descname">fully_contains</code><spanclass="sig-paren">(</span><em>x</em>, <em>y</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.fully_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">x,</span><spanclass="pre">y</span></code> is in the bounding box, but not on its edge.</p>
<codeclass="descname">fully_containsx</code><spanclass="sig-paren">(</span><em>x</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">x</span></code> is in the open (<aclass="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x0</span></code></a>, <aclass="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">x1</span></code></a>) interval.</p>
<codeclass="descname">fully_containsy</code><spanclass="sig-paren">(</span><em>y</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether <codeclass="xref py py-obj docutils literal"><spanclass="pre">y</span></code> is in the open (<aclass="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y0</span></code></a>, <aclass="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><codeclass="xref py py-attr docutils literal"><spanclass="pre">y1</span></code></a>) interval.</p>
<codeclass="descname">fully_overlaps</code><spanclass="sig-paren">(</span><em>other</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.fully_overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether this bounding box overlaps with the other bounding box,
<codeclass="descname">get_points</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.get_points" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.height">
<codeclass="descname">height</code><aclass="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
<emclass="property">static </em><codeclass="descname">intersection</code><spanclass="sig-paren">(</span><em>bbox1</em>, <em>bbox2</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.intersection" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the intersection of the two bboxes or None
if they do not intersect.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.intervalx">
<codeclass="descname">intervalx</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.intervalx" title="matplotlib.transforms.BboxBase.intervalx"><codeclass="xref py py-attr docutils literal"><spanclass="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>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.intervaly">
<codeclass="descname">intervaly</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.intervaly" title="matplotlib.transforms.BboxBase.intervaly"><codeclass="xref py py-attr docutils literal"><spanclass="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
<codeclass="descname">inverse_transformed</code><spanclass="sig-paren">(</span><em>transform</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.inverse_transformed" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> object, statically transformed by
the inverse of the given transform.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.is_affine">
<codeclass="descname">is_affine</code><emclass="property"> = True</em><aclass="headerlink" href="#matplotlib.transforms.BboxBase.is_affine" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.is_bbox">
<codeclass="descname">is_bbox</code><emclass="property"> = True</em><aclass="headerlink" href="#matplotlib.transforms.BboxBase.is_bbox" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.is_unit">
<codeclass="descname">is_unit</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.is_unit" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if the <aclass="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">Bbox</span></code></a> is the unit bounding box
from (0, 0) to (1, 1).</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.max">
<codeclass="descname">max</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.max" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.max" title="matplotlib.transforms.BboxBase.max"><codeclass="xref py py-attr docutils literal"><spanclass="pre">max</span></code></a> is the top-right corner of the bounding box.</p>