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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 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>
<divclass="highlight-python"><divclass="highlight"><pre>full transform == non-affine part + affine part
</pre></div>
</div>
<p>The backends are not expected to handle non-affine transformations
themselves.</p>
<dlclass="class">
<dtid="matplotlib.transforms.TransformNode">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">TransformNode</code><spanclass="sig-paren">(</span><em>shorthand_name=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformNode" title="Permalink to this definition">¶</a></dt>
<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>
<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>
<codeclass="descname">frozen</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformNode.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a frozen copy of this transform node. The frozen copy
will not update when its children change. Useful for storing
a previously known state of a transform where
<codeclass="docutils literal"><spanclass="pre">copy.deepcopy()</span></code> might normally be used.</p>
<codeclass="descname">invalidate</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformNode.invalidate" title="Permalink to this definition">¶</a></dt>
<dd><p>Invalidate this <aclass="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><codeclass="xref py py-class docutils literal"><spanclass="pre">TransformNode</span></code></a> and triggers an
invalidation of its ancestors. Should be called any
<codeclass="descname">pass_through</code><emclass="property"> = False</em><aclass="headerlink" href="#matplotlib.transforms.TransformNode.pass_through" title="Permalink to this definition">¶</a></dt>
<dd><p>If pass_through is True, all ancestors will always be
invalidated, even if ‘self’ is already invalid.</p>
<codeclass="descname">set_children</code><spanclass="sig-paren">(</span><em>*children</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformNode.set_children" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the children of the transform, to let the invalidation
system know which transforms can invalidate this transform.
Should be called from the constructor of any transforms that
depend on other transforms.</p>
</dd></dl>
</dd></dl>
<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 <em>True</em> if (<em>x</em>, <em>y</em>) is a coordinate inside 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 True if <em>x</em> is between or equal to <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> and
<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 True if <em>y</em> is between or equal to <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> and
<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>.</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 True if (<em>x</em>, <em>y</em>) is a coordinate inside the bounding
<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 True if <em>x</em> is between but not equal to <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> and
<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 True if <em>y</em> is between but not equal to <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> and
<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 True if this bounding box overlaps with the given
bounding box <em>other</em>, but not on its edge alone.</p>
</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
<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="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>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.min">
<codeclass="descname">min</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.min" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><codeclass="xref py py-attr docutils literal"><spanclass="pre">min</span></code></a> is the bottom-left corner of the bounding
box.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.overlaps">
<codeclass="descname">overlaps</code><spanclass="sig-paren">(</span><em>other</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if this bounding box overlaps with the given
bounding box <em>other</em>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.p0">
<codeclass="descname">p0</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.p0" title="matplotlib.transforms.BboxBase.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 <aclass="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><codeclass="xref py py-attr docutils literal"><spanclass="pre">min</span></code></a>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.p1">
<codeclass="descname">p1</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.p1" title="matplotlib.transforms.BboxBase.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 <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>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.padded">
<codeclass="descname">padded</code><spanclass="sig-paren">(</span><em>p</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.padded" 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> that is padded on all four sides by
the given value.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.rotated">
<codeclass="descname">rotated</code><spanclass="sig-paren">(</span><em>radians</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.rotated" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new bounding box that bounds a rotated version of
this bounding box by the given radians. The new bounding box
is still aligned with the axes, of course.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.shrunk">
<codeclass="descname">shrunk</code><spanclass="sig-paren">(</span><em>mx</em>, <em>my</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.shrunk" 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>, shrunk by the factor <em>mx</em>
in the <em>x</em> direction and the factor <em>my</em> in the <em>y</em> direction.
The lower left corner of the box remains unchanged. Normally
<em>mx</em> and <em>my</em> will be less than 1, but this is not enforced.</p>
<codeclass="descname">shrunk_to_aspect</code><spanclass="sig-paren">(</span><em>box_aspect</em>, <em>container=None</em>, <em>fig_aspect=1.0</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.shrunk_to_aspect" 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>, shrunk so that it is as
large as it can be while having the desired aspect ratio,
<em>box_aspect</em>. If the box coordinates are relative—that
is, fractions of a larger box such as a figure—then the
physical aspect ratio of that figure is specified with
<em>fig_aspect</em>, so that <em>box_aspect</em> can also be given as a
ratio of the absolute dimensions, not the relative dimensions.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.size">
<codeclass="descname">size</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.size" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width and height of the bounding box. May be negative,
in the same way as <aclass="reference internal" href="#matplotlib.transforms.BboxBase.width" title="matplotlib.transforms.BboxBase.width"><codeclass="xref py py-attr docutils literal"><spanclass="pre">width</span></code></a> and <aclass="reference internal" href="#matplotlib.transforms.BboxBase.height" title="matplotlib.transforms.BboxBase.height"><codeclass="xref py py-attr docutils literal"><spanclass="pre">height</span></code></a>.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.splitx">
<codeclass="descname">splitx</code><spanclass="sig-paren">(</span><em>*args</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.splitx" title="Permalink to this definition">¶</a></dt>
<p>Returns a list of 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> objects formed by
splitting the original one with vertical lines at fractional
positions <em>f1</em>, <em>f2</em>, ...</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.BboxBase.splity">
<codeclass="descname">splity</code><spanclass="sig-paren">(</span><em>*args</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.splity" title="Permalink to this definition">¶</a></dt>
<p>Returns a list of 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> objects formed by
splitting the original one with horizontal lines at fractional
<codeclass="descname">transformed</code><spanclass="sig-paren">(</span><em>transform</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.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
<codeclass="descname">translated</code><spanclass="sig-paren">(</span><em>tx</em>, <em>ty</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.translated" 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>, statically translated by
<em>tx</em> and <em>ty</em>.</p>
</dd></dl>
<dlclass="staticmethod">
<dtid="matplotlib.transforms.BboxBase.union">
<emclass="property">static </em><codeclass="descname">union</code><spanclass="sig-paren">(</span><em>bboxes</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.BboxBase.union" title="Permalink to this definition">¶</a></dt>
<dd><p>Return 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> that contains all of the given bboxes.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.width">
<codeclass="descname">width</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.width" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width of the bounding box. It may be negative if
<codeclass="descname">x0</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.x0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the first of the pair of <em>x</em> coordinates that
define the bounding box. <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> is not guaranteed to be
less than <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>. If you require that, use <aclass="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><codeclass="xref py py-attr docutils literal"><spanclass="pre">xmin</span></code></a>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.x1">
<codeclass="descname">x1</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.x1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the second of the pair of <em>x</em> coordinates
that define the bounding box. <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> is not guaranteed to be
greater than <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>. If you require that, use <aclass="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><codeclass="xref py py-attr docutils literal"><spanclass="pre">xmax</span></code></a>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.xmax">
<codeclass="descname">xmax</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.xmax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><codeclass="xref py py-attr docutils literal"><spanclass="pre">xmax</span></code></a> is the right edge of the bounding box.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.xmin">
<codeclass="descname">xmin</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.xmin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><codeclass="xref py py-attr docutils literal"><spanclass="pre">xmin</span></code></a> is the left edge of the bounding box.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.y0">
<codeclass="descname">y0</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.y0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the first of the pair of <em>y</em> coordinates that
define the bounding box. <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> is not guaranteed to be
less than <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>. If you require that, use <aclass="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><codeclass="xref py py-attr docutils literal"><spanclass="pre">ymin</span></code></a>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.y1">
<codeclass="descname">y1</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.y1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <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> is the second of the pair of <em>y</em> coordinates
that define the bounding box. <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> is not guaranteed to be
greater than <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>. If you require that, use <aclass="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><codeclass="xref py py-attr docutils literal"><spanclass="pre">ymax</span></code></a>.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.ymax">
<codeclass="descname">ymax</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.ymax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><codeclass="xref py py-attr docutils literal"><spanclass="pre">ymax</span></code></a> is the top edge of the bounding box.</p>
</dd></dl>
<dlclass="attribute">
<dtid="matplotlib.transforms.BboxBase.ymin">
<codeclass="descname">ymin</code><aclass="headerlink" href="#matplotlib.transforms.BboxBase.ymin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <aclass="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><codeclass="xref py py-attr docutils literal"><spanclass="pre">ymin</span></code></a> is the bottom edge of the bounding box.</p>
</dd></dl>
</dd></dl>
<dlclass="class">
<dtid="matplotlib.transforms.Bbox">
<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" title="matplotlib.transforms.Bbox.update_from_data"><codeclass="xref py py-meth docutils literal"><spanclass="pre">update_from_data()</span></code></a> or
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="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="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><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>
</dd></dl>
<dlclass="class">
<dtid="matplotlib.transforms.TransformedBbox">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">TransformedBbox</code><spanclass="sig-paren">(</span><em>bbox</em>, <em>transform</em>, <em>**kwargs</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformedBbox" title="Permalink to this definition">¶</a></dt>
<p>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> that is automatically transformed by a given
transform. When either the child bounding box or transform
changes, the bounds of this bbox will update accordingly.</p>
<codeclass="descname">get_points</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.TransformedBbox.get_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the points of the bounding box directly as a numpy array
of the form: [[x0, y0], [x1, y1]].</p>
</dd></dl>
</dd></dl>
<dlclass="class">
<dtid="matplotlib.transforms.Transform">
<emclass="property">class </em><codeclass="descclassname">matplotlib.transforms.</code><codeclass="descname">Transform</code><spanclass="sig-paren">(</span><em>shorthand_name=None</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform" title="Permalink to this definition">¶</a></dt>
<p>The base class of all <aclass="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><codeclass="xref py py-class docutils literal"><spanclass="pre">TransformNode</span></code></a> instances that
actually perform a transformation.</p>
<p>All non-affine transformations should be subclasses of this class.
New affine transformations should be subclasses of
<codeclass="descname">contains_branch</code><spanclass="sig-paren">(</span><em>other</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.contains_branch" title="Permalink to this definition">¶</a></dt>
<dd><p>Return whether the given transform is a sub-tree of this transform.</p>
<p>This routine uses transform equality to identify sub-trees, therefore
in many situations it is object id which will be used.</p>
<p>For the case where the given transform represents the whole
<codeclass="descname">contains_branch_seperately</code><spanclass="sig-paren">(</span><em>other_transform</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.contains_branch_seperately" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns whether the given branch is a sub-tree of this transform on
each seperate dimension.</p>
<p>A common use for this method is to identify if a transform is a blended
transform containing an axes’ data transform. e.g.:</p>
<codeclass="descname">get_affine</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.get_affine" title="Permalink to this definition">¶</a></dt>
<codeclass="descname">get_matrix</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the Affine transformation array for the affine part
<codeclass="descname">has_inverse</code><emclass="property"> = False</em><aclass="headerlink" href="#matplotlib.transforms.Transform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd><p>True if this transform has a corresponding inverse transform.</p>
<codeclass="descname">input_dims</code><emclass="property"> = None</em><aclass="headerlink" href="#matplotlib.transforms.Transform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd><p>The number of input dimensions of this transform.
Must be overridden (with integers) in the subclass.</p>
</dd></dl>
<dlclass="method">
<dtid="matplotlib.transforms.Transform.inverted">
<codeclass="descname">inverted</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
<codeclass="descname">is_separable</code><emclass="property"> = False</em><aclass="headerlink" href="#matplotlib.transforms.Transform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd><p>True if this transform is separable in the x- and y- dimensions.</p>
<codeclass="descname">output_dims</code><emclass="property"> = None</em><aclass="headerlink" href="#matplotlib.transforms.Transform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd><p>The number of output dimensions of this transform.
Must be overridden (with integers) in the subclass.</p>
<codeclass="descname">transform</code><spanclass="sig-paren">(</span><em>values</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs the transformation on the given array of values.</p>
<p>Accepts a numpy array of shape (N x <aclass="reference internal" href="#matplotlib.transforms.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.output_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code></a>.</p>
<codeclass="descname">transform_affine</code><spanclass="sig-paren">(</span><em>values</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.output_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code></a>.</p>
<codeclass="descname">transform_angles</code><spanclass="sig-paren">(</span><em>angles</em>, <em>pts</em>, <em>radians=False</em>, <em>pushoff=1e-05</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform_angles" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs transformation on a set of angles anchored at
specific locations.</p>
<p>The <em>angles</em> must be a column vector (i.e., numpy array).</p>
<p>The <em>pts</em> must be a two-column numpy array of x,y positions
(angle transforms currently only work in 2D). This array must
have the same number of rows as <em>angles</em>.</p>
<dlclass="docutils">
<dt><em>radians</em> indicates whether or not input angles are given in</dt>
<dd>radians (True) or degrees (False; the default).</dd>
<dt><em>pushoff</em> is the distance to move away from <em>pts</em> for</dt>
<dd>determining transformed angles (see discussion of method
below).</dd>
</dl>
<p>The transformed angles are returned in an array with the same
size as <em>angles</em>.</p>
<p>The generic version of this method uses a very generic
algorithm that transforms <em>pts</em>, as well as locations very
close to <em>pts</em>, to find the angle in the transformed system.</p>
<codeclass="descname">transform_bbox</code><spanclass="sig-paren">(</span><em>bbox</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform_bbox" title="Permalink to this definition">¶</a></dt>
<dd><p>Transform the given bounding box.</p>
<p>Note, for smarter transforms including caching (a common
requirement for matplotlib figures), see <aclass="reference internal" href="#matplotlib.transforms.TransformedBbox" title="matplotlib.transforms.TransformedBbox"><codeclass="xref py py-class docutils literal"><spanclass="pre">TransformedBbox</span></code></a>.</p>
<codeclass="descname">transform_non_affine</code><spanclass="sig-paren">(</span><em>values</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><codeclass="docutils literal"><spanclass="pre">transform(values)</span></code> is always equivalent to
<p>In non-affine transformations, this is generally equivalent to
<codeclass="docutils literal"><spanclass="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <aclass="reference internal" href="#matplotlib.transforms.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.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.Transform.input_dims" title="matplotlib.transforms.Transform.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.Transform.output_dims" title="matplotlib.transforms.Transform.output_dims"><codeclass="xref py py-attr docutils literal"><spanclass="pre">output_dims</span></code></a>.</p>
<codeclass="descname">transform_path</code><spanclass="sig-paren">(</span><em>path</em><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.transforms.Transform.transform_path" title="Permalink to this definition">¶</a></dt>