<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>Working with transformations — Matplotlib v1.1.1 documentation</title>
<link rel="stylesheet" href="../_static/mpl.css" type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css" type="text/css" />
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../',
VERSION: '1.1.1',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true
};
</script>
<script type="text/javascript" src="../_static/jquery.js"></script>
<script type="text/javascript" src="../_static/underscore.js"></script>
<script type="text/javascript" src="../_static/doctools.js"></script>
<link rel="search" type="application/opensearchdescription+xml"
title="Search within Matplotlib v1.1.1 documentation"
href="../_static/opensearch.xml"/>
<link rel="top" title="Matplotlib v1.1.1 documentation" href="../index.html" />
<link rel="up" title="The Matplotlib Developers’ Guide" href="index.html" />
<link rel="next" title="Adding new scales and projections to matplotlib" href="add_new_projection.html" />
<link rel="prev" title="Doing a matplolib release" href="release_guide.html" />
</head>
<body>
<!-- Piwik -->
<script type="text/javascript">
if ("matplotlib.sourceforge.net" == document.location.hostname ||
"matplotlib.sf.net" == document.location.hostname) {
var pkBaseURL = (("https:" == document.location.protocol) ? "https://apps.sourceforge.net/piwik/matplotlib/" : "http://apps.sourceforge.net/piwik/matplotlib/");
document.write(unescape("%3Cscript src='" + pkBaseURL + "piwik.js' type='text/javascript'%3E%3C/script%3E"));
}
</script>
<script type="text/javascript">
if ("matplotlib.sourceforge.net" == document.location.hostname ||
"matplotlib.sf.net" == document.location.hostname) {
piwik_action_name = '';
piwik_idsite = 1;
piwik_url = pkBaseURL + "piwik.php";
piwik_log(piwik_action_name, piwik_idsite, piwik_url);
document.write(unescape('%3Cobject%3E%3Cnoscript%3E%3Cp%3E%3Cimg src="http://apps.sourceforge.net/piwik/matplotlib/piwik.php?idsite=1" alt="piwik"/%3E%3C/p%3E%3C/noscript%3E%3C/object%3E'));
}
</script>
<!-- End Piwik Tag -->
<link rel="shortcut icon" href="_static/favicon.ico">
<div style="background-color: white; text-align: left; padding: 10px 10px 15px 15px">
<a href="../index.html"><img src="../_static/logo2.png" border="0" alt="matplotlib"/></a>
</div>
<div class="related">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="../genindex.html" title="General Index"
accesskey="I">index</a></li>
<li class="right" >
<a href="../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="right" >
<a href="add_new_projection.html" title="Adding new scales and projections to matplotlib"
accesskey="N">next</a> |</li>
<li class="right" >
<a href="release_guide.html" title="Doing a matplolib release"
accesskey="P">previous</a> |</li>
<li><a href="../index.html">home</a>| </li>
<li><a href="../search.html">search</a>| </li>
<li><a href="../examples/index.html">examples</a>| </li>
<li><a href="../gallery.html">gallery</a>| </li>
<li><a href="../contents.html">docs</a> »</li>
<li><a href="index.html" accesskey="U">The Matplotlib Developers’ Guide</a> »</li>
</ul>
</div>
<div class="sphinxsidebar">
<div class="sphinxsidebarwrapper">
<h3><a href="../contents.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">Working with transformations</a><ul>
<li><a class="reference internal" href="#module-matplotlib.transforms"><tt class="docutils literal"><span class="pre">matplotlib.transforms</span></tt></a></li>
</ul>
</li>
</ul>
<h4>Previous topic</h4>
<p class="topless"><a href="release_guide.html"
title="previous chapter">Doing a matplolib release</a></p>
<h4>Next topic</h4>
<p class="topless"><a href="add_new_projection.html"
title="next chapter">Adding new scales and projections to matplotlib</a></p>
<h3>This Page</h3>
<ul class="this-page-menu">
<li><a href="../_sources/devel/transformations.txt"
rel="nofollow">Show Source</a></li>
</ul>
<div id="searchbox" style="display: none">
<h3>Quick search</h3>
<form class="search" action="../search.html" method="get">
<input type="text" name="q" size="18" />
<input type="submit" value="Go" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
<p class="searchtip" style="font-size: 90%">
Enter search terms or a module, class or function name.
</p>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body">
<div class="section" id="working-with-transformations">
<h1>Working with transformations<a class="headerlink" href="#working-with-transformations" title="Permalink to this headline">¶</a></h1>
<p class="graphviz">
digraph inheritancedbde0cb62f {
rankdir=LR;
size="8.0, 12.0";
"Transform" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.Transform",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"TransformNode" -> "Transform" [arrowsize=0.5,style="setlinewidth(0.5)"];
"Affine2DBase" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.Affine2DBase",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"AffineBase" -> "Affine2DBase" [arrowsize=0.5,style="setlinewidth(0.5)"];
"IdentityTransform" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.IdentityTransform",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "IdentityTransform" [arrowsize=0.5,style="setlinewidth(0.5)"];
"ScaledTranslation" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.ScaledTranslation",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "ScaledTranslation" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BboxTransformToMaxOnly" [shape=box,style="setlinewidth(0.5)",fontsize=10,fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25];
"BboxTransformTo" -> "BboxTransformToMaxOnly" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BboxTransformTo" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BboxTransformTo",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "BboxTransformTo" [arrowsize=0.5,style="setlinewidth(0.5)"];
"TransformWrapper" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.TransformWrapper",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Transform" -> "TransformWrapper" [arrowsize=0.5,style="setlinewidth(0.5)"];
"Bbox" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.Bbox",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"BboxBase" -> "Bbox" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BlendedGenericTransform" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BlendedGenericTransform",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Transform" -> "BlendedGenericTransform" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BlendedAffine2D" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BlendedAffine2D",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "BlendedAffine2D" [arrowsize=0.5,style="setlinewidth(0.5)"];
"TransformedBbox" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.TransformedBbox",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"BboxBase" -> "TransformedBbox" [arrowsize=0.5,style="setlinewidth(0.5)"];
"CompositeGenericTransform" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.CompositeGenericTransform",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Transform" -> "CompositeGenericTransform" [arrowsize=0.5,style="setlinewidth(0.5)"];
"Path" [style="setlinewidth(0.5)",URL="../api/path_api.html#matplotlib.path.Path",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2D" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.Affine2D",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "Affine2D" [arrowsize=0.5,style="setlinewidth(0.5)"];
"TransformedPath" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.TransformedPath",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"TransformNode" -> "TransformedPath" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BboxTransformFrom" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BboxTransformFrom",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "BboxTransformFrom" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BboxTransform" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BboxTransform",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "BboxTransform" [arrowsize=0.5,style="setlinewidth(0.5)"];
"BboxBase" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.BboxBase",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"TransformNode" -> "BboxBase" [arrowsize=0.5,style="setlinewidth(0.5)"];
"TransformNode" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.TransformNode",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"AffineBase" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.AffineBase",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Transform" -> "AffineBase" [arrowsize=0.5,style="setlinewidth(0.5)"];
"CompositeAffine2D" [style="setlinewidth(0.5)",URL="#matplotlib.transforms.CompositeAffine2D",fontname=Vera Sans, DejaVu Sans, Liberation Sans, Arial, Helvetica, sans,height=0.25,shape=box,fontsize=10];
"Affine2DBase" -> "CompositeAffine2D" [arrowsize=0.5,style="setlinewidth(0.5)"];
}
</p>
<div class="section" id="module-matplotlib.transforms">
<span id="matplotlib-transforms"></span><h2><a class="reference internal" href="#module-matplotlib.transforms" title="matplotlib.transforms"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.transforms</span></tt></a><a class="headerlink" href="#module-matplotlib.transforms" title="Permalink to this headline">¶</a></h2>
<p>matplotlib includes a framework for arbitrary geometric
transformations that is used determine the final position of all
elements drawn on the canvas.</p>
<p>Transforms are composed into trees of <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a> objects
whose actual value depends on their children. When the contents of
children change, their parents are automatically invalidated. The
next time an invalidated transform is accessed, it is recomputed to
reflect those changes. This invalidation/caching approach prevents
unnecessary recomputations of transforms, and contributes to better
interactive performance.</p>
<p>For example, here is a graph of the transform tree used to plot data
to the graph:</p>
<img alt="../_images/transforms.png" src="../_images/transforms.png" />
<p>The framework can be used for both affine and non-affine
transformations. However, for speed, we want use the backend
renderers to perform affine transformations whenever possible.
Therefore, it is possible to perform just the affine or non-affine
part of a transformation on a set of data. The affine is always
assumed to occur after the non-affine. For any transform:</p>
<div class="highlight-python"><pre>full transform == non-affine part + affine part</pre>
</div>
<p>The backends are not expected to handle non-affine transformations
themselves.</p>
<dl class="class">
<dt id="matplotlib.transforms.TransformNode">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">TransformNode</tt><a class="headerlink" href="#matplotlib.transforms.TransformNode" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <tt class="xref py py-class docutils literal"><span class="pre">object</span></tt></p>
<p><a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a> is the base class for anything that
participates in the transform tree and needs to invalidate its
parents or be invalidated. This includes classes that are not
really transforms, such as bounding boxes, since some transforms
depend on bounding boxes to compute their values.</p>
<p>Creates a new <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a>.</p>
<dl class="method">
<dt id="matplotlib.transforms.TransformNode.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformNode.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a frozen copy of this transform node. The frozen copy
will not update when its children change. Useful for storing
a previously known state of a transform where
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformNode.invalidate">
<tt class="descname">invalidate</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformNode.invalidate" title="Permalink to this definition">¶</a></dt>
<dd><p>Invalidate this <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a> and all of its
ancestors. Should be called any time the transform changes.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformNode.set_children">
<tt class="descname">set_children</tt><big>(</big><em>*children</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformNode.set_children" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the children of the transform, to let the invalidation
system know which transforms can invalidate this transform.
Should be called from the constructor of any transforms that
depend on other transforms.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BboxBase">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BboxBase</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.TransformNode</span></tt></a></p>
<p>This is the base class of all bounding boxes, and provides
read-only access to its data. A mutable bounding box is provided
by the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> class.</p>
<p>The canonical representation is as two points, with no
restrictions on their ordering. Convenience properties are
provided to get the left, bottom, right and top edges and width
and height, but these are not stored explicitly.</p>
<p>Creates a new <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a>.</p>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.anchored">
<tt class="descname">anchored</tt><big>(</big><em>c</em>, <em>container=None</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.anchored" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>, shifted to position <em>c</em>
within a container.</p>
<p><em>c</em>: may be either:</p>
<blockquote>
<div><ul class="simple">
<li>a sequence (<em>cx</em>, <em>cy</em>) where <em>cx</em> and <em>cy</em> range from 0
to 1, where 0 is left or bottom and 1 is right or top</li>
<li>a string:
- ‘C’ for centered
- ‘S’ for bottom-center
- ‘SE’ for bottom-left
- ‘E’ for left
- etc.</li>
</ul>
</div></blockquote>
<p>Optional argument <em>container</em> is the box within which the
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> is positioned; it defaults to the initial
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.bounds">
<tt class="descname">bounds</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) Returns (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.width" title="matplotlib.transforms.BboxBase.width"><tt class="xref py py-attr docutils literal"><span class="pre">width</span></tt></a>,
<a class="reference internal" href="#matplotlib.transforms.BboxBase.height" title="matplotlib.transforms.BboxBase.height"><tt class="xref py py-attr docutils literal"><span class="pre">height</span></tt></a>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.contains">
<tt class="descname">contains</tt><big>(</big><em>x</em>, <em>y</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns <em>True</em> if (<em>x</em>, <em>y</em>) is a coordinate inside the
bounding box or on its edge.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.containsx">
<tt class="descname">containsx</tt><big>(</big><em>x</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if <em>x</em> is between or equal to <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a> and
<a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.containsy">
<tt class="descname">containsy</tt><big>(</big><em>y</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if <em>y</em> is between or equal to <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a> and
<a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.corners">
<tt class="descname">corners</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.corners" title="Permalink to this definition">¶</a></dt>
<dd><p>Return an array of points which are the four corners of this
rectangle. For example, if this <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> is defined by
the points (<em>a</em>, <em>b</em>) and (<em>c</em>, <em>d</em>), <a class="reference internal" href="#matplotlib.transforms.BboxBase.corners" title="matplotlib.transforms.BboxBase.corners"><tt class="xref py py-meth docutils literal"><span class="pre">corners()</span></tt></a> returns
(<em>a</em>, <em>b</em>), (<em>a</em>, <em>d</em>), (<em>c</em>, <em>b</em>) and (<em>c</em>, <em>d</em>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.count_contains">
<tt class="descname">count_contains</tt><big>(</big><em>vertices</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.count_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Count the number of vertices contained in the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</p>
<p><em>vertices</em> is a Nx2 Numpy array.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.count_overlaps">
<tt class="descname">count_overlaps</tt><big>(</big><em>bboxes</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.count_overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Count the number of bounding boxes that overlap this one.</p>
<p>bboxes is a sequence of <a class="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><tt class="xref py py-class docutils literal"><span class="pre">BboxBase</span></tt></a> objects</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.expanded">
<tt class="descname">expanded</tt><big>(</big><em>sw</em>, <em>sh</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.expanded" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> which is this <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>
expanded around its center by the given factors <em>sw</em> and
<em>sh</em>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.extents">
<tt class="descname">extents</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.extents" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) Returns (<a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p><a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a> is the base class for anything that
participates in the transform tree and needs to invalidate its
parents or be invalidated. This includes classes that are not
really transforms, such as bounding boxes, since some transforms
depend on bounding boxes to compute their values.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_contains">
<tt class="descname">fully_contains</tt><big>(</big><em>x</em>, <em>y</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_contains" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if (<em>x</em>, <em>y</em>) is a coordinate inside the bounding
box, but not on its edge.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_containsx">
<tt class="descname">fully_containsx</tt><big>(</big><em>x</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsx" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if <em>x</em> is between but not equal to <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a> and
<a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_containsy">
<tt class="descname">fully_containsy</tt><big>(</big><em>y</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_containsy" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if <em>y</em> is between but not equal to <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a> and
<a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.fully_overlaps">
<tt class="descname">fully_overlaps</tt><big>(</big><em>other</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.fully_overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if this bounding box overlaps with the given
bounding box <em>other</em>, but not on its edge alone.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.height">
<tt class="descname">height</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.height" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The height of the bounding box. It may be negative if
<a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a> < <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.intervalx">
<tt class="descname">intervalx</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.intervalx" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.intervalx" title="matplotlib.transforms.BboxBase.intervalx"><tt class="xref py py-attr docutils literal"><span class="pre">intervalx</span></tt></a> is the pair of <em>x</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from left to
right.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.intervaly">
<tt class="descname">intervaly</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.intervaly" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.intervaly" title="matplotlib.transforms.BboxBase.intervaly"><tt class="xref py py-attr docutils literal"><span class="pre">intervaly</span></tt></a> is the pair of <em>y</em> coordinates that define
the bounding box. It is not guaranteed to be sorted from bottom to
top.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.inverse_transformed">
<tt class="descname">inverse_transformed</tt><big>(</big><em>transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.inverse_transformed" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> object, statically transformed by
the inverse of the given transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.is_unit">
<tt class="descname">is_unit</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.is_unit" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> is the unit bounding box
from (0, 0) to (1, 1).</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.max">
<tt class="descname">max</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.max" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.max" title="matplotlib.transforms.BboxBase.max"><tt class="xref py py-attr docutils literal"><span class="pre">max</span></tt></a> is the top-right corner of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.min">
<tt class="descname">min</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.min" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><tt class="xref py py-attr docutils literal"><span class="pre">min</span></tt></a> is the bottom-left corner of the bounding
box.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.overlaps">
<tt class="descname">overlaps</tt><big>(</big><em>other</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.overlaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if this bounding box overlaps with the given
bounding box <em>other</em>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.p0">
<tt class="descname">p0</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.p0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.p0" title="matplotlib.transforms.BboxBase.p0"><tt class="xref py py-attr docutils literal"><span class="pre">p0</span></tt></a> is the first pair of (<em>x</em>, <em>y</em>) coordinates that
define the bounding box. It is not guaranteed to be the bottom-left
corner. For that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.min" title="matplotlib.transforms.BboxBase.min"><tt class="xref py py-attr docutils literal"><span class="pre">min</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.p1">
<tt class="descname">p1</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.p1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.p1" title="matplotlib.transforms.BboxBase.p1"><tt class="xref py py-attr docutils literal"><span class="pre">p1</span></tt></a> is the second pair of (<em>x</em>, <em>y</em>) coordinates that
define the bounding box. It is not guaranteed to be the top-right
corner. For that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.max" title="matplotlib.transforms.BboxBase.max"><tt class="xref py py-attr docutils literal"><span class="pre">max</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.padded">
<tt class="descname">padded</tt><big>(</big><em>p</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.padded" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> that is padded on all four sides by
the given value.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.rotated">
<tt class="descname">rotated</tt><big>(</big><em>radians</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.rotated" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new bounding box that bounds a rotated version of
this bounding box by the given radians. The new bounding box
is still aligned with the axes, of course.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.shrunk">
<tt class="descname">shrunk</tt><big>(</big><em>mx</em>, <em>my</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.shrunk" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>, shrunk by the factor <em>mx</em>
in the <em>x</em> direction and the factor <em>my</em> in the <em>y</em> direction.
The lower left corner of the box remains unchanged. Normally
<em>mx</em> and <em>my</em> will be less than 1, but this is not enforced.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.shrunk_to_aspect">
<tt class="descname">shrunk_to_aspect</tt><big>(</big><em>box_aspect</em>, <em>container=None</em>, <em>fig_aspect=1.0</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.shrunk_to_aspect" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>, shrunk so that it is as
large as it can be while having the desired aspect ratio,
<em>box_aspect</em>. If the box coordinates are relative—that
is, fractions of a larger box such as a figure—then the
physical aspect ratio of that figure is specified with
<em>fig_aspect</em>, so that <em>box_aspect</em> can also be given as a
ratio of the absolute dimensions, not the relative dimensions.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.size">
<tt class="descname">size</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.size" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width and height of the bounding box. May be negative,
in the same way as <a class="reference internal" href="#matplotlib.transforms.BboxBase.width" title="matplotlib.transforms.BboxBase.width"><tt class="xref py py-attr docutils literal"><span class="pre">width</span></tt></a> and <a class="reference internal" href="#matplotlib.transforms.BboxBase.height" title="matplotlib.transforms.BboxBase.height"><tt class="xref py py-attr docutils literal"><span class="pre">height</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.splitx">
<tt class="descname">splitx</tt><big>(</big><em>*args</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.splitx" title="Permalink to this definition">¶</a></dt>
<dd><p>e.g., <tt class="docutils literal"><span class="pre">bbox.splitx(f1,</span> <span class="pre">f2,</span> <span class="pre">...)</span></tt></p>
<p>Returns a list of new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> objects formed by
splitting the original one with vertical lines at fractional
positions <em>f1</em>, <em>f2</em>, ...</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.splity">
<tt class="descname">splity</tt><big>(</big><em>*args</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.splity" title="Permalink to this definition">¶</a></dt>
<dd><p>e.g., <tt class="docutils literal"><span class="pre">bbox.splitx(f1,</span> <span class="pre">f2,</span> <span class="pre">...)</span></tt></p>
<p>Returns a list of new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> objects formed by
splitting the original one with horizontal lines at fractional
positions <em>f1</em>, <em>f2</em>, ...</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.transformed">
<tt class="descname">transformed</tt><big>(</big><em>transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.transformed" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> object, statically transformed by
the given transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BboxBase.translated">
<tt class="descname">translated</tt><big>(</big><em>tx</em>, <em>ty</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.translated" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>, statically translated by
<em>tx</em> and <em>ty</em>.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.BboxBase.union">
<em class="property">static </em><tt class="descname">union</tt><big>(</big><em>bboxes</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxBase.union" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> that contains all of the given bboxes.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.width">
<tt class="descname">width</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.width" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) The width of the bounding box. It may be negative if
<a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a> < <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.x0">
<tt class="descname">x0</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.x0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a> is the first of the pair of <em>x</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a> is not guaranteed to be
less than <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><tt class="xref py py-attr docutils literal"><span class="pre">xmin</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.x1">
<tt class="descname">x1</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.x1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a> is the second of the pair of <em>x</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.BboxBase.x1" title="matplotlib.transforms.BboxBase.x1"><tt class="xref py py-attr docutils literal"><span class="pre">x1</span></tt></a> is not guaranteed to be
greater than <a class="reference internal" href="#matplotlib.transforms.BboxBase.x0" title="matplotlib.transforms.BboxBase.x0"><tt class="xref py py-attr docutils literal"><span class="pre">x0</span></tt></a>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><tt class="xref py py-attr docutils literal"><span class="pre">xmax</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.xmax">
<tt class="descname">xmax</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.xmax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmax" title="matplotlib.transforms.BboxBase.xmax"><tt class="xref py py-attr docutils literal"><span class="pre">xmax</span></tt></a> is the right edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.xmin">
<tt class="descname">xmin</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.xmin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.xmin" title="matplotlib.transforms.BboxBase.xmin"><tt class="xref py py-attr docutils literal"><span class="pre">xmin</span></tt></a> is the left edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.y0">
<tt class="descname">y0</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.y0" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a> is the first of the pair of <em>y</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a> is not guaranteed to be
less than <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><tt class="xref py py-attr docutils literal"><span class="pre">ymin</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.y1">
<tt class="descname">y1</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.y1" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a> is the second of the pair of <em>y</em> coordinates that
define the bounding box. <a class="reference internal" href="#matplotlib.transforms.BboxBase.y1" title="matplotlib.transforms.BboxBase.y1"><tt class="xref py py-attr docutils literal"><span class="pre">y1</span></tt></a> is not guaranteed to be
greater than <a class="reference internal" href="#matplotlib.transforms.BboxBase.y0" title="matplotlib.transforms.BboxBase.y0"><tt class="xref py py-attr docutils literal"><span class="pre">y0</span></tt></a>. If you require that, use <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><tt class="xref py py-attr docutils literal"><span class="pre">ymax</span></tt></a>.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.ymax">
<tt class="descname">ymax</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.ymax" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymax" title="matplotlib.transforms.BboxBase.ymax"><tt class="xref py py-attr docutils literal"><span class="pre">ymax</span></tt></a> is the top edge of the bounding box.</p>
</dd></dl>
<dl class="attribute">
<dt id="matplotlib.transforms.BboxBase.ymin">
<tt class="descname">ymin</tt><a class="headerlink" href="#matplotlib.transforms.BboxBase.ymin" title="Permalink to this definition">¶</a></dt>
<dd><p>(property) <a class="reference internal" href="#matplotlib.transforms.BboxBase.ymin" title="matplotlib.transforms.BboxBase.ymin"><tt class="xref py py-attr docutils literal"><span class="pre">ymin</span></tt></a> is the bottom edge of the bounding box.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Bbox">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">Bbox</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.BboxBase</span></tt></a></p>
<p>A mutable bounding box.</p>
<p><em>points</em>: a 2x2 numpy array of the form [[x0, y0], [x1, y1]]</p>
<p>If you need to create a <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> object from another form
of data, consider the static methods <a class="reference internal" href="#matplotlib.transforms.Bbox.unit" title="matplotlib.transforms.Bbox.unit"><tt class="xref py py-meth docutils literal"><span class="pre">unit()</span></tt></a>,
<a class="reference internal" href="#matplotlib.transforms.Bbox.from_bounds" title="matplotlib.transforms.Bbox.from_bounds"><tt class="xref py py-meth docutils literal"><span class="pre">from_bounds()</span></tt></a> and <a class="reference internal" href="#matplotlib.transforms.Bbox.from_extents" title="matplotlib.transforms.Bbox.from_extents"><tt class="xref py py-meth docutils literal"><span class="pre">from_extents()</span></tt></a>.</p>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.from_bounds">
<em class="property">static </em><tt class="descname">from_bounds</tt><big>(</big><em>x0</em>, <em>y0</em>, <em>width</em>, <em>height</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.from_bounds" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> from <em>x0</em>, <em>y0</em>,
<em>width</em> and <em>height</em>.</p>
<p><em>width</em> and <em>height</em> may be negative.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.from_extents">
<em class="property">static </em><tt class="descname">from_extents</tt><big>(</big><em>*args</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.from_extents" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new Bbox from <em>left</em>, <em>bottom</em>,
<em>right</em> and <em>top</em>.</p>
<p>The <em>y</em>-axis increases upwards.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.get_points">
<tt class="descname">get_points</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.get_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the points of the bounding box directly as a numpy array
of the form: [[x0, y0], [x1, y1]].</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.ignore">
<tt class="descname">ignore</tt><big>(</big><em>value</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.ignore" title="Permalink to this definition">¶</a></dt>
<dd><p>Set whether the existing bounds of the box should be ignored
by subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data" title="matplotlib.transforms.Bbox.update_from_data"><tt class="xref py py-meth docutils literal"><span class="pre">update_from_data()</span></tt></a> or
<a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="matplotlib.transforms.Bbox.update_from_data_xy"><tt class="xref py py-meth docutils literal"><span class="pre">update_from_data_xy()</span></tt></a>.</p>
<p><em>value</em>:</p>
<blockquote>
<div><ul class="simple">
<li>When True, subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data" title="matplotlib.transforms.Bbox.update_from_data"><tt class="xref py py-meth docutils literal"><span class="pre">update_from_data()</span></tt></a>
will ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>When False, subsequent calls to <a class="reference internal" href="#matplotlib.transforms.Bbox.update_from_data" title="matplotlib.transforms.Bbox.update_from_data"><tt class="xref py py-meth docutils literal"><span class="pre">update_from_data()</span></tt></a>
will include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
</ul>
</div></blockquote>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutated">
<tt class="descname">mutated</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.mutated" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the bbox has changed since init</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutatedx">
<tt class="descname">mutatedx</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.mutatedx" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the x-limits have changed since init</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.mutatedy">
<tt class="descname">mutatedy</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.mutatedy" title="Permalink to this definition">¶</a></dt>
<dd><p>return whether the y-limits have changed since init</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.set">
<tt class="descname">set</tt><big>(</big><em>other</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Set this bounding box from the “frozen” bounds of another
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.set_points">
<tt class="descname">set_points</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.set_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the points of the bounding box directly from a numpy array
of the form: [[x0, y0], [x1, y1]]. No error checking is
performed, as this method is mainly for internal use.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Bbox.unit">
<em class="property">static </em><tt class="descname">unit</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.unit" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new unit <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> from (0, 0) to
(1, 1).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_data">
<tt class="descname">update_from_data</tt><big>(</big><em>x</em>, <em>y</em>, <em>ignore=None</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_data" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>x</em>: a numpy array of <em>x</em>-values</p>
<p><em>y</em>: a numpy array of <em>y</em>-values</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><tt class="xref py py-meth docutils literal"><span class="pre">ignore()</span></tt></a>.</li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_data_xy">
<tt class="descname">update_from_data_xy</tt><big>(</big><em>xy</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_data_xy" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>xy</em>: a numpy array of 2D points</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><tt class="xref py py-meth docutils literal"><span class="pre">ignore()</span></tt></a>.</li>
</ul>
</dd>
</dl>
<p><em>updatex</em>: when True, update the x values</p>
<p><em>updatey</em>: when True, update the y values</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Bbox.update_from_path">
<tt class="descname">update_from_path</tt><big>(</big><em>path</em>, <em>ignore=None</em>, <em>updatex=True</em>, <em>updatey=True</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Bbox.update_from_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Update the bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> based on the passed in
data. After updating, the bounds will have positive <em>width</em>
and <em>height</em>; <em>x0</em> and <em>y0</em> will be the minimal values.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance</p>
<dl class="docutils">
<dt><em>ignore</em>:</dt>
<dd><ul class="first last simple">
<li>when True, ignore the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when False, include the existing bounds of the <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</li>
<li>when None, use the last value passed to <a class="reference internal" href="#matplotlib.transforms.Bbox.ignore" title="matplotlib.transforms.Bbox.ignore"><tt class="xref py py-meth docutils literal"><span class="pre">ignore()</span></tt></a>.</li>
</ul>
</dd>
</dl>
<p><em>updatex</em>: when True, update the x values</p>
<p><em>updatey</em>: when True, update the y values</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.TransformedBbox">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">TransformedBbox</tt><big>(</big><em>bbox</em>, <em>transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedBbox" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.BboxBase" title="matplotlib.transforms.BboxBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.BboxBase</span></tt></a></p>
<p>A <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> that is automatically transformed by a given
transform. When either the child bounding box or transform
changes, the bounds of this bbox will update accordingly.</p>
<p><em>bbox</em>: a child <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a></p>
<p><em>transform</em>: a 2D <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">Transform</span></tt></a></p>
<dl class="method">
<dt id="matplotlib.transforms.TransformedBbox.get_points">
<tt class="descname">get_points</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedBbox.get_points" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the points of the bounding box directly as a numpy array
of the form: [[x0, y0], [x1, y1]].</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Transform">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">Transform</tt><a class="headerlink" href="#matplotlib.transforms.Transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.TransformNode</span></tt></a></p>
<p>The base class of all <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a> instances that
actually perform a transformation.</p>
<p>All non-affine transformations should be subclasses of this class.
New affine transformations should be subclasses of
<a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><tt class="xref py py-class docutils literal"><span class="pre">Affine2D</span></tt></a>.</p>
<p>Subclasses of this class should override the following members (at
minimum):</p>
<blockquote>
<div><ul class="simple">
<li><tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt></li>
<li><tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.transform" title="matplotlib.transforms.Transform.transform"><tt class="xref py py-meth docutils literal"><span class="pre">transform()</span></tt></a></li>
<li><tt class="xref py py-attr docutils literal"><span class="pre">is_separable</span></tt></li>
<li><tt class="xref py py-attr docutils literal"><span class="pre">has_inverse</span></tt></li>
<li><a class="reference internal" href="#matplotlib.transforms.Transform.inverted" title="matplotlib.transforms.Transform.inverted"><tt class="xref py py-meth docutils literal"><span class="pre">inverted()</span></tt></a> (if <tt class="xref py py-meth docutils literal"><span class="pre">has_inverse()</span></tt> can return True)</li>
</ul>
</div></blockquote>
<p>If the transform needs to do something non-standard with
<a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.path.Path</span></tt></a> objects, such as adding curves
where there were once line segments, it should override:</p>
<blockquote>
<div><ul class="simple">
<li><a class="reference internal" href="#matplotlib.transforms.Transform.transform_path" title="matplotlib.transforms.Transform.transform_path"><tt class="xref py py-meth docutils literal"><span class="pre">transform_path()</span></tt></a></li>
</ul>
</div></blockquote>
<p>Creates a new <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">TransformNode</span></tt></a>.</p>
<dl class="method">
<dt id="matplotlib.transforms.Transform.get_affine">
<tt class="descname">get_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.inverted">
<tt class="descname">inverted</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform">
<tt class="descname">transform</tt><big>(</big><em>values</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs the transformation on the given array of values.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_affine">
<tt class="descname">transform_affine</tt><big>(</big><em>values</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_angles">
<tt class="descname">transform_angles</tt><big>(</big><em>angles</em>, <em>pts</em>, <em>radians=False</em>, <em>pushoff=1.0000000000000001e-05</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_angles" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs transformation on a set of angles anchored at
specific locations.</p>
<p>The <em>angles</em> must be a column vector (i.e., numpy array).</p>
<p>The <em>pts</em> must be a two-column numpy array of x,y positions
(angle transforms currently only work in 2D). This array must
have the same number of rows as <em>angles</em>.</p>
<dl class="docutils">
<dt><em>radians</em> indicates whether or not input angles are given in</dt>
<dd>radians (True) or degrees (False; the default).</dd>
<dt><em>pushoff</em> is the distance to move away from <em>pts</em> for</dt>
<dd>determining transformed angles (see discussion of method
below).</dd>
</dl>
<p>The transformed angles are returned in an array with the same
size as <em>angles</em>.</p>
<p>The generic version of this method uses a very generic
algorithm that transforms <em>pts</em>, as well as locations very
close to <em>pts</em>, to find the angle in the transformed system.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_non_affine">
<tt class="descname">transform_non_affine</tt><big>(</big><em>values</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_path">
<tt class="descname">transform_path</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a transformed copy of path.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p>In some cases, this transform may insert curves into the path
that began as line segments.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_path_affine">
<tt class="descname">transform_path_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the affine part of
this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_path_non_affine">
<tt class="descname">transform_path_non_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Transform.transform_point">
<tt class="descname">transform_point</tt><big>(</big><em>point</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Transform.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 <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>.
The transformed point is returned as a sequence of length
<tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.TransformWrapper">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">TransformWrapper</tt><big>(</big><em>child</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformWrapper" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></tt></a></p>
<p>A helper class that holds a single child transform and acts
equivalently to it.</p>
<p>This is useful if a node of the transform tree must be replaced at
run time with a transform of a different type. This class allows
that replacement to correctly trigger invalidation.</p>
<p>Note that <a class="reference internal" href="#matplotlib.transforms.TransformWrapper" title="matplotlib.transforms.TransformWrapper"><tt class="xref py py-class docutils literal"><span class="pre">TransformWrapper</span></tt></a> instances must have the same
input and output dimensions during their entire lifetime, so the
child transform may only be replaced with another child transform
of the same dimensions.</p>
<p><em>child</em>: A class:<cite>Transform</cite> instance. This child may later
be replaced with <a class="reference internal" href="#matplotlib.transforms.TransformWrapper.set" title="matplotlib.transforms.TransformWrapper.set"><tt class="xref py py-meth docutils literal"><span class="pre">set()</span></tt></a>.</p>
<dl class="method">
<dt id="matplotlib.transforms.TransformWrapper.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformWrapper.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
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformWrapper.set">
<tt class="descname">set</tt><big>(</big><em>child</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformWrapper.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Replace the current child of this transform with another one.</p>
<p>The new child must have the same number of input and output
dimensions as the current child.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.AffineBase">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">AffineBase</tt><a class="headerlink" href="#matplotlib.transforms.AffineBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></tt></a></p>
<p>The base class of all affine transformations of any number of
dimensions.</p>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.get_affine">
<tt class="descname">get_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.AffineBase.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.AffineBase.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_non_affine">
<tt class="descname">transform_non_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_path_affine">
<tt class="descname">transform_path_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the affine part of
this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.AffineBase.transform_path_non_affine">
<tt class="descname">transform_path_non_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.AffineBase.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Affine2DBase">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">Affine2DBase</tt><a class="headerlink" href="#matplotlib.transforms.Affine2DBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.AffineBase" title="matplotlib.transforms.AffineBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.AffineBase</span></tt></a></p>
<p>The base class of all 2D affine transformations.</p>
<p>2D affine transformations are performed using a 3x3 numpy array:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
<p>This class provides the read-only interface. For a mutable 2D
affine transformation, use <a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><tt class="xref py py-class docutils literal"><span class="pre">Affine2D</span></tt></a>.</p>
<p>Subclasses of this class will generally only need to override a
constructor and <tt class="xref py py-meth docutils literal"><span class="pre">get_matrix()</span></tt> that generates a custom 3x3 matrix.</p>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.frozen" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a frozen copy of this transform node. The frozen copy
will not update when its children change. Useful for storing
a previously known state of a transform where
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.inverted">
<tt class="descname">inverted</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2DBase.matrix_from_values">
<em class="property">static </em><tt class="descname">matrix_from_values</tt><big>(</big><em>a</em>, <em>b</em>, <em>c</em>, <em>d</em>, <em>e</em>, <em>f</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.matrix_from_values" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new transformation matrix as a 3x3
numpy array of the form:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.to_values">
<tt class="descname">to_values</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.to_values" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the values of the matrix as a sequence (a,b,c,d,e,f)</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.transform">
<tt class="descname">transform</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform" 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><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.transform_affine">
<tt class="descname">transform_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the affine part of this transformation on the
given array of values.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2DBase.transform_point">
<tt class="descname">transform_point</tt><big>(</big><em>point</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2DBase.transform_point" title="Permalink to this definition">¶</a></dt>
<dd><p>A convenience function that returns the transformed copy of a
single point.</p>
<p>The point is given as a sequence of length <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>.
The transformed point is returned as a sequence of length
<tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.Affine2D">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">Affine2D</tt><big>(</big><em>matrix=None</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p>A mutable 2D affine transformation.</p>
<p>Initialize an Affine transform from a 3x3 numpy float array:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
<p>If <em>matrix</em> is None, initialize with the identity transform.</p>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.clear">
<tt class="descname">clear</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.clear" title="Permalink to this definition">¶</a></dt>
<dd><p>Reset the underlying matrix to the identity transform.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2D.from_values">
<em class="property">static </em><tt class="descname">from_values</tt><big>(</big><em>a</em>, <em>b</em>, <em>c</em>, <em>d</em>, <em>e</em>, <em>f</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.from_values" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Create a new Affine2D instance from the given
values:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
<p>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a 3x3 numpy array:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
<p>.</p>
</dd></dl>
<dl class="staticmethod">
<dt id="matplotlib.transforms.Affine2D.identity">
<em class="property">static </em><tt class="descname">identity</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.identity" title="Permalink to this definition">¶</a></dt>
<dd><p>(staticmethod) Return a new <a class="reference internal" href="#matplotlib.transforms.Affine2D" title="matplotlib.transforms.Affine2D"><tt class="xref py py-class docutils literal"><span class="pre">Affine2D</span></tt></a> object that is
the identity transform.</p>
<p>Unless this transform will be mutated later on, consider using
the faster <a class="reference internal" href="#matplotlib.transforms.IdentityTransform" title="matplotlib.transforms.IdentityTransform"><tt class="xref py py-class docutils literal"><span class="pre">IdentityTransform</span></tt></a> class instead.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate">
<tt class="descname">rotate</tt><big>(</big><em>theta</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in radians) to this transform in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_around">
<tt class="descname">rotate_around</tt><big>(</big><em>x</em>, <em>y</em>, <em>theta</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_around" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in radians) around the point (x, y) in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg">
<tt class="descname">rotate_deg</tt><big>(</big><em>degrees</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_deg" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in degrees) to this transform in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.rotate_deg_around">
<tt class="descname">rotate_deg_around</tt><big>(</big><em>x</em>, <em>y</em>, <em>degrees</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.rotate_deg_around" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a rotation (in degrees) around the point (x, y) in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.scale">
<tt class="descname">scale</tt><big>(</big><em>sx</em>, <em>sy=None</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a scale in place.</p>
<p>If <em>sy</em> is None, the same scale is applied in both the <em>x</em>- and
<em>y</em>-directions.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.set">
<tt class="descname">set</tt><big>(</big><em>other</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.set" title="Permalink to this definition">¶</a></dt>
<dd><p>Set this transformation from the frozen copy of another
<a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">Affine2DBase</span></tt></a> object.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.set_matrix">
<tt class="descname">set_matrix</tt><big>(</big><em>mtx</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.set_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the underlying transformation matrix from a 3x3 numpy array:</p>
<div class="highlight-python"><pre>a c e
b d f
0 0 1</pre>
</div>
<p>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.Affine2D.translate">
<tt class="descname">translate</tt><big>(</big><em>tx</em>, <em>ty</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.Affine2D.translate" title="Permalink to this definition">¶</a></dt>
<dd><p>Adds a translation in place.</p>
<p>Returns <em>self</em>, so this method can easily be chained with more
calls to <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate" title="matplotlib.transforms.Affine2D.rotate"><tt class="xref py py-meth docutils literal"><span class="pre">rotate()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.rotate_deg" title="matplotlib.transforms.Affine2D.rotate_deg"><tt class="xref py py-meth docutils literal"><span class="pre">rotate_deg()</span></tt></a>, <a class="reference internal" href="#matplotlib.transforms.Affine2D.translate" title="matplotlib.transforms.Affine2D.translate"><tt class="xref py py-meth docutils literal"><span class="pre">translate()</span></tt></a>
and <a class="reference internal" href="#matplotlib.transforms.Affine2D.scale" title="matplotlib.transforms.Affine2D.scale"><tt class="xref py py-meth docutils literal"><span class="pre">scale()</span></tt></a>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.IdentityTransform">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">IdentityTransform</tt><a class="headerlink" href="#matplotlib.transforms.IdentityTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p>A special class that does on thing, the identity transform, in a
fast way.</p>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.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
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.get_affine">
<tt class="descname">get_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.inverted">
<tt class="descname">inverted</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform">
<tt class="descname">transform</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform_affine">
<tt class="descname">transform_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform_non_affine">
<tt class="descname">transform_non_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform_path">
<tt class="descname">transform_path</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform_path_affine">
<tt class="descname">transform_path_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.IdentityTransform.transform_path_non_affine">
<tt class="descname">transform_path_non_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.IdentityTransform.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BlendedGenericTransform">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BlendedGenericTransform</tt><big>(</big><em>x_transform</em>, <em>y_transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></tt></a></p>
<p>A “blended” transform uses one transform for the <em>x</em>-direction, and
another transform for the <em>y</em>-direction.</p>
<p>This “generic” version can handle any given child transform in the
<em>x</em>- and <em>y</em>-directions.</p>
<p>Create a new “blended” transform using <em>x_transform</em> to
transform the <em>x</em>-axis and <em>y_transform</em> to transform the
<em>y</em>-axis.</p>
<p>You will generally not call this constructor directly but use
the <a class="reference internal" href="#matplotlib.transforms.blended_transform_factory" title="matplotlib.transforms.blended_transform_factory"><tt class="xref py py-func docutils literal"><span class="pre">blended_transform_factory()</span></tt></a> function instead, which
can determine automatically which kind of blended transform to
create.</p>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.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
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.get_affine">
<tt class="descname">get_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.inverted">
<tt class="descname">inverted</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.transform">
<tt class="descname">transform</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.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 <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.transform_affine">
<tt class="descname">transform_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.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><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.BlendedGenericTransform.transform_non_affine">
<tt class="descname">transform_non_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedGenericTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BlendedAffine2D">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BlendedAffine2D</tt><big>(</big><em>x_transform</em>, <em>y_transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedAffine2D" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p>A “blended” transform uses one transform for the <em>x</em>-direction, and
another transform for the <em>y</em>-direction.</p>
<p>This version is an optimization for the case where both child
transforms are of type <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">Affine2DBase</span></tt></a>.</p>
<p>Create a new “blended” transform using <em>x_transform</em> to
transform the <em>x</em>-axis and <em>y_transform</em> to transform the
<em>y</em>-axis.</p>
<p>Both <em>x_transform</em> and <em>y_transform</em> must be 2D affine
transforms.</p>
<p>You will generally not call this constructor directly but use
the <a class="reference internal" href="#matplotlib.transforms.blended_transform_factory" title="matplotlib.transforms.blended_transform_factory"><tt class="xref py py-func docutils literal"><span class="pre">blended_transform_factory()</span></tt></a> function instead, which
can determine automatically which kind of blended transform to
create.</p>
<dl class="method">
<dt id="matplotlib.transforms.BlendedAffine2D.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BlendedAffine2D.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="function">
<dt id="matplotlib.transforms.blended_transform_factory">
<tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">blended_transform_factory</tt><big>(</big><em>x_transform</em>, <em>y_transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.blended_transform_factory" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new “blended” transform using <em>x_transform</em> to transform
the <em>x</em>-axis and <em>y_transform</em> to transform the <em>y</em>-axis.</p>
<p>A faster version of the blended transform is returned for the case
where both child transforms are affine.</p>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.CompositeGenericTransform">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">CompositeGenericTransform</tt><big>(</big><em>a</em>, <em>b</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></tt></a></p>
<p>A composite transform formed by applying transform <em>a</em> then
transform <em>b</em>.</p>
<p>This “generic” version can handle any two arbitrary
transformations.</p>
<p>Create a new composite transform that is the result of
applying transform <em>a</em> then transform <em>b</em>.</p>
<p>You will generally not call this constructor directly but use
the <a class="reference internal" href="#matplotlib.transforms.composite_transform_factory" title="matplotlib.transforms.composite_transform_factory"><tt class="xref py py-func docutils literal"><span class="pre">composite_transform_factory()</span></tt></a> function instead,
which can automatically choose the best kind of composite
transform instance to create.</p>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.frozen">
<tt class="descname">frozen</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.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
<tt class="docutils literal"><span class="pre">copy.deepcopy()</span></tt> might normally be used.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.get_affine">
<tt class="descname">get_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.get_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the affine part of this transform.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.inverted">
<tt class="descname">inverted</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
<p><tt class="docutils literal"><span class="pre">x</span> <span class="pre">===</span> <span class="pre">self.inverted().transform(self.transform(x))</span></tt></p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform">
<tt class="descname">transform</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.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 <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform_affine">
<tt class="descname">transform_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.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><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally a no-op. In
affine transformations, this is equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform_non_affine">
<tt class="descname">transform_non_affine</tt><big>(</big><em>points</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Performs only the non-affine part of the transformation.</p>
<p><tt class="docutils literal"><span class="pre">transform(values)</span></tt> is always equivalent to
<tt class="docutils literal"><span class="pre">transform_affine(transform_non_affine(values))</span></tt>.</p>
<p>In non-affine transformations, this is generally equivalent to
<tt class="docutils literal"><span class="pre">transform(values)</span></tt>. In affine transformations, this is
always a no-op.</p>
<p>Accepts a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">input_dims</span></tt>) and
returns a numpy array of shape (N x <tt class="xref py py-attr docutils literal"><span class="pre">output_dims</span></tt>).</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform_path">
<tt class="descname">transform_path</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.transform_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a transformed copy of path.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p>In some cases, this transform may insert curves into the path
that began as line segments.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform_path_affine">
<tt class="descname">transform_path_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.transform_path_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the affine part of
this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.CompositeGenericTransform.transform_path_non_affine">
<tt class="descname">transform_path_non_affine</tt><big>(</big><em>path</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeGenericTransform.transform_path_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a copy of path, transformed only by the non-affine
part of this transform.</p>
<p><em>path</em>: a <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> instance.</p>
<p><tt class="docutils literal"><span class="pre">transform_path(path)</span></tt> is equivalent to
<tt class="docutils literal"><span class="pre">transform_path_affine(transform_path_non_affine(values))</span></tt>.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.CompositeAffine2D">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">CompositeAffine2D</tt><big>(</big><em>a</em>, <em>b</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeAffine2D" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p>A composite transform formed by applying transform <em>a</em> then transform <em>b</em>.</p>
<p>This version is an optimization that handles the case where both <em>a</em>
and <em>b</em> are 2D affines.</p>
<p>Create a new composite transform that is the result of
applying transform <em>a</em> then transform <em>b</em>.</p>
<p>Both <em>a</em> and <em>b</em> must be instances of <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">Affine2DBase</span></tt></a>.</p>
<p>You will generally not call this constructor directly but use
the <a class="reference internal" href="#matplotlib.transforms.composite_transform_factory" title="matplotlib.transforms.composite_transform_factory"><tt class="xref py py-func docutils literal"><span class="pre">composite_transform_factory()</span></tt></a> function instead,
which can automatically choose the best kind of composite
transform instance to create.</p>
<dl class="method">
<dt id="matplotlib.transforms.CompositeAffine2D.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.CompositeAffine2D.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="function">
<dt id="matplotlib.transforms.composite_transform_factory">
<tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">composite_transform_factory</tt><big>(</big><em>a</em>, <em>b</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.composite_transform_factory" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a new composite transform that is the result of applying
transform a then transform b.</p>
<p>Shortcut versions of the blended transform are provided for the
case where both child transforms are affine, or one or the other
is the identity transform.</p>
<p>Composite transforms may also be created using the ‘+’ operator,
e.g.:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">c</span> <span class="o">=</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span>
</pre></div>
</div>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BboxTransform">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BboxTransform</tt><big>(</big><em>boxin</em>, <em>boxout</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p><a class="reference internal" href="#matplotlib.transforms.BboxTransform" title="matplotlib.transforms.BboxTransform"><tt class="xref py py-class docutils literal"><span class="pre">BboxTransform</span></tt></a> linearly transforms points from one
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> to another <a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</p>
<p>Create a new <a class="reference internal" href="#matplotlib.transforms.BboxTransform" title="matplotlib.transforms.BboxTransform"><tt class="xref py py-class docutils literal"><span class="pre">BboxTransform</span></tt></a> that linearly transforms
points from <em>boxin</em> to <em>boxout</em>.</p>
<dl class="method">
<dt id="matplotlib.transforms.BboxTransform.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransform.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BboxTransformTo">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BboxTransformTo</tt><big>(</big><em>boxout</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransformTo" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p><a class="reference internal" href="#matplotlib.transforms.BboxTransformTo" title="matplotlib.transforms.BboxTransformTo"><tt class="xref py py-class docutils literal"><span class="pre">BboxTransformTo</span></tt></a> is a transformation that linearly
transforms points from the unit bounding box to a given
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>.</p>
<p>Create a new <a class="reference internal" href="#matplotlib.transforms.BboxTransformTo" title="matplotlib.transforms.BboxTransformTo"><tt class="xref py py-class docutils literal"><span class="pre">BboxTransformTo</span></tt></a> that linearly transforms
points from the unit bounding box to <em>boxout</em>.</p>
<dl class="method">
<dt id="matplotlib.transforms.BboxTransformTo.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransformTo.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.BboxTransformFrom">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">BboxTransformFrom</tt><big>(</big><em>boxin</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransformFrom" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p><a class="reference internal" href="#matplotlib.transforms.BboxTransformFrom" title="matplotlib.transforms.BboxTransformFrom"><tt class="xref py py-class docutils literal"><span class="pre">BboxTransformFrom</span></tt></a> linearly transforms points from a given
<a class="reference internal" href="#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> to the unit bounding box.</p>
<dl class="method">
<dt id="matplotlib.transforms.BboxTransformFrom.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.BboxTransformFrom.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.ScaledTranslation">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">ScaledTranslation</tt><big>(</big><em>xt</em>, <em>yt</em>, <em>scale_trans</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.ScaledTranslation" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.Affine2DBase" title="matplotlib.transforms.Affine2DBase"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Affine2DBase</span></tt></a></p>
<p>A transformation that translates by <em>xt</em> and <em>yt</em>, after <em>xt</em> and <em>yt</em>
have been transformad by the given transform <em>scale_trans</em>.</p>
<dl class="method">
<dt id="matplotlib.transforms.ScaledTranslation.get_matrix">
<tt class="descname">get_matrix</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.ScaledTranslation.get_matrix" title="Permalink to this definition">¶</a></dt>
<dd><p>Get the underlying transformation matrix as a numpy array.</p>
</dd></dl>
</dd></dl>
<dl class="class">
<dt id="matplotlib.transforms.TransformedPath">
<em class="property">class </em><tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">TransformedPath</tt><big>(</big><em>path</em>, <em>transform</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedPath" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.transforms.TransformNode" title="matplotlib.transforms.TransformNode"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.TransformNode</span></tt></a></p>
<p>A <a class="reference internal" href="#matplotlib.transforms.TransformedPath" title="matplotlib.transforms.TransformedPath"><tt class="xref py py-class docutils literal"><span class="pre">TransformedPath</span></tt></a> caches a non-affine transformed copy of
the <a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a>. This cached copy is
automatically updated when the non-affine part of the transform
changes.</p>
<div class="admonition note">
<p class="first admonition-title">Note</p>
<p class="last">Paths are considered immutable by this class. Any update to the
path’s vertices/codes will not trigger a transform recomputation.</p>
</div>
<p>Create a new <a class="reference internal" href="#matplotlib.transforms.TransformedPath" title="matplotlib.transforms.TransformedPath"><tt class="xref py py-class docutils literal"><span class="pre">TransformedPath</span></tt></a> from the given
<a class="reference internal" href="../api/path_api.html#matplotlib.path.Path" title="matplotlib.path.Path"><tt class="xref py py-class docutils literal"><span class="pre">Path</span></tt></a> and <a class="reference internal" href="#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">Transform</span></tt></a>.</p>
<dl class="method">
<dt id="matplotlib.transforms.TransformedPath.get_fully_transformed_path">
<tt class="descname">get_fully_transformed_path</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedPath.get_fully_transformed_path" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a fully-transformed copy of the child path.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformedPath.get_transformed_path_and_affine">
<tt class="descname">get_transformed_path_and_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedPath.get_transformed_path_and_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the child path, with the non-affine part of
the transform already applied, along with the affine part of
the path necessary to complete the transformation.</p>
</dd></dl>
<dl class="method">
<dt id="matplotlib.transforms.TransformedPath.get_transformed_points_and_affine">
<tt class="descname">get_transformed_points_and_affine</tt><big>(</big><big>)</big><a class="headerlink" href="#matplotlib.transforms.TransformedPath.get_transformed_points_and_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a copy of the child path, with the non-affine part of
the transform already applied, along with the affine part of
the path necessary to complete the transformation. Unlike
<a class="reference internal" href="#matplotlib.transforms.TransformedPath.get_transformed_path_and_affine" title="matplotlib.transforms.TransformedPath.get_transformed_path_and_affine"><tt class="xref py py-meth docutils literal"><span class="pre">get_transformed_path_and_affine()</span></tt></a>, no interpolation will
be performed.</p>
</dd></dl>
</dd></dl>
<dl class="function">
<dt id="matplotlib.transforms.nonsingular">
<tt class="descclassname">matplotlib.transforms.</tt><tt class="descname">nonsingular</tt><big>(</big><em>vmin</em>, <em>vmax</em>, <em>expander=0.001</em>, <em>tiny=1.0000000000000001e-15</em>, <em>increasing=True</em><big>)</big><a class="headerlink" href="#matplotlib.transforms.nonsingular" title="Permalink to this definition">¶</a></dt>
<dd><p>Ensure the endpoints of a range are finite and not too close together.</p>
<p>“too close” means the interval is smaller than ‘tiny’ times
the maximum absolute value.</p>
<p>If they are too close, each will be moved by the ‘expander’.
If ‘increasing’ is True and vmin > vmax, they will be swapped,
regardless of whether they are too close.</p>
<p>If either is inf or -inf or nan, return - expander, expander.</p>
</dd></dl>
</div>
</div>
</div>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="related">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="../genindex.html" title="General Index"
>index</a></li>
<li class="right" >
<a href="../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="right" >
<a href="add_new_projection.html" title="Adding new scales and projections to matplotlib"
>next</a> |</li>
<li class="right" >
<a href="release_guide.html" title="Doing a matplolib release"
>previous</a> |</li>
<li><a href="../index.html">home</a>| </li>
<li><a href="../search.html">search</a>| </li>
<li><a href="../examples/index.html">examples</a>| </li>
<li><a href="../gallery.html">gallery</a>| </li>
<li><a href="../contents.html">docs</a> »</li>
<li><a href="index.html" >The Matplotlib Developers’ Guide</a> »</li>
</ul>
</div>
<div class="footer">
© Copyright 2008, John Hunter, Darren Dale, Michael Droettboom.
Last updated on Oct 04, 2012.
Created using <a href="http://sphinx.pocoo.org/">Sphinx</a> 1.0.7.
</div>
</body>
</html>
distrib
>
Mandriva
>
2010.2
>
i586
>
media
>
contrib-backports
>
by-pkgid
>
a44f8c7e78ee9c5838c1fb080c9e7630
>
files
>
1656
