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<ul>
<li><a class="reference internal" href="#">API Changes</a><ul>
<li><a class="reference internal" href="#changes-in-1-2-x">Changes in 1.2.x</a></li>
<li><a class="reference internal" href="#changes-in-1-1-x">Changes in 1.1.x</a></li>
<li><a class="reference internal" href="#changes-beyond-0-99-x">Changes beyond 0.99.x</a></li>
<li><a class="reference internal" href="#changes-in-0-99">Changes in 0.99</a></li>
<li><a class="reference internal" href="#changes-for-0-98-x">Changes for 0.98.x</a></li>
<li><a class="reference internal" href="#changes-for-0-98-1">Changes for 0.98.1</a></li>
<li><a class="reference internal" href="#changes-for-0-98-0">Changes for 0.98.0</a><ul>
<li><a class="reference internal" href="#notes-about-the-transforms-refactoring">Notes about the transforms refactoring</a><ul>
<li><a class="reference internal" href="#matplotlib-transforms"><tt class="docutils literal"><span class="pre">matplotlib.transforms</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-axes"><tt class="docutils literal"><span class="pre">matplotlib.axes</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-artist"><tt class="docutils literal"><span class="pre">matplotlib.artist</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-collections"><tt class="docutils literal"><span class="pre">matplotlib.collections</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-colors"><tt class="docutils literal"><span class="pre">matplotlib.colors</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-contour"><tt class="docutils literal"><span class="pre">matplotlib.contour</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-figure"><tt class="docutils literal"><span class="pre">matplotlib.figure</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-patches"><tt class="docutils literal"><span class="pre">matplotlib.patches</span></tt></a></li>
<li><a class="reference internal" href="#matplotlib-backend-bases"><tt class="docutils literal"><span class="pre">matplotlib.backend_bases</span></tt></a><ul>
<li><a class="reference internal" href="#rendererbase"><tt class="docutils literal"><span class="pre">RendererBase</span></tt></a></li>
</ul>
</li>
</ul>
</li>
</ul>
</li>
<li><a class="reference internal" href="#changes-for-0-91-2">Changes for 0.91.2</a></li>
<li><a class="reference internal" href="#changes-for-0-91-1">Changes for 0.91.1</a></li>
<li><a class="reference internal" href="#changes-for-0-91-0">Changes for 0.91.0</a></li>
<li><a class="reference internal" href="#changes-for-0-90-1">Changes for 0.90.1</a></li>
<li><a class="reference internal" href="#changes-for-0-90-0">Changes for 0.90.0</a></li>
<li><a class="reference internal" href="#changes-for-0-87-7">Changes for 0.87.7</a></li>
<li><a class="reference internal" href="#changes-for-0-86">Changes for 0.86</a></li>
<li><a class="reference internal" href="#changes-for-0-85">Changes for 0.85</a></li>
<li><a class="reference internal" href="#changes-for-0-84">Changes for 0.84</a></li>
<li><a class="reference internal" href="#changes-for-0-83">Changes for 0.83</a></li>
<li><a class="reference internal" href="#changes-for-0-82">Changes for 0.82</a></li>
<li><a class="reference internal" href="#changes-for-0-81">Changes for 0.81</a></li>
<li><a class="reference internal" href="#changes-for-0-80">Changes for 0.80</a></li>
<li><a class="reference internal" href="#changes-for-0-73">Changes for 0.73</a></li>
<li><a class="reference internal" href="#changes-for-0-72">Changes for 0.72</a></li>
<li><a class="reference internal" href="#changes-for-0-71">Changes for 0.71</a></li>
<li><a class="reference internal" href="#changes-for-0-70">Changes for 0.70</a></li>
<li><a class="reference internal" href="#changes-for-0-65-1">Changes for 0.65.1</a></li>
<li><a class="reference internal" href="#changes-for-0-65">Changes for 0.65</a></li>
<li><a class="reference internal" href="#changes-for-0-63">Changes for 0.63</a></li>
<li><a class="reference internal" href="#changes-for-0-61">Changes for 0.61</a></li>
<li><a class="reference internal" href="#changes-for-0-60">Changes for 0.60</a></li>
<li><a class="reference internal" href="#changes-for-0-54-3">Changes for 0.54.3</a></li>
<li><a class="reference internal" href="#changes-for-0-54">Changes for 0.54</a><ul>
<li><a class="reference internal" href="#matlab-interface">MATLAB interface</a><ul>
<li><a class="reference internal" href="#dpi">dpi</a></li>
<li><a class="reference internal" href="#pcolor-and-scatter">pcolor and scatter</a></li>
<li><a class="reference internal" href="#mathtext-spacing">mathtext spacing</a></li>
</ul>
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<li><a class="reference internal" href="#object-interface-application-programmers">Object interface - Application programmers</a><ul>
<li><a class="reference internal" href="#autoscaling">Autoscaling</a></li>
<li><a class="reference internal" href="#axes-creation">Axes creation</a></li>
<li><a class="reference internal" href="#artist-methods">Artist methods</a></li>
<li><a class="reference internal" href="#bounding-boxes">Bounding boxes</a></li>
<li><a class="reference internal" href="#object-constructors">Object constructors</a></li>
<li><a class="reference internal" href="#transformations">Transformations</a></li>
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<li><a class="reference internal" href="#changes-for-0-50">Changes for 0.50</a></li>
<li><a class="reference internal" href="#changes-for-0-42">Changes for 0.42</a></li>
<li><a class="reference internal" href="#changes-for-0-40">Changes for 0.40</a></li>
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<div class="section" id="api-changes">
<h1>API Changes<a class="headerlink" href="#api-changes" title="Permalink to this headline">¶</a></h1>
<p>This chapter is a log of changes to matplotlib that affect the
outward-facing API. If updating matplotlib breaks your scripts, this
list may help describe what changes may be necessary in your code or
help figure out possible sources of the changes you are experiencing.</p>
<p>For new features that were added to matplotlib, please see
<a class="reference internal" href="../users/whats_new.html#whats-new"><em>What’s new in matplotlib</em></a>.</p>
<div class="section" id="changes-in-1-2-x">
<h2>Changes in 1.2.x<a class="headerlink" href="#changes-in-1-2-x" title="Permalink to this headline">¶</a></h2>
<ul>
<li><p class="first">The <tt class="docutils literal"><span class="pre">classic</span></tt> option of the rc parameter <tt class="docutils literal"><span class="pre">toolbar</span></tt> is deprecated
and will be removed in the next release.</p>
</li>
<li><p class="first">The <tt class="xref py py-meth docutils literal"><span class="pre">isvector()</span></tt> method has been removed since it
is no longer functional.</p>
</li>
<li><p class="first">The <tt class="xref py py-obj docutils literal"><span class="pre">rasterization_zorder</span></tt> property on <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><tt class="xref py py-obj docutils literal"><span class="pre">Axes</span></tt></a> a
zorder below which artists are rasterized. This has defaulted to
-30000.0, but it now defaults to <tt class="xref py py-obj docutils literal"><span class="pre">None</span></tt>, meaning no artists will be
rasterized. In order to rasterize artists below a given zorder
value, <tt class="xref py py-obj docutils literal"><span class="pre">set_rasterization_zorder</span></tt> must be explicitly called.</p>
</li>
<li><p class="first">In <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.scatter" title="matplotlib.axes.Axes.scatter"><tt class="xref py py-meth docutils literal"><span class="pre">scatter()</span></tt></a>, and <tt class="xref py py-obj docutils literal"><span class="pre">scatter</span></tt>,
when specifying a marker using a tuple, the angle is now specified
in degrees, not radians.</p>
</li>
<li><p class="first">Using <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.twinx" title="matplotlib.axes.Axes.twinx"><tt class="xref py py-meth docutils literal"><span class="pre">twinx()</span></tt></a> or
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.twiny" title="matplotlib.axes.Axes.twiny"><tt class="xref py py-meth docutils literal"><span class="pre">twiny()</span></tt></a> no longer overrides the current locaters
and formatters on the axes.</p>
</li>
<li><p class="first">In <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.contourf" title="matplotlib.axes.Axes.contourf"><tt class="xref py py-meth docutils literal"><span class="pre">contourf()</span></tt></a>, the handling of the <em>extend</em>
kwarg has changed. Formerly, the extended ranges were mapped
after to 0, 1 after being normed, so that they always corresponded
to the extreme values of the colormap. Now they are mapped
outside this range so that they correspond to the special
colormap values determined by the
<a class="reference internal" href="colors_api.html#matplotlib.colors.Colormap.set_under" title="matplotlib.colors.Colormap.set_under"><tt class="xref py py-meth docutils literal"><span class="pre">set_under()</span></tt></a> and
<a class="reference internal" href="colors_api.html#matplotlib.colors.Colormap.set_over" title="matplotlib.colors.Colormap.set_over"><tt class="xref py py-meth docutils literal"><span class="pre">set_over()</span></tt></a> methods, which
default to the colormap end points.</p>
</li>
<li><p class="first">The new rc parameter <tt class="docutils literal"><span class="pre">savefig.format</span></tt> replaces <tt class="docutils literal"><span class="pre">cairo.format</span></tt> and
<tt class="docutils literal"><span class="pre">savefig.extension</span></tt>, and sets the default file format used by
<a class="reference internal" href="figure_api.html#matplotlib.figure.Figure.savefig" title="matplotlib.figure.Figure.savefig"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.figure.Figure.savefig()</span></tt></a>.</p>
</li>
<li><p class="first">In <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.pie" title="matplotlib.pyplot.pie"><tt class="xref py py-meth docutils literal"><span class="pre">pie()</span></tt></a> and <tt class="xref py py-meth docutils literal"><span class="pre">pie()</span></tt>, one can
now set the radius of the pie; setting the <em>radius</em> to ‘None’ (the default
value), will result in a pie with a radius of 1 as before.</p>
</li>
<li><p class="first">Use of <a class="reference internal" href="../devel/add_new_projection.html#matplotlib.projections.projection_factory" title="matplotlib.projections.projection_factory"><tt class="xref py py-func docutils literal"><span class="pre">projection_factory()</span></tt></a> is now deprecated
in favour of axes class identification using
<a class="reference internal" href="../devel/add_new_projection.html#matplotlib.projections.process_projection_requirements" title="matplotlib.projections.process_projection_requirements"><tt class="xref py py-func docutils literal"><span class="pre">process_projection_requirements()</span></tt></a> followed by
direct axes class invocation (at the time of writing, functions which do this
are: <a class="reference internal" href="figure_api.html#matplotlib.figure.Figure.add_axes" title="matplotlib.figure.Figure.add_axes"><tt class="xref py py-meth docutils literal"><span class="pre">add_axes()</span></tt></a>,
<a class="reference internal" href="figure_api.html#matplotlib.figure.Figure.add_subplot" title="matplotlib.figure.Figure.add_subplot"><tt class="xref py py-meth docutils literal"><span class="pre">add_subplot()</span></tt></a> and
<a class="reference internal" href="figure_api.html#matplotlib.figure.Figure.gca" title="matplotlib.figure.Figure.gca"><tt class="xref py py-meth docutils literal"><span class="pre">gca()</span></tt></a>). Therefore:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">key</span> <span class="o">=</span> <span class="n">figure</span><span class="o">.</span><span class="n">_make_key</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">ispolar</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s">'polar'</span><span class="p">,</span> <span class="bp">False</span><span class="p">)</span>
<span class="n">projection</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s">'projection'</span><span class="p">,</span> <span class="bp">None</span><span class="p">)</span>
<span class="k">if</span> <span class="n">ispolar</span><span class="p">:</span>
<span class="k">if</span> <span class="n">projection</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">None</span> <span class="ow">and</span> <span class="n">projection</span> <span class="o">!=</span> <span class="s">'polar'</span><span class="p">:</span>
<span class="k">raise</span> <span class="n">ValuError</span><span class="p">(</span><span class="s">'polar and projection args are inconsistent'</span><span class="p">)</span>
<span class="n">projection</span> <span class="o">=</span> <span class="s">'polar'</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">projection_factory</span><span class="p">(</span><span class="n">projection</span><span class="p">,</span> <span class="bp">self</span><span class="p">,</span> <span class="n">rect</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">key</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_make_key</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="c"># is now</span>
<span class="n">projection_class</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">,</span> <span class="n">key</span> <span class="o">=</span> \
<span class="n">process_projection_requirements</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">ax</span> <span class="o">=</span> <span class="n">projection_class</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">rect</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
</pre></div>
</div>
<p>This change means that third party objects can expose themselves as
matplotlib axes by providing a <tt class="docutils literal"><span class="pre">_as_mpl_axes</span></tt> method. See
<a class="reference internal" href="../devel/add_new_projection.html#adding-new-scales"><em>Adding new scales and projections to matplotlib</em></a> for more detail.</p>
</li>
<li><p class="first">A new keyword <em>extendfrac</em> in <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.colorbar" title="matplotlib.pyplot.colorbar"><tt class="xref py py-meth docutils literal"><span class="pre">colorbar()</span></tt></a> and
<a class="reference internal" href="colorbar_api.html#matplotlib.colorbar.ColorbarBase" title="matplotlib.colorbar.ColorbarBase"><tt class="xref py py-class docutils literal"><span class="pre">ColorbarBase</span></tt></a> allows one to control the size of
the triangular minimum and maximum extensions on colorbars.</p>
</li>
<li><p class="first">A new keyword <em>capthick</em> in <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.errorbar" title="matplotlib.pyplot.errorbar"><tt class="xref py py-meth docutils literal"><span class="pre">errorbar()</span></tt></a> has been
added as an intuitive alias to the <em>markeredgewidth</em> and <em>mew</em> keyword
arguments, which indirectly controlled the thickness of the caps on
the errorbars. For backwards compatibility, specifying either of the
original keyword arguments will override any value provided by
<em>capthick</em>.</p>
</li>
<li><p class="first">Transform subclassing behaviour is now subtly changed. If your transform
implements a non-affine transformation, then it should override the
<tt class="docutils literal"><span class="pre">transform_non_affine</span></tt> method, rather than the generic <tt class="docutils literal"><span class="pre">transform</span></tt> method.
Previously transforms would define <tt class="docutils literal"><span class="pre">transform</span></tt> and then copy the
method into <tt class="docutils literal"><span class="pre">transform_non_affine</span></tt>:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">class</span> <span class="nc">MyTransform</span><span class="p">(</span><span class="n">mtrans</span><span class="o">.</span><span class="n">Transform</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">xy</span><span class="p">):</span>
<span class="o">...</span>
<span class="n">transform_non_affine</span> <span class="o">=</span> <span class="n">transform</span>
</pre></div>
</div>
<p>This approach will no longer function correctly and should be changed to:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="k">class</span> <span class="nc">MyTransform</span><span class="p">(</span><span class="n">mtrans</span><span class="o">.</span><span class="n">Transform</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">xy</span><span class="p">):</span>
<span class="o">...</span>
</pre></div>
</div>
</li>
<li><p class="first">Artists no longer have <tt class="docutils literal"><span class="pre">x_isdata</span></tt> or <tt class="docutils literal"><span class="pre">y_isdata</span></tt> attributes; instead
any artist’s transform can be interrogated with
<tt class="docutils literal"><span class="pre">artist_instance.get_transform().contains_branch(ax.transData)</span></tt></p>
</li>
<li><p class="first">Lines added to an axes now take into account their transform when updating the
data and view limits. This means transforms can now be used as a pre-transform.
For instance:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.transforms</span> <span class="kn">as</span> <span class="nn">mtrans</span>
<span class="gp">>>> </span><span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">axes</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">),</span> <span class="n">transform</span><span class="o">=</span><span class="n">mtrans</span><span class="o">.</span><span class="n">Affine2D</span><span class="p">()</span><span class="o">.</span><span class="n">scale</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span> <span class="o">+</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="p">)</span>
<span class="gp">>>> </span><span class="k">print</span><span class="p">(</span><span class="n">ax</span><span class="o">.</span><span class="n">viewLim</span><span class="p">)</span>
<span class="go">Bbox('array([[ 0., 0.],\n [ 90., 90.]])')</span>
</pre></div>
</div>
</li>
<li><p class="first">One can now easily get a transform which goes from one transform’s coordinate
system to another, in an optimized way, using the new subtract method on a
transform. For instance, to go from data coordinates to axes coordinates:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="gp">>>> </span><span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">axes</span><span class="p">()</span>
<span class="gp">>>> </span><span class="n">data2ax</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">transData</span> <span class="o">-</span> <span class="n">ax</span><span class="o">.</span><span class="n">transAxes</span>
<span class="gp">>>> </span><span class="k">print</span><span class="p">(</span><span class="n">ax</span><span class="o">.</span><span class="n">transData</span><span class="o">.</span><span class="n">depth</span><span class="p">,</span> <span class="n">ax</span><span class="o">.</span><span class="n">transAxes</span><span class="o">.</span><span class="n">depth</span><span class="p">)</span>
<span class="go">3, 1</span>
<span class="gp">>>> </span><span class="k">print</span><span class="p">(</span><span class="n">data2ax</span><span class="o">.</span><span class="n">depth</span><span class="p">)</span>
<span class="go">2</span>
</pre></div>
</div>
<p>for versions before 1.2 this could only be achieved in a sub-optimal way,
using <tt class="docutils literal"><span class="pre">ax.transData</span> <span class="pre">+</span> <span class="pre">ax.transAxes.inverted()</span></tt> (depth is a new concept,
but had it existed it would return 4 for this example).</p>
</li>
<li><p class="first"><tt class="docutils literal"><span class="pre">twinx</span></tt> and <tt class="docutils literal"><span class="pre">twiny</span></tt> now returns an instance of SubplotBase if
parent axes is an instance of SubplotBase.</p>
</li>
<li><p class="first">All Qt3-based backends are now deprecated due to the lack of py3k bindings.
Qt and QtAgg backends will continue to work in v1.2.x for py2.6
and py2.7. It is anticipated that the Qt3 support will be completely
removed for the next release.</p>
</li>
<li><p class="first"><a class="reference internal" href="colors_api.html#matplotlib.colors.ColorConverter" title="matplotlib.colors.ColorConverter"><tt class="xref py py-class docutils literal"><span class="pre">ColorConverter</span></tt></a>,
<a class="reference internal" href="colors_api.html#matplotlib.colors.Colormap" title="matplotlib.colors.Colormap"><tt class="xref py py-class docutils literal"><span class="pre">Colormap</span></tt></a> and
<a class="reference internal" href="colors_api.html#matplotlib.colors.Normalize" title="matplotlib.colors.Normalize"><tt class="xref py py-class docutils literal"><span class="pre">Normalize</span></tt></a> now subclasses <tt class="docutils literal"><span class="pre">object</span></tt></p>
</li>
<li><p class="first">ContourSet instances no longer have a <tt class="docutils literal"><span class="pre">transform</span></tt> attribute. Instead,
access the transform with the <tt class="docutils literal"><span class="pre">get_transform</span></tt> method.</p>
</li>
</ul>
</div>
<div class="section" id="changes-in-1-1-x">
<h2>Changes in 1.1.x<a class="headerlink" href="#changes-in-1-1-x" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>Added new <a class="reference internal" href="sankey_api.html#matplotlib.sankey.Sankey" title="matplotlib.sankey.Sankey"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.sankey.Sankey</span></tt></a> for generating Sankey diagrams.</li>
<li>In <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.imshow" title="matplotlib.pyplot.imshow"><tt class="xref py py-meth docutils literal"><span class="pre">imshow()</span></tt></a>, setting <em>interpolation</em> to ‘nearest’
will now always mean that the nearest-neighbor interpolation is performed.
If you want the no-op interpolation to be performed, choose ‘none’.</li>
<li>There were errors in how the tri-functions were handling input parameters
that had to be fixed. If your tri-plots are not working correctly anymore,
or you were working around apparent mistakes, please see issue #203 in the
github tracker. When in doubt, use kwargs.</li>
<li>The ‘symlog’ scale had some bad behavior in previous versions. This has now
been fixed and users should now be able to use it without frustrations.
The fixes did result in some minor changes in appearance for some users who
may have been depending on the bad behavior.</li>
<li>There is now a common set of markers for all plotting functions. Previously,
some markers existed only for <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.scatter" title="matplotlib.pyplot.scatter"><tt class="xref py py-meth docutils literal"><span class="pre">scatter()</span></tt></a> or just for
<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.plot" title="matplotlib.pyplot.plot"><tt class="xref py py-meth docutils literal"><span class="pre">plot()</span></tt></a>. This is now no longer the case. This merge
did result in a conflict. The string ‘d’ now means “thin diamond” while
‘D’ will mean “regular diamond”.</li>
</ul>
</div>
<div class="section" id="changes-beyond-0-99-x">
<h2>Changes beyond 0.99.x<a class="headerlink" href="#changes-beyond-0-99-x" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>The default behavior of <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_xlim" title="matplotlib.axes.Axes.set_xlim"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_xlim()</span></tt></a>,
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_ylim" title="matplotlib.axes.Axes.set_ylim"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_ylim()</span></tt></a>, and
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.axis" title="matplotlib.axes.Axes.axis"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.axis()</span></tt></a>, and their corresponding
pyplot functions, has been changed: when view limits are
set explicitly with one of these methods, autoscaling is turned
off for the matching axis. A new <em>auto</em> kwarg is available to
control this behavior. The limit kwargs have been renamed to
<em>left</em> and <em>right</em> instead of <em>xmin</em> and <em>xmax</em>, and <em>bottom</em>
and <em>top</em> instead of <em>ymin</em> and <em>ymax</em>. The old names may still
be used, however.</li>
<li>There are five new Axes methods with corresponding pyplot
functions to facilitate autoscaling, tick location, and tick
label formatting, and the general appearance of ticks and
tick labels:<ul>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.autoscale" title="matplotlib.axes.Axes.autoscale"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.autoscale()</span></tt></a> turns autoscaling
on or off, and applies it.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.margins" title="matplotlib.axes.Axes.margins"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.margins()</span></tt></a> sets margins used to
autoscale the <tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.viewLim</span></tt> based on
the <tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.dataLim</span></tt>.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.locator_params" title="matplotlib.axes.Axes.locator_params"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.locator_params()</span></tt></a> allows one to
adjust axes locator parameters such as <em>nbins</em>.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.ticklabel_format" title="matplotlib.axes.Axes.ticklabel_format"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.ticklabel_format()</span></tt></a> is a convenience
method for controlling the <a class="reference internal" href="ticker_api.html#matplotlib.ticker.ScalarFormatter" title="matplotlib.ticker.ScalarFormatter"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.ticker.ScalarFormatter</span></tt></a>
that is used by default with linear axes.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.tick_params" title="matplotlib.axes.Axes.tick_params"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.tick_params()</span></tt></a> controls direction, size,
visibility, and color of ticks and their labels.</li>
</ul>
</li>
<li>The <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.bar" title="matplotlib.axes.Axes.bar"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.bar()</span></tt></a> method accepts a <em>error_kw</em>
kwarg; it is a dictionary of kwargs to be passed to the
errorbar function.</li>
<li>The <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.hist" title="matplotlib.axes.Axes.hist"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.hist()</span></tt></a> <em>color</em> kwarg now accepts
a sequence of color specs to match a sequence of datasets.</li>
<li>The <a class="reference internal" href="collections_api.html#matplotlib.collections.EllipseCollection" title="matplotlib.collections.EllipseCollection"><tt class="xref py py-class docutils literal"><span class="pre">EllipseCollection</span></tt></a> has been
changed in two ways:<ul>
<li>There is a new <em>units</em> option, ‘xy’, that scales the ellipse with
the data units. This matches the :class:’~matplotlib.patches.Ellipse`
scaling.</li>
<li>The <em>height</em> and <em>width</em> kwargs have been changed to specify
the height and width, again for consistency with
<a class="reference internal" href="artist_api.html#matplotlib.patches.Ellipse" title="matplotlib.patches.Ellipse"><tt class="xref py py-class docutils literal"><span class="pre">Ellipse</span></tt></a>, and to better match
their names; previously they specified the half-height and
half-width.</li>
</ul>
</li>
<li>There is a new rc parameter <tt class="docutils literal"><span class="pre">axes.color_cycle</span></tt>, and the color
cycle is now independent of the rc parameter <tt class="docutils literal"><span class="pre">lines.color</span></tt>.
<tt class="xref py py-func docutils literal"><span class="pre">matplotlib.Axes.set_default_color_cycle()</span></tt> is deprecated.</li>
<li>You can now print several figures to one pdf file and modify the
document information dictionary of a pdf file. See the docstrings
of the class <a class="reference internal" href="backend_pdf_api.html#matplotlib.backends.backend_pdf.PdfPages" title="matplotlib.backends.backend_pdf.PdfPages"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.backends.backend_pdf.PdfPages</span></tt></a> for
more information.</li>
<li>Removed <a class="reference external" href="http://www.voidspace.org.uk/python/configobj.html">configobj</a> and <a class="reference external" href="http://code.enthought.com/projects/traits">enthought.traits</a> packages, which are only
required by the experimental traited config and are somewhat out of
date. If needed, install them independently.</li>
</ul>
<ul>
<li><p class="first">The new rc parameter <tt class="docutils literal"><span class="pre">savefig.extension</span></tt> sets the filename extension
that is used by <a class="reference internal" href="figure_api.html#matplotlib.figure.Figure.savefig" title="matplotlib.figure.Figure.savefig"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.figure.Figure.savefig()</span></tt></a> if its <em>fname</em>
argument lacks an extension.</p>
</li>
<li><p class="first">In an effort to simplify the backend API, all clipping rectangles
and paths are now passed in using GraphicsContext objects, even
on collections and images. Therefore:</p>
<div class="highlight-python"><div class="highlight"><pre><span class="n">draw_path_collection</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">master_transform</span><span class="p">,</span> <span class="n">cliprect</span><span class="p">,</span> <span class="n">clippath</span><span class="p">,</span>
<span class="n">clippath_trans</span><span class="p">,</span> <span class="n">paths</span><span class="p">,</span> <span class="n">all_transforms</span><span class="p">,</span> <span class="n">offsets</span><span class="p">,</span>
<span class="n">offsetTrans</span><span class="p">,</span> <span class="n">facecolors</span><span class="p">,</span> <span class="n">edgecolors</span><span class="p">,</span> <span class="n">linewidths</span><span class="p">,</span>
<span class="n">linestyles</span><span class="p">,</span> <span class="n">antialiaseds</span><span class="p">,</span> <span class="n">urls</span><span class="p">)</span>
<span class="c"># is now</span>
<span class="n">draw_path_collection</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gc</span><span class="p">,</span> <span class="n">master_transform</span><span class="p">,</span> <span class="n">paths</span><span class="p">,</span> <span class="n">all_transforms</span><span class="p">,</span>
<span class="n">offsets</span><span class="p">,</span> <span class="n">offsetTrans</span><span class="p">,</span> <span class="n">facecolors</span><span class="p">,</span> <span class="n">edgecolors</span><span class="p">,</span>
<span class="n">linewidths</span><span class="p">,</span> <span class="n">linestyles</span><span class="p">,</span> <span class="n">antialiaseds</span><span class="p">,</span> <span class="n">urls</span><span class="p">)</span>
<span class="n">draw_quad_mesh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">master_transform</span><span class="p">,</span> <span class="n">cliprect</span><span class="p">,</span> <span class="n">clippath</span><span class="p">,</span>
<span class="n">clippath_trans</span><span class="p">,</span> <span class="n">meshWidth</span><span class="p">,</span> <span class="n">meshHeight</span><span class="p">,</span> <span class="n">coordinates</span><span class="p">,</span>
<span class="n">offsets</span><span class="p">,</span> <span class="n">offsetTrans</span><span class="p">,</span> <span class="n">facecolors</span><span class="p">,</span> <span class="n">antialiased</span><span class="p">,</span>
<span class="n">showedges</span><span class="p">)</span>
<span class="c"># is now</span>
<span class="n">draw_quad_mesh</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gc</span><span class="p">,</span> <span class="n">master_transform</span><span class="p">,</span> <span class="n">meshWidth</span><span class="p">,</span> <span class="n">meshHeight</span><span class="p">,</span>
<span class="n">coordinates</span><span class="p">,</span> <span class="n">offsets</span><span class="p">,</span> <span class="n">offsetTrans</span><span class="p">,</span> <span class="n">facecolors</span><span class="p">,</span>
<span class="n">antialiased</span><span class="p">,</span> <span class="n">showedges</span><span class="p">)</span>
<span class="n">draw_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">im</span><span class="p">,</span> <span class="n">bbox</span><span class="p">,</span> <span class="n">clippath</span><span class="o">=</span><span class="bp">None</span><span class="p">,</span> <span class="n">clippath_trans</span><span class="o">=</span><span class="bp">None</span><span class="p">)</span>
<span class="c"># is now</span>
<span class="n">draw_image</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">gc</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">im</span><span class="p">)</span>
</pre></div>
</div>
</li>
<li><p class="first">There are four new Axes methods with corresponding pyplot
functions that deal with unstructured triangular grids:</p>
<ul class="simple">
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.tricontour" title="matplotlib.axes.Axes.tricontour"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.tricontour()</span></tt></a> draws contour lines
on a triangular grid.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.tricontourf" title="matplotlib.axes.Axes.tricontourf"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.tricontourf()</span></tt></a> draws filled contours
on a triangular grid.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.tripcolor" title="matplotlib.axes.Axes.tripcolor"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.tripcolor()</span></tt></a> draws a pseudocolor
plot on a triangular grid.</li>
<li><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.triplot" title="matplotlib.axes.Axes.triplot"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.triplot()</span></tt></a> draws a triangular grid
as lines and/or markers.</li>
</ul>
</li>
</ul>
</div>
<div class="section" id="changes-in-0-99">
<h2>Changes in 0.99<a class="headerlink" href="#changes-in-0-99" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>pylab no longer provides a load and save function. These are
available in matplotlib.mlab, or you can use numpy.loadtxt and
numpy.savetxt for text files, or np.save and np.load for binary
numpy arrays.</li>
<li>User-generated colormaps can now be added to the set recognized
by <a class="reference internal" href="cm_api.html#matplotlib.cm.get_cmap" title="matplotlib.cm.get_cmap"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.cm.get_cmap()</span></tt></a>. Colormaps can be made the
default and applied to the current image using
<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.set_cmap" title="matplotlib.pyplot.set_cmap"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.set_cmap()</span></tt></a>.</li>
<li>changed use_mrecords default to False in mlab.csv2rec since this is
partially broken</li>
<li>Axes instances no longer have a “frame” attribute. Instead, use the
new “spines” attribute. Spines is a dictionary where the keys are
the names of the spines (e.g. ‘left’,’right’ and so on) and the
values are the artists that draw the spines. For normal
(rectilinear) axes, these artists are Line2D instances. For other
axes (such as polar axes), these artists may be Patch instances.</li>
<li>Polar plots no longer accept a resolution kwarg. Instead, each Path
must specify its own number of interpolation steps. This is
unlikely to be a user-visible change – if interpolation of data is
required, that should be done before passing it to matplotlib.</li>
</ul>
</div>
<div class="section" id="changes-for-0-98-x">
<h2>Changes for 0.98.x<a class="headerlink" href="#changes-for-0-98-x" title="Permalink to this headline">¶</a></h2>
<ul>
<li><p class="first">psd(), csd(), and cohere() will now automatically wrap negative
frequency components to the beginning of the returned arrays.
This is much more sensible behavior and makes them consistent
with specgram(). The previous behavior was more of an oversight
than a design decision.</p>
</li>
<li><p class="first">Added new keyword parameters <em>nonposx</em>, <em>nonposy</em> to
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.axes.Axes</span></tt></a> methods that set log scale
parameters. The default is still to mask out non-positive
values, but the kwargs accept ‘clip’, which causes non-positive
values to be replaced with a very small positive value.</p>
</li>
<li><p class="first">Added new <tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.fignum_exists()</span></tt> and
<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.get_fignums" title="matplotlib.pyplot.get_fignums"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.get_fignums()</span></tt></a>; they merely expose
information that had been hidden in <tt class="xref py py-mod docutils literal"><span class="pre">matplotlib._pylab_helpers</span></tt>.</p>
</li>
<li><p class="first">Deprecated numerix package.</p>
</li>
<li><p class="first">Added new <tt class="xref py py-func docutils literal"><span class="pre">matplotlib.image.imsave()</span></tt> and exposed it to the
<a class="reference internal" href="pyplot_api.html#module-matplotlib.pyplot" title="matplotlib.pyplot"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.pyplot</span></tt></a> interface.</p>
</li>
<li><p class="first">Remove support for pyExcelerator in exceltools – use xlwt
instead</p>
</li>
<li><p class="first">Changed the defaults of acorr and xcorr to use usevlines=True,
maxlags=10 and normed=True since these are the best defaults</p>
</li>
<li><p class="first">Following keyword parameters for <tt class="xref py py-class docutils literal"><span class="pre">matplotlib.label.Label</span></tt> are now
deprecated and new set of parameters are introduced. The new parameters
are given as a fraction of the font-size. Also, <em>scatteryoffsets</em>,
<em>fancybox</em> and <em>columnspacing</em> are added as keyword parameters.</p>
<blockquote>
<div><table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head"><p class="first last">Deprecated</p>
</th>
<th class="head"><p class="first last">New</p>
</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><p class="first last">pad</p>
</td>
<td><p class="first last">borderpad</p>
</td>
</tr>
<tr class="row-odd"><td><p class="first last">labelsep</p>
</td>
<td><p class="first last">labelspacing</p>
</td>
</tr>
<tr class="row-even"><td><p class="first last">handlelen</p>
</td>
<td><p class="first last">handlelength</p>
</td>
</tr>
<tr class="row-odd"><td><p class="first last">handlestextsep</p>
</td>
<td><p class="first last">handletextpad</p>
</td>
</tr>
<tr class="row-even"><td><p class="first last">axespad</p>
</td>
<td><p class="first last">borderaxespad</p>
</td>
</tr>
</tbody>
</table>
</div></blockquote>
</li>
<li><p class="first">Removed the configobj and experimental traits rc support</p>
</li>
<li><p class="first">Modified <a class="reference internal" href="mlab_api.html#matplotlib.mlab.psd" title="matplotlib.mlab.psd"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.mlab.psd()</span></tt></a>, <a class="reference internal" href="mlab_api.html#matplotlib.mlab.csd" title="matplotlib.mlab.csd"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.mlab.csd()</span></tt></a>,
<a class="reference internal" href="mlab_api.html#matplotlib.mlab.cohere" title="matplotlib.mlab.cohere"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.mlab.cohere()</span></tt></a>, and <a class="reference internal" href="mlab_api.html#matplotlib.mlab.specgram" title="matplotlib.mlab.specgram"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.mlab.specgram()</span></tt></a>
to scale one-sided densities by a factor of 2. Also, optionally
scale the densities by the sampling frequency, which gives true values
of densities that can be integrated by the returned frequency values.
This also gives better MATLAB compatibility. The corresponding
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.axes.Axes</span></tt></a> methods and <a class="reference internal" href="pyplot_api.html#module-matplotlib.pyplot" title="matplotlib.pyplot"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.pyplot</span></tt></a>
functions were updated as well.</p>
</li>
<li><p class="first">Font lookup now uses a nearest-neighbor approach rather than an
exact match. Some fonts may be different in plots, but should be
closer to what was requested.</p>
</li>
<li><p class="first"><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_xlim" title="matplotlib.axes.Axes.set_xlim"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_xlim()</span></tt></a>,
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_ylim" title="matplotlib.axes.Axes.set_ylim"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_ylim()</span></tt></a> now return a copy of the
<tt class="xref py py-attr docutils literal"><span class="pre">viewlim</span></tt> array to avoid modify-in-place surprises.</p>
</li>
<li><p class="first"><a class="reference internal" href="afm_api.html#matplotlib.afm.AFM.get_fullname" title="matplotlib.afm.AFM.get_fullname"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.afm.AFM.get_fullname()</span></tt></a> and
<a class="reference internal" href="afm_api.html#matplotlib.afm.AFM.get_familyname" title="matplotlib.afm.AFM.get_familyname"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.afm.AFM.get_familyname()</span></tt></a> no longer raise an
exception if the AFM file does not specify these optional
attributes, but returns a guess based on the required FontName
attribute.</p>
</li>
<li><p class="first">Changed precision kwarg in <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.spy" title="matplotlib.pyplot.spy"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.spy()</span></tt></a>; default is
0, and the string value ‘present’ is used for sparse arrays only to
show filled locations.</p>
</li>
<li><p class="first"><a class="reference internal" href="collections_api.html#matplotlib.collections.EllipseCollection" title="matplotlib.collections.EllipseCollection"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.collections.EllipseCollection</span></tt></a> added.</p>
</li>
<li><p class="first">Added <tt class="docutils literal"><span class="pre">angles</span></tt> kwarg to <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.quiver" title="matplotlib.pyplot.quiver"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.quiver()</span></tt></a> for more
flexible specification of the arrow angles.</p>
</li>
<li><p class="first">Deprecated (raise NotImplementedError) all the mlab2 functions from
<a class="reference internal" href="mlab_api.html#module-matplotlib.mlab" title="matplotlib.mlab"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.mlab</span></tt></a> out of concern that some of them were not
clean room implementations.</p>
</li>
<li><p class="first">Methods <a class="reference internal" href="collections_api.html#matplotlib.collections.Collection.get_offsets" title="matplotlib.collections.Collection.get_offsets"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.collections.Collection.get_offsets()</span></tt></a> and
<a class="reference internal" href="collections_api.html#matplotlib.collections.Collection.set_offsets" title="matplotlib.collections.Collection.set_offsets"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.collections.Collection.set_offsets()</span></tt></a> added to
<a class="reference internal" href="collections_api.html#matplotlib.collections.Collection" title="matplotlib.collections.Collection"><tt class="xref py py-class docutils literal"><span class="pre">Collection</span></tt></a> base class.</p>
</li>
<li><p class="first"><tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.figure.Figure.figurePatch</span></tt> renamed
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.figure.Figure.patch</span></tt>;
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.axesPatch</span></tt> renamed
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.patch</span></tt>;
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.axesFrame</span></tt> renamed
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.frame" title="matplotlib.axes.Axes.frame"><tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.frame</span></tt></a>.
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.get_frame" title="matplotlib.axes.Axes.get_frame"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.get_frame()</span></tt></a>, which returns
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.axes.Axes.patch</span></tt>, is deprecated.</p>
</li>
<li><p class="first">Changes in the <tt class="xref py py-class docutils literal"><span class="pre">matplotlib.contour.ContourLabeler</span></tt> attributes
(<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.clabel" title="matplotlib.pyplot.clabel"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.pyplot.clabel()</span></tt></a> function) so that they all have a
form like <tt class="docutils literal"><span class="pre">.labelAttribute</span></tt>. The three attributes that are most
likely to be used by end users, <tt class="docutils literal"><span class="pre">.cl</span></tt>, <tt class="docutils literal"><span class="pre">.cl_xy</span></tt> and
<tt class="docutils literal"><span class="pre">.cl_cvalues</span></tt> have been maintained for the moment (in addition to
their renamed versions), but they are deprecated and will eventually
be removed.</p>
</li>
<li><p class="first">Moved several functions in <a class="reference internal" href="mlab_api.html#module-matplotlib.mlab" title="matplotlib.mlab"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.mlab</span></tt></a> and
<a class="reference internal" href="cbook_api.html#module-matplotlib.cbook" title="matplotlib.cbook"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.cbook</span></tt></a> into a separate module
<tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.numerical_methods</span></tt> because they were unrelated to
the initial purpose of mlab or cbook and appeared more coherent
elsewhere.</p>
</li>
</ul>
</div>
<div class="section" id="changes-for-0-98-1">
<h2>Changes for 0.98.1<a class="headerlink" href="#changes-for-0-98-1" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>Removed broken <tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.axes3d</span></tt> support and replaced it with
a non-implemented error pointing to 0.91.x</li>
</ul>
</div>
<div class="section" id="changes-for-0-98-0">
<h2>Changes for 0.98.0<a class="headerlink" href="#changes-for-0-98-0" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.image.imread()</span></tt> now no longer always returns RGBA data—if
the image is luminance or RGB, it will return a MxN or MxNx3 array
if possible. Also uint8 is no longer always forced to float.</li>
<li>Rewrote the <a class="reference internal" href="cm_api.html#matplotlib.cm.ScalarMappable" title="matplotlib.cm.ScalarMappable"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.cm.ScalarMappable</span></tt></a> callback
infrastructure to use <a class="reference internal" href="cbook_api.html#matplotlib.cbook.CallbackRegistry" title="matplotlib.cbook.CallbackRegistry"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.cbook.CallbackRegistry</span></tt></a>
rather than custom callback handling. Any users of
<tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.cm.ScalarMappable.add_observer()</span></tt> of the
<a class="reference internal" href="cm_api.html#matplotlib.cm.ScalarMappable" title="matplotlib.cm.ScalarMappable"><tt class="xref py py-class docutils literal"><span class="pre">ScalarMappable</span></tt></a> should use the
<tt class="xref py py-attr docutils literal"><span class="pre">matplotlib.cm.ScalarMappable.callbacks</span></tt>
<a class="reference internal" href="cbook_api.html#matplotlib.cbook.CallbackRegistry" title="matplotlib.cbook.CallbackRegistry"><tt class="xref py py-class docutils literal"><span class="pre">CallbackRegistry</span></tt></a> instead.</li>
<li>New axes function and Axes method provide control over the plot
color cycle: <a class="reference internal" href="axes_api.html#matplotlib.axes.set_default_color_cycle" title="matplotlib.axes.set_default_color_cycle"><tt class="xref py py-func docutils literal"><span class="pre">matplotlib.axes.set_default_color_cycle()</span></tt></a> and
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_color_cycle" title="matplotlib.axes.Axes.set_color_cycle"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_color_cycle()</span></tt></a>.</li>
<li>matplotlib now requires Python 2.4, so <a class="reference internal" href="cbook_api.html#module-matplotlib.cbook" title="matplotlib.cbook"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.cbook</span></tt></a> will
no longer provide <tt class="xref py py-class docutils literal"><span class="pre">set</span></tt>, <tt class="xref py py-func docutils literal"><span class="pre">enumerate()</span></tt>, <tt class="xref py py-func docutils literal"><span class="pre">reversed()</span></tt>
or <tt class="xref py py-func docutils literal"><span class="pre">izip()</span></tt> compatibility functions.</li>
<li>In Numpy 1.0, bins are specified by the left edges only. The axes
method <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.hist" title="matplotlib.axes.Axes.hist"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.hist()</span></tt></a> now uses future Numpy 1.3
semantics for histograms. Providing <tt class="docutils literal"><span class="pre">binedges</span></tt>, the last value gives
the upper-right edge now, which was implicitly set to +infinity in
Numpy 1.0. This also means that the last bin doesn’t contain upper
outliers any more by default.</li>
<li>New axes method and pyplot function,
<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.hexbin" title="matplotlib.pyplot.hexbin"><tt class="xref py py-func docutils literal"><span class="pre">hexbin()</span></tt></a>, is an alternative to
<a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.scatter" title="matplotlib.pyplot.scatter"><tt class="xref py py-func docutils literal"><span class="pre">scatter()</span></tt></a> for large datasets. It makes
something like a <a class="reference internal" href="pyplot_api.html#matplotlib.pyplot.pcolor" title="matplotlib.pyplot.pcolor"><tt class="xref py py-func docutils literal"><span class="pre">pcolor()</span></tt></a> of a 2-D
histogram, but uses hexagonal bins.</li>
<li>New kwarg, <tt class="docutils literal"><span class="pre">symmetric</span></tt>, in <a class="reference internal" href="ticker_api.html#matplotlib.ticker.MaxNLocator" title="matplotlib.ticker.MaxNLocator"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.ticker.MaxNLocator</span></tt></a>
allows one require an axis to be centered around zero.</li>
<li>Toolkits must now be imported from <tt class="docutils literal"><span class="pre">mpl_toolkits</span></tt> (not <tt class="docutils literal"><span class="pre">matplotlib.toolkits</span></tt>)</li>
</ul>
<div class="section" id="notes-about-the-transforms-refactoring">
<h3>Notes about the transforms refactoring<a class="headerlink" href="#notes-about-the-transforms-refactoring" title="Permalink to this headline">¶</a></h3>
<p>A major new feature of the 0.98 series is a more flexible and
extensible transformation infrastructure, written in Python/Numpy
rather than a custom C extension.</p>
<p>The primary goal of this refactoring was to make it easier to
extend matplotlib to support new kinds of projections. This is
mostly an internal improvement, and the possible user-visible
changes it allows are yet to come.</p>
<p>See <a class="reference internal" href="../devel/transformations.html#module-matplotlib.transforms" title="matplotlib.transforms"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.transforms</span></tt></a> for a description of the design of
the new transformation framework.</p>
<p>For efficiency, many of these functions return views into Numpy
arrays. This means that if you hold on to a reference to them,
their contents may change. If you want to store a snapshot of
their current values, use the Numpy array method copy().</p>
<p>The view intervals are now stored only in one place – in the
<a class="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.axes.Axes</span></tt></a> instance, not in the locator instances
as well. This means locators must get their limits from their
<a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.axis.Axis</span></tt></a>, which in turn looks up its limits from
the <a class="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><tt class="xref py py-class docutils literal"><span class="pre">Axes</span></tt></a>. If a locator is used temporarily
and not assigned to an Axis or Axes, (e.g. in
<tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.contour</span></tt>), a dummy axis must be created to store its
bounds. Call <tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.ticker.Locator.create_dummy_axis()</span></tt> to
do so.</p>
<p>The functionality of <tt class="xref py py-class docutils literal"><span class="pre">Pbox</span></tt> has been merged with
<a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a>. Its methods now all return
copies rather than modifying in place.</p>
<p>The following lists many of the simple changes necessary to update
code from the old transformation framework to the new one. In
particular, methods that return a copy are named with a verb in the
past tense, whereas methods that alter an object in place are named
with a verb in the present tense.</p>
<div class="section" id="matplotlib-transforms">
<h4><a class="reference internal" href="../devel/transformations.html#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="#matplotlib-transforms" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.get_bounds()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.bounds</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.width()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.width</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.height()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.height</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.intervalx().get_bounds()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.intervalx</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.intervalx().set_bounds()</span></tt></td>
<td>[<tt class="xref py py-attr docutils literal"><span class="pre">Bbox.intervalx</span></tt> is now a property.]</td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.intervaly().get_bounds()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.intervaly</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.intervaly().set_bounds()</span></tt></td>
<td>[<tt class="xref py py-attr docutils literal"><span class="pre">Bbox.intervaly</span></tt> is now a property.]</td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.xmin()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.x0</span></tt> or
<tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.xmin</span></tt> <a class="footnote-reference" href="#id5" id="id1">[1]</a></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.ymin()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.y0</span></tt> or
<tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.ymin</span></tt> <a class="footnote-reference" href="#id5" id="id2">[1]</a></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.xmax()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.x1</span></tt> or
<tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.xmax</span></tt> <a class="footnote-reference" href="#id5" id="id3">[1]</a></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-meth docutils literal"><span class="pre">Bbox.ymax()</span></tt></td>
<td><tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.y1</span></tt> or
<tt class="xref py py-attr docutils literal"><span class="pre">transforms.Bbox.ymax</span></tt> <a class="footnote-reference" href="#id5" id="id4">[1]</a></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.overlaps(bboxes)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.count_overlaps(bboxes)</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">bbox_all(bboxes)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.union(bboxes)</span></tt>
[<tt class="xref py py-meth docutils literal"><span class="pre">transforms.Bbox.union()</span></tt> is a staticmethod.]</td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">lbwh_to_bbox(l,</span> <span class="pre">b,</span> <span class="pre">w,</span> <span class="pre">h)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.from_bounds(x0,</span> <span class="pre">y0,</span> <span class="pre">w,</span> <span class="pre">h)</span></tt>
[<tt class="xref py py-meth docutils literal"><span class="pre">transforms.Bbox.from_bounds()</span></tt> is a staticmethod.]</td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">inverse_transform_bbox(trans,</span> <span class="pre">bbox)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Bbox.inverse_transformed(trans)</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Interval.contains_open(v)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">interval_contains_open(tuple,</span> <span class="pre">v)</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Interval.contains(v)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">interval_contains(tuple,</span> <span class="pre">v)</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">identity_transform()</span></tt></td>
<td><a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.IdentityTransform" title="matplotlib.transforms.IdentityTransform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.IdentityTransform</span></tt></a></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">blend_xy_sep_transform(xtrans,</span> <span class="pre">ytrans)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">blended_transform_factory(xtrans,</span> <span class="pre">ytrans)</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">scale_transform(xs,</span> <span class="pre">ys)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Affine2D().scale(xs[,</span> <span class="pre">ys])</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">get_bbox_transform(boxin,</span> <span class="pre">boxout)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">BboxTransform(boxin,</span> <span class="pre">boxout)</span></tt> or
<tt class="xref py py-obj docutils literal"><span class="pre">BboxTransformFrom(boxin)</span></tt> or
<tt class="xref py py-obj docutils literal"><span class="pre">BboxTransformTo(boxout)</span></tt></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Transform.seq_xy_tup(points)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Transform.transform(points)</span></tt></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Transform.inverse_xy_tup(points)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Transform.inverted().transform(points)</span></tt></td>
</tr>
</tbody>
</table>
<table class="docutils footnote" frame="void" id="id5" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label">[1]</td><td><em>(<a class="fn-backref" href="#id1">1</a>, <a class="fn-backref" href="#id2">2</a>, <a class="fn-backref" href="#id3">3</a>, <a class="fn-backref" href="#id4">4</a>)</em> The <a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt></a> is bound by the points
(x0, y0) to (x1, y1) and there is no defined order to these points,
that is, x0 is not necessarily the left edge of the box. To get
the left edge of the <tt class="xref py py-class docutils literal"><span class="pre">Bbox</span></tt>, use the read-only property
<tt class="xref py py-attr docutils literal"><span class="pre">xmin</span></tt>.</td></tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-axes">
<h4><a class="reference internal" href="axes_api.html#module-matplotlib.axes" title="matplotlib.axes"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.axes</span></tt></a><a class="headerlink" href="#matplotlib-axes" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Axes.get_position()</span></tt></td>
<td><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.get_position" title="matplotlib.axes.Axes.get_position"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.get_position()</span></tt></a> <a class="footnote-reference" href="#id9" id="id6">[2]</a></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Axes.set_position()</span></tt></td>
<td><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_position" title="matplotlib.axes.Axes.set_position"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_position()</span></tt></a> <a class="footnote-reference" href="#id10" id="id7">[3]</a></td>
</tr>
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Axes.toggle_log_lineary()</span></tt></td>
<td><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_yscale" title="matplotlib.axes.Axes.set_yscale"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_yscale()</span></tt></a> <a class="footnote-reference" href="#id11" id="id8">[4]</a></td>
</tr>
<tr class="row-odd"><td><tt class="xref py py-obj docutils literal"><span class="pre">Subplot</span></tt> class</td>
<td>removed.</td>
</tr>
</tbody>
</table>
<p>The <tt class="xref py py-class docutils literal"><span class="pre">Polar</span></tt> class has moved to <a class="reference internal" href="../devel/add_new_projection.html#module-matplotlib.projections.polar" title="matplotlib.projections.polar"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.projections.polar</span></tt></a>.</p>
<table class="docutils footnote" frame="void" id="id9" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id6">[2]</a></td><td><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.get_position" title="matplotlib.axes.Axes.get_position"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.get_position()</span></tt></a> used to return a list
of points, now it returns a <a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Bbox</span></tt></a>
instance.</td></tr>
</tbody>
</table>
<table class="docutils footnote" frame="void" id="id10" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id7">[3]</a></td><td><a class="reference internal" href="axes_api.html#matplotlib.axes.Axes.set_position" title="matplotlib.axes.Axes.set_position"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.axes.Axes.set_position()</span></tt></a> now accepts either
four scalars or a <a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.Bbox" title="matplotlib.transforms.Bbox"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Bbox</span></tt></a> instance.</td></tr>
</tbody>
</table>
<table class="docutils footnote" frame="void" id="id11" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id8">[4]</a></td><td>Since the recfactoring allows for more than two scale types
(‘log’ or ‘linear’), it no longer makes sense to have a toggle.
<tt class="xref py py-obj docutils literal"><span class="pre">Axes.toggle_log_lineary()</span></tt> has been removed.</td></tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-artist">
<h4><a class="reference internal" href="artist_api.html#module-matplotlib.artist" title="matplotlib.artist"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.artist</span></tt></a><a class="headerlink" href="#matplotlib-artist" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Artist.set_clip_path(path)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">Artist.set_clip_path(path,</span> <span class="pre">transform)</span></tt> <a class="footnote-reference" href="#id13" id="id12">[5]</a></td>
</tr>
</tbody>
</table>
<table class="docutils footnote" frame="void" id="id13" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id12">[5]</a></td><td><a class="reference internal" href="artist_api.html#matplotlib.artist.Artist.set_clip_path" title="matplotlib.artist.Artist.set_clip_path"><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.artist.Artist.set_clip_path()</span></tt></a> now accepts a
<a class="reference internal" href="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> instance and a
<a class="reference internal" href="../devel/transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><tt class="xref py py-class docutils literal"><span class="pre">matplotlib.transforms.Transform</span></tt></a> that will be applied to
the path immediately before clipping.</td></tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-collections">
<h4><a class="reference internal" href="collections_api.html#module-matplotlib.collections" title="matplotlib.collections"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.collections</span></tt></a><a class="headerlink" href="#matplotlib-collections" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">linestyle</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">linestyles</span></tt> <a class="footnote-reference" href="#id15" id="id14">[6]</a></td>
</tr>
</tbody>
</table>
<table class="docutils footnote" frame="void" id="id15" rules="none">
<colgroup><col class="label" /><col /></colgroup>
<tbody valign="top">
<tr><td class="label"><a class="fn-backref" href="#id14">[6]</a></td><td>Linestyles are now treated like all other collection
attributes, i.e. a single value or multiple values may be
provided.</td></tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-colors">
<h4><a class="reference internal" href="colors_api.html#module-matplotlib.colors" title="matplotlib.colors"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.colors</span></tt></a><a class="headerlink" href="#matplotlib-colors" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">ColorConvertor.to_rgba_list(c)</span></tt></td>
<td><tt class="xref py py-obj docutils literal"><span class="pre">ColorConvertor.to_rgba_array(c)</span></tt>
[<tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.colors.ColorConvertor.to_rgba_array()</span></tt>
returns an Nx4 Numpy array of RGBA color quadruples.]</td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-contour">
<h4><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.contour</span></tt><a class="headerlink" href="#matplotlib-contour" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><tt class="xref py py-obj docutils literal"><span class="pre">Contour._segments</span></tt></td>
<td><tt class="xref py py-meth docutils literal"><span class="pre">matplotlib.contour.Contour.get_paths`()</span></tt> [Returns a
list of <a class="reference internal" href="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> instances.]</td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="matplotlib-figure">
<h4><a class="reference internal" href="figure_api.html#module-matplotlib.figure" title="matplotlib.figure"><tt class="xref py py-mod docutils literal"><span class="pre">matplotlib.figure</span></tt></a><a class="headerlink" href="#matplotlib-figure" title="Permalink to this headline">¶</a></h4>
<table border="1" class="docutils">
<colgroup>
<col width="50%" />
<col width="50%" />
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head">Old method</th>
<th class="head">New method</th>
</tr>
You can’t perform that action at this time.