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<h1>API Changes in 2.1.0<a class="headerlink" href="#api-changes-in-2-1-0" title="Link to this heading">#</a></h1>
<section id="default-behavior-of-log-scales-changed-to-mask-0-values">
<h2>Default behavior of log scales changed to mask <= 0 values<a class="headerlink" href="#default-behavior-of-log-scales-changed-to-mask-0-values" title="Link to this heading">#</a></h2>
<p>Calling <a class="reference internal" href="../_as_gen/matplotlib.axes.Axes.set_xscale.html#matplotlib.axes.Axes.set_xscale" title="matplotlib.axes.Axes.set_xscale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.axes.Axes.set_xscale</span></code></a> or <a class="reference internal" href="../_as_gen/matplotlib.axes.Axes.set_yscale.html#matplotlib.axes.Axes.set_yscale" title="matplotlib.axes.Axes.set_yscale"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.axes.Axes.set_yscale</span></code></a>
now uses 'mask' as the default method to handle invalid values (as opposed to
'clip'). This means that any values <= 0 on a log scale will not be shown.</p>
<p>Previously they were clipped to a very small number and shown.</p>
</section>
<section id="matplotlib-cbook-callbackregistry-process-suppresses-exceptions-by-default">
<h2><a class="reference internal" href="../cbook_api.html#matplotlib.cbook.CallbackRegistry.process" title="matplotlib.cbook.CallbackRegistry.process"><code class="xref py py-meth docutils literal notranslate"><span class="pre">matplotlib.cbook.CallbackRegistry.process()</span></code></a> suppresses exceptions by default<a class="headerlink" href="#matplotlib-cbook-callbackregistry-process-suppresses-exceptions-by-default" title="Link to this heading">#</a></h2>
<p>Matplotlib uses instances of <a class="reference internal" href="../cbook_api.html#matplotlib.cbook.CallbackRegistry" title="matplotlib.cbook.CallbackRegistry"><code class="xref py py-obj docutils literal notranslate"><span class="pre">CallbackRegistry</span></code></a>
as a bridge between user input event from the GUI and user callbacks.
Previously, any exceptions raised in a user call back would bubble out
of the <code class="docutils literal notranslate"><span class="pre">process</span></code> method, which is typically in the GUI event
loop. Most GUI frameworks simple print the traceback to the screen
and continue as there is not always a clear method of getting the
exception back to the user. However PyQt5 now exits the process when
it receives an un-handled python exception in the event loop. Thus,
<a class="reference internal" href="../cbook_api.html#matplotlib.cbook.CallbackRegistry.process" title="matplotlib.cbook.CallbackRegistry.process"><code class="xref py py-meth docutils literal notranslate"><span class="pre">process()</span></code></a> now suppresses and
prints tracebacks to stderr by default.</p>
<p>What <a class="reference internal" href="../cbook_api.html#matplotlib.cbook.CallbackRegistry.process" title="matplotlib.cbook.CallbackRegistry.process"><code class="xref py py-meth docutils literal notranslate"><span class="pre">process()</span></code></a> does with exceptions
is now user configurable via the <code class="docutils literal notranslate"><span class="pre">exception_handler</span></code> attribute and kwarg. To
restore the previous behavior pass <code class="docutils literal notranslate"><span class="pre">None</span></code></p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">cb</span> <span class="o">=</span> <span class="n">CallbackRegistry</span><span class="p">(</span><span class="n">exception_handler</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
</pre></div>
</div>
<p>A function which take and <code class="docutils literal notranslate"><span class="pre">Exception</span></code> as its only argument may also be passed</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">maybe_reraise</span><span class="p">(</span><span class="n">exc</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">exc</span><span class="p">,</span> <span class="ne">RuntimeError</span><span class="p">):</span>
<span class="k">pass</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="n">exc</span>
<span class="n">cb</span> <span class="o">=</span> <span class="n">CallbackRegistry</span><span class="p">(</span><span class="n">exception_handler</span><span class="o">=</span><span class="n">maybe_reraise</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="improved-toggling-of-the-axes-grids">
<h2>Improved toggling of the axes grids<a class="headerlink" href="#improved-toggling-of-the-axes-grids" title="Link to this heading">#</a></h2>
<p>The <code class="docutils literal notranslate"><span class="pre">g</span></code> key binding now switches the states of the <code class="docutils literal notranslate"><span class="pre">x</span></code> and <code class="docutils literal notranslate"><span class="pre">y</span></code> grids
independently (by cycling through all four on/off combinations).</p>
<p>The new <code class="docutils literal notranslate"><span class="pre">G</span></code> key binding switches the states of the minor grids.</p>
<p>Both bindings are disabled if only a subset of the grid lines (in either
direction) is visible, to avoid making irreversible changes to the figure.</p>
</section>
<section id="ticklabels-are-turned-off-instead-of-being-invisible">
<h2>Ticklabels are turned off instead of being invisible<a class="headerlink" href="#ticklabels-are-turned-off-instead-of-being-invisible" title="Link to this heading">#</a></h2>
<p>Internally, the <a class="reference internal" href="../axis_api.html#matplotlib.axis.Tick" title="matplotlib.axis.Tick"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Tick</span></code></a>'s <code class="docutils literal notranslate"><span class="pre">~matplotlib.axis.Tick.label1On</span></code> attribute
is now used to hide tick labels instead of setting the visibility on the tick
label objects.
This improves overall performance and fixes some issues.
As a consequence, in case those labels ought to be shown,
<a class="reference internal" href="../_as_gen/matplotlib.axes.Axes.tick_params.html#matplotlib.axes.Axes.tick_params" title="matplotlib.axes.Axes.tick_params"><code class="xref py py-func docutils literal notranslate"><span class="pre">tick_params()</span></code></a>
needs to be used, e.g.</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="n">ax</span><span class="o">.</span><span class="n">tick_params</span><span class="p">(</span><span class="n">labelbottom</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="removal-of-warning-on-empty-legends">
<h2>Removal of warning on empty legends<a class="headerlink" href="#removal-of-warning-on-empty-legends" title="Link to this heading">#</a></h2>
<p><a class="reference internal" href="../_as_gen/matplotlib.pyplot.legend.html#matplotlib.pyplot.legend" title="matplotlib.pyplot.legend"><code class="xref py py-obj docutils literal notranslate"><span class="pre">pyplot.legend</span></code></a> used to issue a warning when no labeled artist could be
found. This warning has been removed.</p>
</section>
<section id="more-accurate-legend-autopositioning">
<h2>More accurate legend autopositioning<a class="headerlink" href="#more-accurate-legend-autopositioning" title="Link to this heading">#</a></h2>
<p>Automatic positioning of legends now prefers using the area surrounded
by a <a class="reference internal" href="../_as_gen/matplotlib.lines.Line2D.html#matplotlib.lines.Line2D" title="matplotlib.lines.Line2D"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Line2D</span></code></a> rather than placing the legend over the line itself.</p>
</section>
<section id="cleanup-of-stock-sample-data">
<h2>Cleanup of stock sample data<a class="headerlink" href="#cleanup-of-stock-sample-data" title="Link to this heading">#</a></h2>
<p>The sample data of stocks has been cleaned up to remove redundancies and
increase portability. The <code class="docutils literal notranslate"><span class="pre">AAPL.dat.gz</span></code>, <code class="docutils literal notranslate"><span class="pre">INTC.dat.gz</span></code> and <code class="docutils literal notranslate"><span class="pre">aapl.csv</span></code>
files have been removed entirely and will also no longer be available from
<a class="reference internal" href="../cbook_api.html#matplotlib.cbook.get_sample_data" title="matplotlib.cbook.get_sample_data"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.cbook.get_sample_data</span></code></a>. If a CSV file is required, we suggest using
the <code class="docutils literal notranslate"><span class="pre">msft.csv</span></code> that continues to be shipped in the sample data. If a NumPy
binary file is acceptable, we suggest using one of the following two new files.
The <code class="docutils literal notranslate"><span class="pre">aapl.npy.gz</span></code> and <code class="docutils literal notranslate"><span class="pre">goog.npy</span></code> files have been replaced by <code class="docutils literal notranslate"><span class="pre">aapl.npz</span></code>
and <code class="docutils literal notranslate"><span class="pre">goog.npz</span></code>, wherein the first column's type has changed from
<a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.date" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">datetime.date</span></code></a> to <a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.datetime64" title="(in NumPy v2.3)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.datetime64</span></code></a> for better portability across Python
versions. Note that Matplotlib does not fully support <a class="reference external" href="https://numpy.org/doc/stable/reference/arrays.scalars.html#numpy.datetime64" title="(in NumPy v2.3)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.datetime64</span></code></a> as
yet.</p>
</section>
<section id="updated-qhull-to-2015-2">
<h2>Updated qhull to 2015.2<a class="headerlink" href="#updated-qhull-to-2015-2" title="Link to this heading">#</a></h2>
<p>The version of qhull shipped with Matplotlib, which is used for
Delaunay triangulation, has been updated from version 2012.1 to
2015.2.</p>
</section>
<section id="improved-delaunay-triangulations-with-large-offsets">
<h2>Improved Delaunay triangulations with large offsets<a class="headerlink" href="#improved-delaunay-triangulations-with-large-offsets" title="Link to this heading">#</a></h2>
<p>Delaunay triangulations now deal with large x,y offsets in a better
way. This can cause minor changes to any triangulations calculated
using Matplotlib, i.e. any use of <a class="reference internal" href="../tri_api.html#matplotlib.tri.Triangulation" title="matplotlib.tri.Triangulation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.tri.Triangulation</span></code></a> that
requests that a Delaunay triangulation is calculated, which includes
<a class="reference internal" href="../_as_gen/matplotlib.pyplot.tricontour.html#matplotlib.pyplot.tricontour" title="matplotlib.pyplot.tricontour"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.pyplot.tricontour</span></code></a>, <a class="reference internal" href="../_as_gen/matplotlib.pyplot.tricontourf.html#matplotlib.pyplot.tricontourf" title="matplotlib.pyplot.tricontourf"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.pyplot.tricontourf</span></code></a>,
<a class="reference internal" href="../_as_gen/matplotlib.pyplot.tripcolor.html#matplotlib.pyplot.tripcolor" title="matplotlib.pyplot.tripcolor"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.pyplot.tripcolor</span></code></a>, <a class="reference internal" href="../_as_gen/matplotlib.pyplot.triplot.html#matplotlib.pyplot.triplot" title="matplotlib.pyplot.triplot"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.pyplot.triplot</span></code></a>,
<code class="docutils literal notranslate"><span class="pre">matplotlib.mlab.griddata</span></code> and
<a class="reference internal" href="../_as_gen/mpl_toolkits.mplot3d.axes3d.Axes3D.plot_trisurf.html#mpl_toolkits.mplot3d.axes3d.Axes3D.plot_trisurf" title="mpl_toolkits.mplot3d.axes3d.Axes3D.plot_trisurf"><code class="xref py py-obj docutils literal notranslate"><span class="pre">mpl_toolkits.mplot3d.axes3d.Axes3D.plot_trisurf</span></code></a>.</p>
</section>
<section id="use-backports-functools-lru-cache-instead-of-functools32">
<h2>Use <code class="docutils literal notranslate"><span class="pre">backports.functools_lru_cache</span></code> instead of <code class="docutils literal notranslate"><span class="pre">functools32</span></code><a class="headerlink" href="#use-backports-functools-lru-cache-instead-of-functools32" title="Link to this heading">#</a></h2>
<p>It's better maintained and more widely used (by pylint, jaraco, etc).</p>
</section>
<section id="cbook-is-numlike-only-performs-an-instance-check">
<h2><code class="docutils literal notranslate"><span class="pre">cbook.is_numlike</span></code> only performs an instance check<a class="headerlink" href="#cbook-is-numlike-only-performs-an-instance-check" title="Link to this heading">#</a></h2>
<p><code class="docutils literal notranslate"><span class="pre">matplotlib.cbook.is_numlike</span></code> now only checks that its argument
is an instance of <code class="docutils literal notranslate"><span class="pre">(numbers.Number,</span> <span class="pre">np.Number)</span></code>. In particular,
this means that arrays are now not num-like.</p>
</section>
<section id="elliptical-arcs-now-drawn-between-correct-angles">
<h2>Elliptical arcs now drawn between correct angles<a class="headerlink" href="#elliptical-arcs-now-drawn-between-correct-angles" title="Link to this heading">#</a></h2>
<p>The <a class="reference internal" href="../_as_gen/matplotlib.patches.Arc.html#matplotlib.patches.Arc" title="matplotlib.patches.Arc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.patches.Arc</span></code></a> patch is now correctly drawn between the given
angles.</p>
<p>Previously a circular arc was drawn and then stretched into an ellipse,
so the resulting arc did not lie between <em>theta1</em> and <em>theta2</em>.</p>
</section>
<section id="d-backend-no-longer-sets-the-backend">
<h2><code class="docutils literal notranslate"><span class="pre">-d$backend</span></code> no longer sets the backend<a class="headerlink" href="#d-backend-no-longer-sets-the-backend" title="Link to this heading">#</a></h2>
<p>It is no longer possible to set the backend by passing <code class="docutils literal notranslate"><span class="pre">-d$backend</span></code>
at the command line. Use the <code class="docutils literal notranslate"><span class="pre">MPLBACKEND</span></code> environment variable
instead.</p>
</section>
<section id="path-intersects-bbox-always-treats-the-bounding-box-as-filled">
<h2>Path.intersects_bbox always treats the bounding box as filled<a class="headerlink" href="#path-intersects-bbox-always-treats-the-bounding-box-as-filled" title="Link to this heading">#</a></h2>
<p>Previously, when <code class="docutils literal notranslate"><span class="pre">Path.intersects_bbox</span></code> was called with <code class="docutils literal notranslate"><span class="pre">filled</span></code> set to
<code class="docutils literal notranslate"><span class="pre">False</span></code>, it would treat both the path and the bounding box as unfilled. This
behavior was not well documented and it is usually not the desired behavior,
since bounding boxes are used to represent more complex shapes located inside
the bounding box. This behavior has now been changed: when <code class="docutils literal notranslate"><span class="pre">filled</span></code> is
<code class="docutils literal notranslate"><span class="pre">False</span></code>, the path will be treated as unfilled, but the bounding box is still
treated as filled. The old behavior was arguably an implementation bug.</p>
<p>When <code class="docutils literal notranslate"><span class="pre">Path.intersects_bbox</span></code> is called with <code class="docutils literal notranslate"><span class="pre">filled</span></code> set to <code class="docutils literal notranslate"><span class="pre">True</span></code>
(the default value), there is no change in behavior. For those rare cases where
<code class="docutils literal notranslate"><span class="pre">Path.intersects_bbox</span></code> was called with <code class="docutils literal notranslate"><span class="pre">filled</span></code> set to <code class="docutils literal notranslate"><span class="pre">False</span></code> and where
the old behavior is actually desired, the suggested workaround is to call
<code class="docutils literal notranslate"><span class="pre">Path.intersects_path</span></code> with a rectangle as the path:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span><span class="w"> </span><span class="nn">matplotlib.path</span><span class="w"> </span><span class="kn">import</span> <span class="n">Path</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">matplotlib.transforms</span><span class="w"> </span><span class="kn">import</span> <span class="n">Bbox</span><span class="p">,</span> <span class="n">BboxTransformTo</span>
<span class="n">rect</span> <span class="o">=</span> <span class="n">Path</span><span class="o">.</span><span class="n">unit_rectangle</span><span class="p">()</span><span class="o">.</span><span class="n">transformed</span><span class="p">(</span><span class="n">BboxTransformTo</span><span class="p">(</span><span class="n">bbox</span><span class="p">))</span>
<span class="n">result</span> <span class="o">=</span> <span class="n">path</span><span class="o">.</span><span class="n">intersects_path</span><span class="p">(</span><span class="n">rect</span><span class="p">,</span> <span class="n">filled</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
</pre></div>
</div>
</section>
<section id="wx-no-longer-calls-generates-idleevent-events-or-calls-idle-event">
<h2>WX no longer calls generates <code class="docutils literal notranslate"><span class="pre">IdleEvent</span></code> events or calls <code class="docutils literal notranslate"><span class="pre">idle_event</span></code><a class="headerlink" href="#wx-no-longer-calls-generates-idleevent-events-or-calls-idle-event" title="Link to this heading">#</a></h2>
<p>Removed unused private method <code class="docutils literal notranslate"><span class="pre">_onIdle</span></code> from <code class="docutils literal notranslate"><span class="pre">FigureCanvasWx</span></code>.</p>
<p>The <code class="docutils literal notranslate"><span class="pre">IdleEvent</span></code> class and <code class="docutils literal notranslate"><span class="pre">FigureCanvasBase.idle_event</span></code> method
will be removed in 2.2</p>
</section>
<section id="correct-scaling-of-magnitude-spectrum">
<h2>Correct scaling of <code class="docutils literal notranslate"><span class="pre">magnitude_spectrum()</span></code><a class="headerlink" href="#correct-scaling-of-magnitude-spectrum" title="Link to this heading">#</a></h2>
<p>The functions <a class="reference internal" href="../mlab_api.html#matplotlib.mlab.magnitude_spectrum" title="matplotlib.mlab.magnitude_spectrum"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.mlab.magnitude_spectrum()</span></code></a> and <a class="reference internal" href="../_as_gen/matplotlib.pyplot.magnitude_spectrum.html#matplotlib.pyplot.magnitude_spectrum" title="matplotlib.pyplot.magnitude_spectrum"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.pyplot.magnitude_spectrum()</span></code></a> implicitly assumed the sum
of windowing function values to be one. In Matplotlib and Numpy the
standard windowing functions are scaled to have maximum value of one,
which usually results in a sum of the order of n/2 for a n-point
signal. Thus the amplitude scaling <code class="docutils literal notranslate"><span class="pre">magnitude_spectrum()</span></code> was
off by that amount when using standard windowing functions (<a class="reference external" href="https://github.com/matplotlib/matplotlib/issues/8417">Bug 8417</a> ). Now the
behavior is consistent with <a class="reference internal" href="../_as_gen/matplotlib.pyplot.psd.html#matplotlib.pyplot.psd" title="matplotlib.pyplot.psd"><code class="xref py py-func docutils literal notranslate"><span class="pre">matplotlib.pyplot.psd()</span></code></a> and
<a class="reference external" href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.welch.html#scipy.signal.welch" title="(in SciPy v1.16.1)"><code class="xref py py-func docutils literal notranslate"><span class="pre">scipy.signal.welch()</span></code></a>. The following example demonstrates the
new and old scaling:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="n">tau</span><span class="p">,</span> <span class="n">n</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span> <span class="mi">1024</span> <span class="c1"># 10 second signal with 1024 points</span>
<span class="n">T</span> <span class="o">=</span> <span class="n">tau</span><span class="o">/</span><span class="n">n</span> <span class="c1"># sampling interval</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">n</span><span class="p">)</span><span class="o">*</span><span class="n">T</span>
<span class="n">a</span> <span class="o">=</span> <span class="mi">4</span> <span class="c1"># amplitude</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">a</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="mi">40</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">t</span><span class="p">)</span> <span class="c1"># 20 Hz sine with amplitude a</span>