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<div class="section" id="module-matplotlib.scale">
<span id="matplotlib-scale"></span><h1><code class="docutils literal notranslate"><span class="pre">matplotlib.scale</span></code><a class="headerlink" href="#module-matplotlib.scale" title="Permalink to this headline">¶</a></h1>
<p>Scales define the distribution of data values on an axis, e.g. a log scaling.</p>
<p>They are attached to an <a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a> and hold a <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Transform</span></code></a>, which is
responsible for the actual data transformation.</p>
<p>See also <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">axes.Axes.set_xscale</span></code></a> and the scales examples in the documentation.</p>
<dl class="py class">
<dt id="matplotlib.scale.FuncScale">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">FuncScale</code><span class="sig-paren">(</span><em><span class="n">axis</span></em>, <em><span class="n">functions</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncScale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncScale" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.ScaleBase" title="matplotlib.scale.ScaleBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.ScaleBase</span></code></a></p>
<p>Provide an arbitrary scale with user-supplied function for the axis.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>axis</strong><span class="classifier"><a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a></span></dt><dd><p>The axis for the scale.</p>
</dd>
<dt><strong>functions</strong><span class="classifier">(callable, callable)</span></dt><dd><p>two-tuple of the forward and inverse functions for the scale.
The forward function must be monotonic.</p>
<p>Both functions must have the signature:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="n">values</span><span class="p">:</span> <span class="n">array</span><span class="o">-</span><span class="n">like</span><span class="p">)</span> <span class="o">-></span> <span class="n">array</span><span class="o">-</span><span class="n">like</span>
</pre></div>
</div>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.scale.FuncScale.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncScale.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncScale.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="#matplotlib.scale.FuncTransform" title="matplotlib.scale.FuncTransform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">FuncTransform</span></code></a> associated with this scale.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncScale.name">
<code class="descname">name</code><em class="property"> = 'function'</em><a class="headerlink" href="#matplotlib.scale.FuncScale.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.FuncScale.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncScale.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncScale.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.FuncScaleLog">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">FuncScaleLog</code><span class="sig-paren">(</span><em><span class="n">axis</span></em>, <em><span class="n">functions</span></em>, <em><span class="n">base</span><span class="o">=</span><span class="default_value">10</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncScaleLog"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncScaleLog" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.LogScale" title="matplotlib.scale.LogScale"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.LogScale</span></code></a></p>
<p>Provide an arbitrary scale with user-supplied function for the axis and
then put on a logarithmic axes.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>axis</strong><span class="classifier"><a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.axis.Axis</span></code></a></span></dt><dd><p>The axis for the scale.</p>
</dd>
<dt><strong>functions</strong><span class="classifier">(callable, callable)</span></dt><dd><p>two-tuple of the forward and inverse functions for the scale.
The forward function must be monotonic.</p>
<p>Both functions must have the signature:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="n">values</span><span class="p">:</span> <span class="n">array</span><span class="o">-</span><span class="n">like</span><span class="p">)</span> <span class="o">-></span> <span class="n">array</span><span class="o">-</span><span class="n">like</span>
</pre></div>
</div>
</dd>
<dt><strong>base</strong><span class="classifier">float, default: 10</span></dt><dd><p>Logarithmic base of the scale.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.scale.FuncScaleLog.base">
<em class="property">property </em><code class="descname">base</code><a class="headerlink" href="#matplotlib.scale.FuncScaleLog.base" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.FuncScaleLog.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncScaleLog.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncScaleLog.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Transform</span></code></a> associated with this scale.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncScaleLog.name">
<code class="descname">name</code><em class="property"> = 'functionlog'</em><a class="headerlink" href="#matplotlib.scale.FuncScaleLog.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.FuncTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">FuncTransform</code><span class="sig-paren">(</span><em><span class="n">forward</span></em>, <em><span class="n">inverse</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<p>A simple transform that takes and arbitrary function for the
forward and inverse transform.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>forward</strong><span class="classifier">callable</span></dt><dd><p>The forward function for the transform. This function must have
an inverse and, for best behavior, be monotonic.
It must have the signature:</p>
<div class="highlight-default notranslate"><div class="highlight"><pre><span></span><span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="n">values</span><span class="p">:</span> <span class="n">array</span><span class="o">-</span><span class="n">like</span><span class="p">)</span> <span class="o">-></span> <span class="n">array</span><span class="o">-</span><span class="n">like</span>
</pre></div>
</div>
</dd>
<dt><strong>inverse</strong><span class="classifier">callable</span></dt><dd><p>The inverse of the forward function. Signature as <code class="docutils literal notranslate"><span class="pre">forward</span></code>.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.FuncTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.FuncTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.FuncTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.FuncTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.FuncTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.FuncTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.FuncTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">values</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#FuncTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.FuncTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.FuncTransform.input_dims" title="matplotlib.scale.FuncTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.FuncTransform.input_dims" title="matplotlib.scale.FuncTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.FuncTransform.input_dims" title="matplotlib.scale.FuncTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.FuncTransform.output_dims" title="matplotlib.scale.FuncTransform.output_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code></a>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.InvertedLogTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">InvertedLogTransform</code><span class="sig-paren">(</span><em><span class="n">base</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedLogTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedLogTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedLogTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.InvertedLogTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedLogTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedLogTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedLogTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.InvertedLogTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedLogTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedLogTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.InvertedLogTransform.input_dims" title="matplotlib.scale.InvertedLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.InvertedLogTransform.input_dims" title="matplotlib.scale.InvertedLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.InvertedLogTransform.input_dims" title="matplotlib.scale.InvertedLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.InvertedLogTransform.output_dims" title="matplotlib.scale.InvertedLogTransform.output_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code></a>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">InvertedSymmetricalLogTransform</code><span class="sig-paren">(</span><em><span class="n">base</span></em>, <em><span class="n">linthresh</span></em>, <em><span class="n">linscale</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedSymmetricalLogTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedSymmetricalLogTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.InvertedSymmetricalLogTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#InvertedSymmetricalLogTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.InvertedSymmetricalLogTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.InvertedSymmetricalLogTransform.input_dims" title="matplotlib.scale.InvertedSymmetricalLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.InvertedSymmetricalLogTransform.input_dims" title="matplotlib.scale.InvertedSymmetricalLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.InvertedSymmetricalLogTransform.input_dims" title="matplotlib.scale.InvertedSymmetricalLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.InvertedSymmetricalLogTransform.output_dims" title="matplotlib.scale.InvertedSymmetricalLogTransform.output_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code></a>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LinearScale">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LinearScale</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LinearScale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LinearScale" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.ScaleBase" title="matplotlib.scale.ScaleBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.ScaleBase</span></code></a></p>
<p>The default linear scale.</p>
<dl class="py method">
<dt id="matplotlib.scale.LinearScale.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LinearScale.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LinearScale.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the transform for linear scaling, which is just the
<a class="reference internal" href="transformations.html#matplotlib.transforms.IdentityTransform" title="matplotlib.transforms.IdentityTransform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">IdentityTransform</span></code></a>.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LinearScale.name">
<code class="descname">name</code><em class="property"> = 'linear'</em><a class="headerlink" href="#matplotlib.scale.LinearScale.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LinearScale.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LinearScale.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LinearScale.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LogScale">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LogScale</code><span class="sig-paren">(</span><em><span class="n">axis</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogScale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogScale" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.ScaleBase" title="matplotlib.scale.ScaleBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.ScaleBase</span></code></a></p>
<p>A standard logarithmic scale. Care is taken to only plot positive values.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>axis</strong><span class="classifier"><a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a></span></dt><dd><p>The axis for the scale.</p>
</dd>
<dt><strong>base</strong><span class="classifier">float, default: 10</span></dt><dd><p>The base of the logarithm.</p>
</dd>
<dt><strong>nonpositive</strong><span class="classifier">{'clip', 'mask'}, default: 'clip'</span></dt><dd><p>Determines the behavior for non-positive values. They can either
be masked as invalid, or clipped to a very small positive number.</p>
</dd>
<dt><strong>subs</strong><span class="classifier">sequence of int, default: None</span></dt><dd><p>Where to place the subticks between each major tick. For example,
in a log10 scale, <code class="docutils literal notranslate"><span class="pre">[2,</span> <span class="pre">3,</span> <span class="pre">4,</span> <span class="pre">5,</span> <span class="pre">6,</span> <span class="pre">7,</span> <span class="pre">8,</span> <span class="pre">9]</span></code> will place 8
logarithmically spaced minor ticks between each major tick.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.InvertedLogTransform">
<em class="property">property </em><code class="descname">InvertedLogTransform</code><a class="headerlink" href="#matplotlib.scale.LogScale.InvertedLogTransform" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.LogTransform">
<em class="property">property </em><code class="descname">LogTransform</code><a class="headerlink" href="#matplotlib.scale.LogScale.LogTransform" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.base">
<em class="property">property </em><code class="descname">base</code><a class="headerlink" href="#matplotlib.scale.LogScale.base" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogScale.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogScale.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="#matplotlib.scale.LogScale.LogTransform" title="matplotlib.scale.LogScale.LogTransform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LogTransform</span></code></a> associated with this scale.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.limit_range_for_scale">
<code class="descname">limit_range_for_scale</code><span class="sig-paren">(</span><em><span class="n">vmin</span></em>, <em><span class="n">vmax</span></em>, <em><span class="n">minpos</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogScale.limit_range_for_scale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogScale.limit_range_for_scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Limit the domain to positive values.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogScale.name">
<code class="descname">name</code><em class="property"> = 'log'</em><a class="headerlink" href="#matplotlib.scale.LogScale.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogScale.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogScale.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogScale.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LogTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LogTransform</code><span class="sig-paren">(</span><em><span class="n">base</span></em>, <em><span class="n">nonpositive</span><span class="o">=</span><span class="default_value">'clip'</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.LogTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.LogTransform.input_dims" title="matplotlib.scale.LogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.LogTransform.input_dims" title="matplotlib.scale.LogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a>).</p>
</dd>
</dl>
</td>
</tr>
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><dl class="first last docutils">
<dt>array</dt><dd><p>The output values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.LogTransform.input_dims" title="matplotlib.scale.LogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or
shape (N x <a class="reference internal" href="#matplotlib.scale.LogTransform.output_dims" title="matplotlib.scale.LogTransform.output_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">output_dims</span></code></a>), depending on the input.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LogisticTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LogisticTransform</code><span class="sig-paren">(</span><em><span class="n">nonpositive</span><span class="o">=</span><span class="default_value">'mask'</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogisticTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogisticTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.LogisticTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogisticTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogisticTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogisticTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogisticTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogisticTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogisticTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogisticTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogisticTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogisticTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogisticTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogisticTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogisticTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogisticTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>logistic transform (base 10)</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LogitScale">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LogitScale</code><span class="sig-paren">(</span><em><span class="n">axis</span></em>, <em><span class="n">nonpositive</span><span class="o">=</span><span class="default_value">'mask'</span></em>, <em><span class="o">*</span></em>, <em><span class="n">one_half</span><span class="o">=</span><span class="default_value">'\x0crac{1}{2}'</span></em>, <em><span class="n">use_overline</span><span class="o">=</span><span class="default_value">False</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitScale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitScale" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.ScaleBase" title="matplotlib.scale.ScaleBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.ScaleBase</span></code></a></p>
<p>Logit scale for data between zero and one, both excluded.</p>
<p>This scale is similar to a log scale close to zero and to one, and almost
linear around 0.5. It maps the interval ]0, 1[ onto ]-infty, +infty[.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>axis</strong><span class="classifier"><a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">matplotlib.axis.Axis</span></code></a></span></dt><dd><p>Currently unused.</p>
</dd>
<dt><strong>nonpositive</strong><span class="classifier">{'mask', 'clip'}</span></dt><dd><p>Determines the behavior for values beyond the open interval ]0, 1[.
They can either be masked as invalid, or clipped to a number very
close to 0 or 1.</p>
</dd>
<dt><strong>use_overline</strong><span class="classifier">bool, default: False</span></dt><dd><p>Indicate the usage of survival notation (overline{x}) in place of
standard notation (1-x) for probability close to one.</p>
</dd>
<dt><strong>one_half</strong><span class="classifier">str, default: r"frac{1}{2}"</span></dt><dd><p>The string used for ticks formatter to represent 1/2.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py method">
<dt id="matplotlib.scale.LogitScale.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitScale.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitScale.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="#matplotlib.scale.LogitTransform" title="matplotlib.scale.LogitTransform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">LogitTransform</span></code></a> associated with this scale.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogitScale.limit_range_for_scale">
<code class="descname">limit_range_for_scale</code><span class="sig-paren">(</span><em><span class="n">vmin</span></em>, <em><span class="n">vmax</span></em>, <em><span class="n">minpos</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitScale.limit_range_for_scale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitScale.limit_range_for_scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Limit the domain to values between 0 and 1 (excluded).</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogitScale.name">
<code class="descname">name</code><em class="property"> = 'logit'</em><a class="headerlink" href="#matplotlib.scale.LogitScale.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogitScale.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitScale.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitScale.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.LogitTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">LogitTransform</code><span class="sig-paren">(</span><em><span class="n">nonpositive</span><span class="o">=</span><span class="default_value">'mask'</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.LogitTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogitTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogitTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogitTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogitTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogitTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.LogitTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.LogitTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.LogitTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.LogitTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#LogitTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.LogitTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>logit transform (base 10), masked or clipped</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.ScaleBase">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">ScaleBase</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#ScaleBase"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.ScaleBase" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>The base class for all scales.</p>
<p>Scales are separable transformations, working on a single dimension.</p>
<p>Any subclasses will want to override:</p>
<ul class="simple">
<li><code class="xref py py-attr docutils literal notranslate"><span class="pre">name</span></code></li>
<li><a class="reference internal" href="#matplotlib.scale.ScaleBase.get_transform" title="matplotlib.scale.ScaleBase.get_transform"><code class="xref py py-meth docutils literal notranslate"><span class="pre">get_transform()</span></code></a></li>
<li><a class="reference internal" href="#matplotlib.scale.ScaleBase.set_default_locators_and_formatters" title="matplotlib.scale.ScaleBase.set_default_locators_and_formatters"><code class="xref py py-meth docutils literal notranslate"><span class="pre">set_default_locators_and_formatters()</span></code></a></li>
</ul>
<p>And optionally:</p>
<ul class="simple">
<li><a class="reference internal" href="#matplotlib.scale.ScaleBase.limit_range_for_scale" title="matplotlib.scale.ScaleBase.limit_range_for_scale"><code class="xref py py-meth docutils literal notranslate"><span class="pre">limit_range_for_scale()</span></code></a></li>
</ul>
<p>Construct a new scale.</p>
<p class="rubric">Notes</p>
<p>The following note is for scale implementors.</p>
<p>For back-compatibility reasons, scales take an <a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a>
object as first argument. However, this argument should not
be used: a single scale object should be usable by multiple
<a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a>es at the same time.</p>
<dl class="py method">
<dt id="matplotlib.scale.ScaleBase.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#ScaleBase.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.ScaleBase.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">Transform</span></code></a> object
associated with this scale.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.ScaleBase.limit_range_for_scale">
<code class="descname">limit_range_for_scale</code><span class="sig-paren">(</span><em><span class="n">vmin</span></em>, <em><span class="n">vmax</span></em>, <em><span class="n">minpos</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#ScaleBase.limit_range_for_scale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.ScaleBase.limit_range_for_scale" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the range <em>vmin</em>, <em>vmax</em>, restricted to the
domain supported by this scale (if any).</p>
<p><em>minpos</em> should be the minimum positive value in the data.
This is used by log scales to determine a minimum value.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.ScaleBase.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#ScaleBase.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.ScaleBase.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.SymmetricalLogScale">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">SymmetricalLogScale</code><span class="sig-paren">(</span><em><span class="n">axis</span></em>, <em><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogScale"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="#matplotlib.scale.ScaleBase" title="matplotlib.scale.ScaleBase"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.scale.ScaleBase</span></code></a></p>
<p>The symmetrical logarithmic scale is logarithmic in both the
positive and negative directions from the origin.</p>
<p>Since the values close to zero tend toward infinity, there is a
need to have a range around zero that is linear. The parameter
<em>linthresh</em> allows the user to specify the size of this range
(-<em>linthresh</em>, <em>linthresh</em>).</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>base</strong><span class="classifier">float, default: 10</span></dt><dd><p>The base of the logarithm.</p>
</dd>
<dt><strong>linthresh</strong><span class="classifier">float, default: 2</span></dt><dd><p>Defines the range <code class="docutils literal notranslate"><span class="pre">(-x,</span> <span class="pre">x)</span></code>, within which the plot is linear.
This avoids having the plot go to infinity around zero.</p>
</dd>
<dt><strong>subs</strong><span class="classifier">sequence of int</span></dt><dd><p>Where to place the subticks between each major tick.
For example, in a log10 scale: <code class="docutils literal notranslate"><span class="pre">[2,</span> <span class="pre">3,</span> <span class="pre">4,</span> <span class="pre">5,</span> <span class="pre">6,</span> <span class="pre">7,</span> <span class="pre">8,</span> <span class="pre">9]</span></code> will place
8 logarithmically spaced minor ticks between each major tick.</p>
</dd>
<dt><strong>linscale</strong><span class="classifier">float, optional</span></dt><dd><p>This allows the linear range <code class="docutils literal notranslate"><span class="pre">(-linthresh,</span> <span class="pre">linthresh)</span></code> to be
stretched relative to the logarithmic range. Its value is the number of
decades to use for each half of the linear range. For example, when
<em>linscale</em> == 1.0 (the default), the space used for the positive and
negative halves of the linear range will be equal to one decade in
the logarithmic range.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<p>Construct a new scale.</p>
<p class="rubric">Notes</p>
<p>The following note is for scale implementors.</p>
<p>For back-compatibility reasons, scales take an <a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a>
object as first argument. However, this argument should not
be used: a single scale object should be usable by multiple
<a class="reference internal" href="axis_api.html#matplotlib.axis.Axis" title="matplotlib.axis.Axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Axis</span></code></a>es at the same time.</p>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.InvertedSymmetricalLogTransform">
<em class="property">property </em><code class="descname">InvertedSymmetricalLogTransform</code><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.InvertedSymmetricalLogTransform" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.SymmetricalLogTransform">
<em class="property">property </em><code class="descname">SymmetricalLogTransform</code><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.SymmetricalLogTransform" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.base">
<em class="property">property </em><code class="descname">base</code><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.base" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.get_transform">
<code class="descname">get_transform</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogScale.get_transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.get_transform" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the <a class="reference internal" href="#matplotlib.scale.SymmetricalLogScale.SymmetricalLogTransform" title="matplotlib.scale.SymmetricalLogScale.SymmetricalLogTransform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">SymmetricalLogTransform</span></code></a> associated with this scale.</p>
</dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.linscale">
<em class="property">property </em><code class="descname">linscale</code><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.linscale" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.linthresh">
<em class="property">property </em><code class="descname">linthresh</code><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.linthresh" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.SymmetricalLogScale.name">
<code class="descname">name</code><em class="property"> = 'symlog'</em><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.name" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogScale.set_default_locators_and_formatters">
<code class="descname">set_default_locators_and_formatters</code><span class="sig-paren">(</span><em><span class="n">axis</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogScale.set_default_locators_and_formatters"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogScale.set_default_locators_and_formatters" title="Permalink to this definition">¶</a></dt>
<dd><p>Set the locators and formatters of <em>axis</em> to instances suitable for
this scale.</p>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt id="matplotlib.scale.SymmetricalLogTransform">
<em class="property">class </em><code class="descclassname">matplotlib.scale.</code><code class="descname">SymmetricalLogTransform</code><span class="sig-paren">(</span><em><span class="n">base</span></em>, <em><span class="n">linthresh</span></em>, <em><span class="n">linscale</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogTransform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform" title="Permalink to this definition">¶</a></dt>
<dd><p>Bases: <a class="reference internal" href="transformations.html#matplotlib.transforms.Transform" title="matplotlib.transforms.Transform"><code class="xref py py-class docutils literal notranslate"><span class="pre">matplotlib.transforms.Transform</span></code></a></p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first last docutils">
<dt><strong>shorthand_name</strong><span class="classifier">str</span></dt><dd><p>A string representing the "name" of the transform. The name carries
no significance other than to improve the readability of
<code class="docutils literal notranslate"><span class="pre">str(transform)</span></code> when DEBUG=True.</p>
</dd>
</dl>
</td>
</tr>
</tbody>
</table>
<dl class="py attribute">
<dt id="matplotlib.scale.SymmetricalLogTransform.has_inverse">
<code class="descname">has_inverse</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.has_inverse" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.SymmetricalLogTransform.input_dims">
<code class="descname">input_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.input_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogTransform.inverted">
<code class="descname">inverted</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogTransform.inverted"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.inverted" title="Permalink to this definition">¶</a></dt>
<dd><p>Return the corresponding inverse transformation.</p>
<p>It holds <code class="docutils literal notranslate"><span class="pre">x</span> <span class="pre">==</span> <span class="pre">self.inverted().transform(self.transform(x))</span></code>.</p>
<p>The return value of this method should be treated as
temporary. An update to <em>self</em> does not cause a corresponding
update to its inverted copy.</p>
</dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.SymmetricalLogTransform.is_separable">
<code class="descname">is_separable</code><em class="property"> = True</em><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.is_separable" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt id="matplotlib.scale.SymmetricalLogTransform.output_dims">
<code class="descname">output_dims</code><em class="property"> = 1</em><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.output_dims" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>
<dl class="py method">
<dt id="matplotlib.scale.SymmetricalLogTransform.transform_non_affine">
<code class="descname">transform_non_affine</code><span class="sig-paren">(</span><em><span class="n">a</span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/matplotlib/scale.html#SymmetricalLogTransform.transform_non_affine"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#matplotlib.scale.SymmetricalLogTransform.transform_non_affine" title="Permalink to this definition">¶</a></dt>
<dd><p>Apply only the non-affine part of this transformation.</p>
<p><code class="docutils literal notranslate"><span class="pre">transform(values)</span></code> is always equivalent to
<code class="docutils literal notranslate"><span class="pre">transform_affine(transform_non_affine(values))</span></code>.</p>
<p>In non-affine transformations, this is generally equivalent to
<code class="docutils literal notranslate"><span class="pre">transform(values)</span></code>. In affine transformations, this is
always a no-op.</p>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><dl class="first docutils">
<dt><strong>values</strong><span class="classifier">array</span></dt><dd><p>The input values as NumPy array of length <a class="reference internal" href="#matplotlib.scale.SymmetricalLogTransform.input_dims" title="matplotlib.scale.SymmetricalLogTransform.input_dims"><code class="xref py py-attr docutils literal notranslate"><span class="pre">input_dims</span></code></a> or