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<h1>Plotting commands summary<aclass="headerlink" href="#plotting-commands-summary" title="Permalink to this headline">¶</a></h1>
<dlclass="function">
<dtid="matplotlib.pyplot.plotting">
<codeclass="descclassname">matplotlib.pyplot.</code><codeclass="descname">plotting</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.pyplot.plotting" title="Permalink to this definition">¶</a></dt>
<td>Annotate the point <codeclass="docutils literal"><spanclass="pre">xy</span></code> with text <codeclass="docutils literal"><spanclass="pre">s</span></code>.</td>
<td>Get the current <aclass="reference internal" href="axes_api.html#matplotlib.axes.Axes" title="matplotlib.axes.Axes"><codeclass="xref py py-class docutils literal"><spanclass="pre">Axes</span></code></a> instance on the current figure matching the given keyword args, or create one.</td>
<td>Make a scatter plot of <codeclass="xref py py-obj docutils literal"><spanclass="pre">x</span></code> vs <codeclass="xref py py-obj docutils literal"><spanclass="pre">y</span></code> Marker size is scaled by <codeclass="xref py py-obj docutils literal"><spanclass="pre">s</span></code> and marker color is mapped to <codeclass="xref py py-obj docutils literal"><spanclass="pre">c</span></code> Parameters ———- x, y : array_like, shape (n, ) Input data s : scalar or array_like, shape (n, ), optional size in points^2.</td>
<td>Create a figure and a set of subplots This utility wrapper makes it convenient to create common layouts of subplots, including the enclosing figure object, in a single call.</td>
<td>Change the <aclass="reference internal" href="ticker_api.html#matplotlib.ticker.ScalarFormatter" title="matplotlib.ticker.ScalarFormatter"><codeclass="xref py py-obj docutils literal"><spanclass="pre">ScalarFormatter</span></code></a> used by default for linear axes.</td>
<td>Get or set the <em>y</em>-limits of the current tick locations and labels.</td>
</tr>
</tbody>
</table>
</dd></dl>
<dlclass="function">
<dtid="matplotlib.pyplot.colormaps">
<codeclass="descclassname">matplotlib.pyplot.</code><codeclass="descname">colormaps</code><spanclass="sig-paren">(</span><spanclass="sig-paren">)</span><aclass="headerlink" href="#matplotlib.pyplot.colormaps" title="Permalink to this definition">¶</a></dt>
<dd><p>Matplotlib provides a number of colormaps, and others can be added using
<aclass="reference internal" href="cm_api.html#matplotlib.cm.register_cmap" title="matplotlib.cm.register_cmap"><codeclass="xref py py-func docutils literal"><spanclass="pre">register_cmap()</span></code></a>. This function documents the built-in
colormaps, and will also return a list of all registered colormaps if called.</p>
<p>You can set the colormap for an image, pcolor, scatter, etc,
<p>In interactive mode, <aclass="reference internal" href="pyplot_api.html#matplotlib.pyplot.set_cmap" title="matplotlib.pyplot.set_cmap"><codeclass="xref py py-func docutils literal"><spanclass="pre">set_cmap()</span></code></a> will update the colormap post-hoc,
allowing you to see which one works best for your data.</p>
<p>All built-in colormaps can be reversed by appending <codeclass="docutils literal"><spanclass="pre">_r</span></code>: For instance,
<codeclass="docutils literal"><spanclass="pre">gray_r</span></code> is the reverse of <codeclass="docutils literal"><spanclass="pre">gray</span></code>.</p>
<p>There are several common color schemes used in visualization:</p>
<dlclass="docutils">
<dt>Sequential schemes</dt>
<dd>for unipolar data that progresses from low to high</dd>
<dt>Diverging schemes</dt>
<dd>for bipolar data that emphasizes positive or negative deviations from a
central value</dd>
<dt>Cyclic schemes</dt>
<dd>meant for plotting values that wrap around at the
endpoints, such as phase angle, wind direction, or time of day</dd>
<dt>Qualitative schemes</dt>
<dd>for nominal data that has no inherent ordering, where color is used
only to distinguish categories</dd>
</dl>
<p>The base colormaps are derived from those of the same name provided
with Matlab:</p>
<blockquote>
<div><tableborder="1" class="docutils">
<colgroup>
<colwidth="13%" />
<colwidth="87%" />
</colgroup>
<theadvalign="bottom">
<trclass="row-odd"><thclass="head">Colormap</th>
<thclass="head">Description</th>
</tr>
</thead>
<tbodyvalign="top">
<trclass="row-even"><td>autumn</td>
<td>sequential linearly-increasing shades of red-orange-yellow</td>
</tr>
<trclass="row-odd"><td>bone</td>
<td>sequential increasing black-white color map with
a tinge of blue, to emulate X-ray film</td>
</tr>
<trclass="row-even"><td>cool</td>
<td>linearly-decreasing shades of cyan-magenta</td>
</tr>
<trclass="row-odd"><td>copper</td>
<td>sequential increasing shades of black-copper</td>
</tr>
<trclass="row-even"><td>flag</td>
<td>repetitive red-white-blue-black pattern (not cyclic at
endpoints)</td>
</tr>
<trclass="row-odd"><td>gray</td>
<td>sequential linearly-increasing black-to-white
grayscale</td>
</tr>
<trclass="row-even"><td>hot</td>
<td>sequential black-red-yellow-white, to emulate blackbody
radiation from an object at increasing temperatures</td>
</tr>
<trclass="row-odd"><td>hsv</td>
<td>cyclic red-yellow-green-cyan-blue-magenta-red, formed
by changing the hue component in the HSV color space</td>
</tr>
<trclass="row-even"><td>inferno</td>
<td>perceptually uniform shades of black-red-yellow</td>
</tr>
<trclass="row-odd"><td>jet</td>
<td>a spectral map with dark endpoints, blue-cyan-yellow-red;
based on a fluid-jet simulation by NCSA <aclass="footnote-reference" href="#id6" id="id1">[1]</a></td>
</tr>
<trclass="row-even"><td>magma</td>
<td>perceptually uniform shades of black-red-white</td>
Research <aclass="footnote-reference" href="#id7" id="id2">[2]</a></td>
</tr>
<trclass="row-odd"><td>gist_rainbow</td>
<td>runs through the colors in spectral order from red to
violet at full saturation (like <em>hsv</em> but not cyclic)</td>
</tr>
<trclass="row-even"><td>gist_stern</td>
<td>“Stern special” color table from Interactive Data
Language software</td>
</tr>
</tbody>
</table>
</div></blockquote>
<p>The following colormaps are based on the <aclass="reference external" href="http://colorbrewer2.org">ColorBrewer</a> color specifications and designs developed by
Cynthia Brewer:</p>
<p>ColorBrewer Diverging (luminance is highest at the midpoint, and
decreases towards differently-colored endpoints):</p>
<tr><tdclass="label"><aclass="fn-backref" href="#id1">[1]</a></td><td>Rainbow colormaps, <codeclass="docutils literal"><spanclass="pre">jet</span></code> in particular, are considered a poor
choice for scientific visualization by many researchers: <aclass="reference external" href="http://ieeexplore.ieee.org/document/4118486/?arnumber=4118486">Rainbow Color
<tr><tdclass="label"><aclass="fn-backref" href="#id3">[3]</a></td><td>See <aclass="reference external" href="http://www.kennethmoreland.com/color-maps/">Diverging Color Maps for Scientific Visualization</a> by Kenneth Moreland.</td></tr>
<tr><tdclass="label"><aclass="fn-backref" href="#id4">[4]</a></td><td>See <aclass="reference external" href="http://www.mathworks.com/matlabcentral/fileexchange/2662-cmrmap-m">A Color Map for Effective Black-and-White Rendering of