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<title>Content with notebooks — job-dispatcher docs</title>
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<section class="tex2jax_ignore mathjax_ignore" id="content-with-notebooks">
<h1>Content with notebooks<a class="headerlink" href="#content-with-notebooks" title="Permalink to this heading">#</a></h1>
<p>You can also create content with Jupyter Notebooks. This means that you can include
code blocks and their outputs in your book.</p>
<section id="markdown-notebooks">
<h2>Markdown + notebooks<a class="headerlink" href="#markdown-notebooks" title="Permalink to this heading">#</a></h2>
<p>As it is markdown, you can embed images, HTML, etc into your posts!</p>
<p><img alt="" src="https://myst-parser.readthedocs.io/en/latest/_static/logo-wide.svg" /></p>
<p>You can also <span class="math notranslate nohighlight">\(add_{math}\)</span> and</p>
<div class="math notranslate nohighlight">
\[
math^{blocks}
\]</div>
<p>or</p>
<div class="math notranslate nohighlight">
\[\begin{split}
\begin{aligned}
\mbox{mean} la_{tex} \\ \\
math blocks
\end{aligned}
\end{split}\]</div>
<p>But make sure you $Escape $your $dollar signs $you want to keep!</p>
</section>
<section id="myst-markdown">
<h2>MyST markdown<a class="headerlink" href="#myst-markdown" title="Permalink to this heading">#</a></h2>
<p>MyST markdown works in Jupyter Notebooks as well. For more information about MyST markdown, check
out <a class="reference external" href="https://jupyterbook.org/content/myst.html">the MyST guide in Jupyter Book</a>,
or see <a class="reference external" href="https://myst-parser.readthedocs.io/en/latest/">the MyST markdown documentation</a>.</p>
</section>
<section id="code-blocks-and-outputs">
<h2>Code blocks and outputs<a class="headerlink" href="#code-blocks-and-outputs" title="Permalink to this heading">#</a></h2>
<p>Jupyter Book will also embed your code blocks and output in your book.
For example, here’s some sample Matplotlib code:</p>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">matplotlib</span> <span class="kn">import</span> <span class="n">rcParams</span><span class="p">,</span> <span class="n">cycler</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ion</span><span class="p">()</span>
</pre></div>
</div>
</div>
<div class="cell_output docutils container">
<div class="output traceback highlight-ipythontb notranslate"><div class="highlight"><pre><span></span><span class="gt">---------------------------------------------------------------------------</span>
<span class="ne">ModuleNotFoundError</span><span class="g g-Whitespace"> </span>Traceback (most recent call last)
<span class="nn">/tmp/ipykernel_39618/2191868119.py</span> in <span class="ni"><cell line: 1></span><span class="nt">()</span>
<span class="ne">----> </span><span class="mi">1</span> <span class="kn">from</span> <span class="nn">matplotlib</span> <span class="kn">import</span> <span class="n">rcParams</span><span class="p">,</span> <span class="n">cycler</span>
<span class="g g-Whitespace"> </span><span class="mi">2</span> <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="g g-Whitespace"> </span><span class="mi">3</span> <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="g g-Whitespace"> </span><span class="mi">4</span> <span class="n">plt</span><span class="o">.</span><span class="n">ion</span><span class="p">()</span>
<span class="ne">ModuleNotFoundError</span>: No module named 'matplotlib'
</pre></div>
</div>
</div>
</div>
<div class="cell docutils container">
<div class="cell_input docutils container">
<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Fixing random state for reproducibility</span>
<span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">seed</span><span class="p">(</span><span class="mi">19680801</span><span class="p">)</span>
<span class="n">N</span> <span class="o">=</span> <span class="mi">10</span>
<span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">logspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">100</span><span class="p">)</span> <span class="o">+</span> <span class="n">ii</span> <span class="k">for</span> <span class="n">ii</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">N</span><span class="p">)]</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">)</span><span class="o">.</span><span class="n">T</span>
<span class="n">cmap</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">cm</span><span class="o">.</span><span class="n">coolwarm</span>
<span class="n">rcParams</span><span class="p">[</span><span class="s1">'axes.prop_cycle'</span><span class="p">]</span> <span class="o">=</span> <span class="n">cycler</span><span class="p">(</span><span class="n">color</span><span class="o">=</span><span class="n">cmap</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">N</span><span class="p">)))</span>
<span class="kn">from</span> <span class="nn">matplotlib.lines</span> <span class="kn">import</span> <span class="n">Line2D</span>
<span class="n">custom_lines</span> <span class="o">=</span> <span class="p">[</span><span class="n">Line2D</span><span class="p">([</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="n">cmap</span><span class="p">(</span><span class="mf">0.</span><span class="p">),</span> <span class="n">lw</span><span class="o">=</span><span class="mi">4</span><span class="p">),</span>
<span class="n">Line2D</span><span class="p">([</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="n">cmap</span><span class="p">(</span><span class="mf">.5</span><span class="p">),</span> <span class="n">lw</span><span class="o">=</span><span class="mi">4</span><span class="p">),</span>
<span class="n">Line2D</span><span class="p">([</span><span class="mi">0</span><span class="p">],</span> <span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">color</span><span class="o">=</span><span class="n">cmap</span><span class="p">(</span><span class="mf">1.</span><span class="p">),</span> <span class="n">lw</span><span class="o">=</span><span class="mi">4</span><span class="p">)]</span>
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">5</span><span class="p">))</span>
<span class="n">lines</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">custom_lines</span><span class="p">,</span> <span class="p">[</span><span class="s1">'Cold'</span><span class="p">,</span> <span class="s1">'Medium'</span><span class="p">,</span> <span class="s1">'Hot'</span><span class="p">]);</span>
</pre></div>
</div>
</div>
</div>
<p>There is a lot more that you can do with outputs (such as including interactive outputs)
with your book. For more information about this, see <a class="reference external" href="https://jupyterbook.org">the Jupyter Book documentation</a></p>
</section>
</section>
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