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<title>Codebraid with Jupyter kernels</title>
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<header id="title-block-header">
<h1 class="title">Codebraid with Jupyter kernels</h1>
</header>
<p>Using Codebraid with Jupyter kernels rather than the built-in code
execution system is as simple as adding a Codebraid setting to the
document YAML metadata. For example, this document begins with the
following metadata:</p>
<pre><code>---
title: "Codebraid with Jupyter kernels"
codebraid:
jupyter: true
---</code></pre>
<p>In this case, Codebraid automatically selects a kernel based on code
language. It is also possible to select a specific kernel. For
example,</p>
<pre><code>---
codebraid:
jupyter:
kernel: python3
---</code></pre>
<p>This would set a default kernel for the entire document. The kernel
can be overridden for an individual session by setting
<code>jupyter_kernel=<kernel></code> on the first code chunk of a
session.</p>
<h2 id="matplotlib"><a href="https://matplotlib.org/">Matplotlib</a></h2>
<p>Plots are included automatically.</p>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.python .cb-nb}
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(0, 2*np.pi, 1001)
x_tick_values = np.linspace(0, 2*np.pi, 5)
x_tick_labels = ['0', r'$\pi/2$', r'$\pi$', r'$3\pi/2$', r'$2\pi$']
plt.plot(x, np.cos(x), label=r'$\cos(x)$')
plt.plot(x, np.sin(x), label=r'$\sin(x)$')
plt.xticks(x_tick_values, x_tick_labels)
plt.legend(prop={'size': 12})
plt.grid()
```</code></pre>
</div>
<div class="exampleOutput">
<div class="sourceCode" id="cb4" data-startFrom="1"><pre class="sourceCode numberSource python numberLines"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1"></a><span class="op">%</span>matplotlib inline</span>
<span id="cb4-2"><a href="#cb4-2"></a><span class="im">import</span> matplotlib.pyplot <span class="im">as</span> plt</span>
<span id="cb4-3"><a href="#cb4-3"></a><span class="im">import</span> numpy <span class="im">as</span> np</span>
<span id="cb4-4"><a href="#cb4-4"></a>x <span class="op">=</span> np.linspace(<span class="dv">0</span>, <span class="dv">2</span><span class="op">*</span>np.pi, <span class="dv">1001</span>)</span>
<span id="cb4-5"><a href="#cb4-5"></a>x_tick_values <span class="op">=</span> np.linspace(<span class="dv">0</span>, <span class="dv">2</span><span class="op">*</span>np.pi, <span class="dv">5</span>)</span>
<span id="cb4-6"><a href="#cb4-6"></a>x_tick_labels <span class="op">=</span> [<span class="st">'0'</span>, <span class="vs">r'$\pi/2$'</span>, <span class="vs">r'$\pi$'</span>, <span class="vs">r'$3\pi/2$'</span>, <span class="vs">r'$2\pi$'</span>]</span>
<span id="cb4-7"><a href="#cb4-7"></a>plt.plot(x, np.cos(x), label<span class="op">=</span><span class="vs">r'$\cos(x)$'</span>)</span>
<span id="cb4-8"><a href="#cb4-8"></a>plt.plot(x, np.sin(x), label<span class="op">=</span><span class="vs">r'$\sin(x)$'</span>)</span>
<span id="cb4-9"><a href="#cb4-9"></a>plt.xticks(x_tick_values, x_tick_labels)</span>
<span id="cb4-10"><a href="#cb4-10"></a>plt.legend(prop<span class="op">=</span>{<span class="st">'size'</span>: <span class="dv">12</span>})</span>
<span id="cb4-11"><a href="#cb4-11"></a>plt.grid()</span></code></pre></div>
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" class="richOutput" /></p>
</div>
</div>
<p>If there are errors or warnings, they are shown as well. Copying this
code into a Jupyter notebook yields the same output.</p>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.python .cb-nb}
plt.plot(x, np.sin(x)/x, label=r'$\sin(x)/x$')
plt.plot(x, np.cos(np.sin(x)), label=r'$\cos(\sin(x))$')
plt.xticks(x_tick_values, x_tick_labels)
plt.legend(prop={'size': 12})
plt.grid()
```</code></pre>
</div>
<div class="exampleOutput">
<div class="sourceCode" id="cb6" data-startFrom="12"><pre class="sourceCode numberSource python numberLines"><code class="sourceCode python" style="counter-reset: source-line 11;"><span id="cb6-12"><a href="#cb6-12"></a>plt.plot(x, np.sin(x)<span class="op">/</span>x, label<span class="op">=</span><span class="vs">r'$\sin(x)/x$'</span>)</span>
<span id="cb6-13"><a href="#cb6-13"></a>plt.plot(x, np.cos(np.sin(x)), label<span class="op">=</span><span class="vs">r'$\cos(\sin(x))$'</span>)</span>
<span id="cb6-14"><a href="#cb6-14"></a>plt.xticks(x_tick_values, x_tick_labels)</span>
<span id="cb6-15"><a href="#cb6-15"></a>plt.legend(prop<span class="op">=</span>{<span class="st">'size'</span>: <span class="dv">12</span>})</span>
<span id="cb6-16"><a href="#cb6-16"></a>plt.grid()</span></code></pre></div>
<pre class="stderr"><code>~\AppData\Local\Temp\ipykernel_15472\293500280.py:1: RuntimeWarning: invalid value encountered in divide
plt.plot(x, np.sin(x)/x, label=r'$\sin(x)/x$')</code></pre>
<p><img src="data:image/png;base64,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" class="richOutput" /></p>
</div>
</div>
<h2 id="sympy"><a href="https://www.sympy.org/">SymPy</a></h2>
<p>SymPy equations are displayed as well. This example runs in a
separate session from the plots above. Multiple Jupyter kernels can be
used within a single document, and multiple independent sessions are
possible per kernel.</p>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.python .cb-nb session=sympy name=sympy1}
from sympy import *
init_printing(use_latex='mathjax')
x = Symbol('x')
eqn = E**(-x**2)
int_eqn = Integral(eqn, (x, -oo, oo))
int_eqn
```</code></pre>
</div>
<div class="exampleOutput">
<div class="sourceCode" id="cb9" data-startFrom="1"><pre class="sourceCode numberSource python numberLines"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1"></a><span class="im">from</span> sympy <span class="im">import</span> <span class="op">*</span></span>
<span id="cb9-2"><a href="#cb9-2"></a>init_printing(use_latex<span class="op">=</span><span class="st">'mathjax'</span>)</span>
<span id="cb9-3"><a href="#cb9-3"></a>x <span class="op">=</span> Symbol(<span class="st">'x'</span>)</span>
<span id="cb9-4"><a href="#cb9-4"></a>eqn <span class="op">=</span> E<span class="op">**</span>(<span class="op">-</span>x<span class="op">**</span><span class="dv">2</span>)</span>
<span id="cb9-5"><a href="#cb9-5"></a>int_eqn <span class="op">=</span> Integral(eqn, (x, <span class="op">-</span>oo, oo))</span>
<span id="cb9-6"><a href="#cb9-6"></a>int_eqn</span></code></pre></div>
<p><img style="vertical-align:middle" src="data:image/png;base64,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" alt="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" title="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" class="math inline" /></p>
</div>
</div>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.python .cb-nb session=sympy name=sympy2}
int_eqn.doit()
```</code></pre>
</div>
<div class="exampleOutput">
<div class="sourceCode" id="cb11" data-startFrom="7"><pre class="sourceCode numberSource python numberLines"><code class="sourceCode python" style="counter-reset: source-line 6;"><span id="cb11-7"><a href="#cb11-7"></a>int_eqn.doit()</span></code></pre></div>
<p><img style="vertical-align:middle" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABkAAAATBAMAAACXXLs2AAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMma7EJkiq81E3Yl2VO9oNArgAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAkklEQVQYGWNgAAPG/yDwAcJhYHaAMsCUKDKHwQyZx1iAzGNPQOalI3MYAhnY+v///wcRYzFgYE04cAXIYWxgYGAVYBBgu7AByJv0iYHBGUhzOwQASYYqBoadQIqZwQDEk58A1MbAcJvhA4jH0cBzAUh1MnwE8Tg/cgBJlgUMliAew/KzYApK6Dcg8/gUkHmMCA4AfKcdepFzPIwAAAAASUVORK5CYII=" alt="\displaystyle \sqrt{\pi}" title="\displaystyle \sqrt{\pi}" class="math inline" /></p>
</div>
</div>
<p>A Jupyter kernel can provide multiple formats for representing an
object. SymPy typically provides a LaTeX representation, a plain-text
representation, and a PNG representation. By default, Codebraid chooses
display formats in this order of precedence: LaTeX, Markdown, PNG, JPG,
plain. (This can be customized; see <code>rich_output</code> in the
documentation for details.) So Codebraid displays the SymPy math in
LaTeX form. For this to render as nicely as possible in the browser,
Pandoc should be run with one of the flags for rendering math in HTML,
such as <code>--mathjax</code>. For this document, Pandoc was used with
<code>--webtex</code> to convert LaTeX into PNG during the document
build process.</p>
<p><code>cb-paste</code> works with rich output like plots and LaTeX,
just like it normally does with code, stdout, and stderr.</p>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.cb-paste copy=sympy1+sympy2 show=rich_output}
```</code></pre>
</div>
<div class="exampleOutput">
<p><img style="vertical-align:middle" src="data:image/png;base64,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" alt="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" title="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" class="math inline" /></p>
<p><img style="vertical-align:middle" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABkAAAATBAMAAACXXLs2AAAAMFBMVEX///8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAv3aB7AAAAD3RSTlMAMma7EJkiq81E3Yl2VO9oNArgAAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAkklEQVQYGWNgAAPG/yDwAcJhYHaAMsCUKDKHwQyZx1iAzGNPQOalI3MYAhnY+v///wcRYzFgYE04cAXIYWxgYGAVYBBgu7AByJv0iYHBGUhzOwQASYYqBoadQIqZwQDEk58A1MbAcJvhA4jH0cBzAUh1MnwE8Tg/cgBJlgUMliAew/KzYApK6Dcg8/gUkHmMCA4AfKcdepFzPIwAAAAASUVORK5CYII=" alt="\displaystyle \sqrt{\pi}" title="\displaystyle \sqrt{\pi}" class="math inline" /></p>
</div>
</div>
<h2 id="customizing-output">Customizing output</h2>
<p>When working with <code>rich_output</code> formats that have a
<code>text/*</code> mime type, such as LaTeX and Markdown, it is
possible to display the rendered output or show the markup. For example,
using <code>show=rich_output:latex:raw</code> displays the raw
(rendered) LaTeX, while <code>show=rich_output:latex:verbatim</code>
displays the LaTeX markup verbatim.</p>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.cb-paste copy=sympy1 show=rich_output:latex:raw}
```</code></pre>
</div>
<div class="exampleOutput">
<p><img style="vertical-align:middle" src="data:image/png;base64,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" alt="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" title="\displaystyle \int\limits_{-\infty}^{\infty} e^{- x^{2}}\, dx" class="math inline" /></p>
</div>
</div>
<div class="example">
<div class="exampleMarkup">
<pre><code>```{.cb-paste copy=sympy1 show=rich_output:latex:verbatim}
```</code></pre>
</div>
<div class="exampleOutput">
<div class="sourceCode" id="cb15"><pre class="sourceCode latex"><code class="sourceCode latex"><span id="cb15-1"><a href="#cb15-1" aria-hidden="true" tabindex="-1"></a><span class="ss">$</span><span class="sc">\displaystyle</span><span class="ss"> </span><span class="sc">\int\limits</span><span class="ss">_{-</span><span class="sc">\infty</span><span class="ss">}^{</span><span class="sc">\infty</span><span class="ss">} e^{- x^{2}}</span><span class="sc">\,</span><span class="ss"> dx$</span></span></code></pre></div>
</div>
</div>
</body>
</html>