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<div class="section" id="publication-quality-plot-production-with-matplotlib">
<h1>Publication-quality plot production with <strong>matplotlib</strong><a class="headerlink" href="#publication-quality-plot-production-with-matplotlib" title="Permalink to this headline">¶</a></h1>
<p>This document deals with producing production-quality plots from SimPy
simulation output using the <strong>matplotlib</strong> library. matplotlib is known to
work on Linux, Unix, MS Windows and OS X platforms. This library is not part
of the SimPy distribution and has to be downloaded and installed separately.</p>
<p>Simulation programs normally produce large quantities of output which needs to
be visualized, e.g. by plotting. These plots can help with aggregating data,
e.g. for detecting trends over time, frequency distributions or determining
the warm-up period of a simulation model experiment.</p>
<p>SimPy’s SimPlot plotting package is an easy to use, out-of-the-box capability
which can produce a full range of plot graphs on the screen and in PostScript
format. After installing SimPy, it can be used without installing any other
software. It is tightly integrated with SimPy, e.g. its Monitor data collection
class.</p>
<p>The SimPlot library is not intended to produce publication-quality plots. If
you want to publish your plots in a report or on the web, consider using an
external plotting library which can be called rom Python.</p>
<div class="section" id="about-matplotlib">
<h2>About matplotlib<a class="headerlink" href="#about-matplotlib" title="Permalink to this headline">¶</a></h2>
<p>A very popular plotting library for Python is matplotlib. Its capabilities far
exceed those of SimPy’s SimPlot. This is how matplotlib is described on its
home page:</p>
<blockquote>
<div><em>“matplotlib is a python 2D plotting library which produces publication
quality figures in a variety of hardcopy formats and interactive
environments across platforms. matplotlib can be used in python scripts,
the python and ipython shell (a la matlab or mathematica), web application
servers, and six graphical user interface toolkits.”</em></div></blockquote>
<p>The matplotlib screenshots (with Python code) at
<a class="reference external" href="http://matplotlib.sourceforge.net/users/screenshots.html">http://matplotlib.sourceforge.net/users/screenshots.html</a> show the great range
of quality displays the library can produce with little coding. For the
investment in time in downloading, installing and learning matplotlib, the
SimPy user is rewarded with a powerful plotting capability.</p>
<div class="section" id="downloading-matplotlib">
<h3>Downloading matplotlib<a class="headerlink" href="#downloading-matplotlib" title="Permalink to this headline">¶</a></h3>
<p>You can download matplotlib from <a class="reference external" href="https://sourceforge.net/projects/matplotlib">https://sourceforge.net/projects/matplotlib</a>.
Extensive installation instructions are provided at
<a class="reference external" href="http://matplotlib.sourceforge.net/users/installing.html">http://matplotlib.sourceforge.net/users/installing.html</a>.</p>
</div>
<div class="section" id="matplotlib-input-data">
<h3>matplotlib input data<a class="headerlink" href="#matplotlib-input-data" title="Permalink to this headline">¶</a></h3>
<p>matplotlib takes separate sequences (lists, tuples, arrays) for x- and
y-values. SimPlot, on the other hand, plots Monitor instances, i.e., lists of
[x,y] lists.</p>
<p>This difference in data structures is easy to overcome in SimPy by using the
Monitor functions <code class="docutils literal"><span class="pre">yseries</span></code> (returning the list of y-data) and <code class="docutils literal"><span class="pre">tseries</span></code>
(returning the list of time- or x-data).</p>
</div>
<div class="section" id="an-example-from-the-bank-tutorial">
<h3>An example from the Bank Tutorial<a class="headerlink" href="#an-example-from-the-bank-tutorial" title="Permalink to this headline">¶</a></h3>
<p>As an example of how to use matplotlib with SimPy, a modified version of
bank12.py from the Bank Tutorial is used here. It produces a line plot of the
counter’s queue length and a histogram of the customer wait times:</p>
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80</pre></div></td><td class="code"><div class="highlight"><pre><span></span><span class="ch">#! /usr/local/bin/python</span>
<span class="sd">""" Based on bank12.py in Bank Tutorial.</span>
<span class="sd"> This program uses matplotlib. It produces two plots:</span>
<span class="sd"> - Queue length over time</span>
<span class="sd"> - Histogram of queue length</span>
<span class="sd">"""</span>
<span class="kn">from</span> <span class="nn">SimPy.Simulation</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">import</span> <span class="nn">pylab</span> <span class="kn">as</span> <span class="nn">pyl</span>
<span class="kn">from</span> <span class="nn">random</span> <span class="kn">import</span> <span class="n">Random</span>
<span class="c1">## Model components</span>
<span class="k">class</span> <span class="nc">Source</span><span class="p">(</span><span class="n">Process</span><span class="p">):</span>
<span class="sd">""" Source generates customers randomly"""</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">seed</span><span class="o">=</span><span class="mi">333</span><span class="p">):</span>
<span class="n">Process</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">SEED</span> <span class="o">=</span> <span class="n">seed</span>
<span class="k">def</span> <span class="nf">generate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">number</span><span class="p">,</span><span class="n">interval</span><span class="p">):</span>
<span class="n">rv</span> <span class="o">=</span> <span class="n">Random</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">SEED</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">number</span><span class="p">):</span>
<span class="n">c</span> <span class="o">=</span> <span class="n">Customer</span><span class="p">(</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Customer</span><span class="si">%02d</span><span class="s2">"</span><span class="o">%</span><span class="p">(</span><span class="n">i</span><span class="p">,))</span>
<span class="n">activate</span><span class="p">(</span><span class="n">c</span><span class="p">,</span><span class="n">c</span><span class="o">.</span><span class="n">visit</span><span class="p">(</span><span class="n">timeInBank</span><span class="o">=</span><span class="mf">12.0</span><span class="p">))</span>
<span class="n">t</span> <span class="o">=</span> <span class="n">rv</span><span class="o">.</span><span class="n">expovariate</span><span class="p">(</span><span class="mf">1.0</span><span class="o">/</span><span class="n">interval</span><span class="p">)</span>
<span class="k">yield</span> <span class="n">hold</span><span class="p">,</span><span class="bp">self</span><span class="p">,</span><span class="n">t</span>
<span class="k">class</span> <span class="nc">Customer</span><span class="p">(</span><span class="n">Process</span><span class="p">):</span>
<span class="sd">""" Customer arrives, is served and leaves """</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">name</span><span class="p">):</span>
<span class="n">Process</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
<span class="k">def</span> <span class="nf">visit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">timeInBank</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
<span class="n">arrive</span><span class="o">=</span><span class="n">now</span><span class="p">()</span>
<span class="k">yield</span> <span class="n">request</span><span class="p">,</span><span class="bp">self</span><span class="p">,</span><span class="n">counter</span>
<span class="n">wait</span><span class="o">=</span><span class="n">now</span><span class="p">()</span><span class="o">-</span><span class="n">arrive</span>
<span class="n">wate</span><span class="o">.</span><span class="n">observe</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="n">wait</span><span class="p">)</span>
<span class="n">tib</span> <span class="o">=</span> <span class="n">counterRV</span><span class="o">.</span><span class="n">expovariate</span><span class="p">(</span><span class="mf">1.0</span><span class="o">/</span><span class="n">timeInBank</span><span class="p">)</span>
<span class="k">yield</span> <span class="n">hold</span><span class="p">,</span><span class="bp">self</span><span class="p">,</span><span class="n">tib</span>
<span class="k">yield</span> <span class="n">release</span><span class="p">,</span><span class="bp">self</span><span class="p">,</span><span class="n">counter</span>
<span class="k">class</span> <span class="nc">Observer</span><span class="p">(</span><span class="n">Process</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">Process</span><span class="o">.</span><span class="n">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="k">def</span> <span class="nf">observe</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">while</span> <span class="bp">True</span><span class="p">:</span>
<span class="k">yield</span> <span class="n">hold</span><span class="p">,</span><span class="bp">self</span><span class="p">,</span><span class="mi">5</span>
<span class="n">qu</span><span class="o">.</span><span class="n">observe</span><span class="p">(</span><span class="n">y</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">counter</span><span class="o">.</span><span class="n">waitQ</span><span class="p">))</span>
<span class="c1">## Model</span>
<span class="k">def</span> <span class="nf">model</span><span class="p">(</span><span class="n">counterseed</span><span class="o">=</span><span class="mi">3939393</span><span class="p">):</span>
<span class="k">global</span> <span class="n">counter</span><span class="p">,</span><span class="n">counterRV</span><span class="p">,</span><span class="n">waitMonitor</span>
<span class="n">counter</span> <span class="o">=</span> <span class="n">Resource</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Clerk"</span><span class="p">,</span><span class="n">capacity</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>
<span class="n">counterRV</span> <span class="o">=</span> <span class="n">Random</span><span class="p">(</span><span class="n">counterseed</span><span class="p">)</span>
<span class="n">waitMonitor</span> <span class="o">=</span> <span class="n">Monitor</span><span class="p">()</span>
<span class="n">initialize</span><span class="p">()</span>
<span class="n">sourceseed</span><span class="o">=</span><span class="mi">1133</span>
<span class="n">source</span> <span class="o">=</span> <span class="n">Source</span><span class="p">(</span><span class="n">seed</span> <span class="o">=</span> <span class="n">sourceseed</span><span class="p">)</span>
<span class="n">activate</span><span class="p">(</span><span class="n">source</span><span class="p">,</span><span class="n">source</span><span class="o">.</span><span class="n">generate</span><span class="p">(</span><span class="mi">100</span><span class="p">,</span><span class="mf">10.0</span><span class="p">))</span>
<span class="n">ob</span><span class="o">=</span><span class="n">Observer</span><span class="p">()</span>
<span class="n">activate</span><span class="p">(</span><span class="n">ob</span><span class="p">,</span><span class="n">ob</span><span class="o">.</span><span class="n">observe</span><span class="p">())</span>
<span class="n">simulate</span><span class="p">(</span><span class="n">until</span><span class="o">=</span><span class="mf">2000.0</span><span class="p">)</span>
<span class="n">qu</span><span class="o">=</span><span class="n">Monitor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Queue length"</span><span class="p">)</span>
<span class="n">wate</span><span class="o">=</span><span class="n">Monitor</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Wait time"</span><span class="p">)</span>
<span class="c1">## Experiment data</span>
<span class="n">sourceSeed</span><span class="o">=</span><span class="mi">333</span>
<span class="c1">## Experiment</span>
<span class="n">model</span><span class="p">()</span>
<span class="c1">## Output</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mf">5.5</span><span class="p">,</span><span class="mi">4</span><span class="p">))</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">qu</span><span class="o">.</span><span class="n">tseries</span><span class="p">(),</span><span class="n">qu</span><span class="o">.</span><span class="n">yseries</span><span class="p">())</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Bank12: queue length over time"</span><span class="p">,</span>
<span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">"time"</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">"queue length before counter"</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="bp">True</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="s2">r".\bank12.png"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">clf</span><span class="p">()</span>
<span class="n">n</span><span class="p">,</span> <span class="n">bins</span><span class="p">,</span> <span class="n">patches</span> <span class="o">=</span> <span class="n">pyl</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">qu</span><span class="o">.</span><span class="n">yseries</span><span class="p">(),</span> <span class="mi">10</span><span class="p">,</span> <span class="n">normed</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">"Bank12: Frequency of counter queue length"</span><span class="p">,</span>
<span class="n">fontsize</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">"queuelength"</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">"frequency"</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">9</span><span class="p">,</span><span class="n">fontweight</span><span class="o">=</span><span class="s2">"bold"</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="bp">True</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">xlim</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="mi">30</span><span class="p">)</span>
<span class="n">pyl</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="s2">r".\bank12histo.png"</span><span class="p">)</span>
</pre></div>
</td></tr></table></div>
<p>Here is the explanation of this program:</p>
<p><strong>Line number and explanation</strong></p>
<dl class="docutils">
<dt>01</dt>
<dd>Imports the matplotlib <strong>pylab</strong> module (this import form is needed to avoid
namespace clashes with SimPy).</dd>
<dt>63</dt>
<dd>Sets the size of the figures following to a width of 5.5 and a height of 4 inches.</dd>
<dt>64</dt>
<dd>Plots the series of queue-length values (qu.yseries()) over their observation
times series (qu.tseries()).</dd>
<dt>65</dt>
<dd>Sets the figure title, its font size, and its font weight.</dd>
<dt>67</dt>
<dd>Sets the x-axis label, its font size, and its font weight.</dd>
<dt>68</dt>
<dd>Sets the y-axis label, its font size, and its font weight.</dd>
<dt>69</dt>
<dd>Gives the graph a grid.</dd>
<dt>70</dt>
<dd>Saves the plot under the given name.</dd>
</dl>
<p>72 Clears the current figure (e.g., resets the axes values from the previous plot).</p>
<dl class="docutils">
<dt>73</dt>
<dd>Makes a histogram of the queue-length series (qu.series()) with 10 bins. The <em>normed</em>
parameter makes the frequency counts relative to 1.</dd>
<dt>74</dt>
<dd>Sets the title etc.</dd>
<dt>76</dt>
<dd>Sets the x-axis label etc.</dd>
<dt>77</dt>
<dd>Sets the y-axis label etc.</dd>
<dt>78</dt>
<dd>Gives the graph a grid.</dd>
<dt>79</dt>
<dd>Limits the x-axis to the range[0..30].</dd>
<dt>80</dt>
<dd>Saves the plot under the given name.</dd>
</dl>
<p>Running the program above results in two PNG files. The first (<code class="docutils literal"><span class="pre">bank12.png</span></code>)
shows the queue length over time:</p>
<img alt="../../../_images/bank12.png" src="../../../_images/bank12.png" />
<p>The second output file (<code class="docutils literal"><span class="pre">bank12histo.png</span></code>) is a histogram of the customer
queue length at the counter:</p>
<img alt="../../../_images/bank12histo.png" src="../../../_images/bank12histo.png" />
</div>
</div>
<div class="section" id="conclusion">
<h2>Conclusion<a class="headerlink" href="#conclusion" title="Permalink to this headline">¶</a></h2>
<p>The small example above already shows the power, flexibility and quality of the
graphics capabilities provided by matplotlib. Almost anything (fonts, graph
sizes, line types, number of series in one plot, number of subplots in a plot,
...) is under user control by setting parameters or calling functions.
Admittedly, it initially takes a lot of reading in the extensive documentation
and some experimentation, but the results are definitely worth the effort!</p>
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<li><a class="reference internal" href="#">Publication-quality plot production with <strong>matplotlib</strong></a><ul>
<li><a class="reference internal" href="#about-matplotlib">About matplotlib</a><ul>
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