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<div class="section" id="old-animation-example-code-movie-demo-py">
<span id="old-animation-movie-demo"></span><h1>old_animation example code: movie_demo.py<a class="headerlink" href="#old-animation-example-code-movie-demo-py" title="Permalink to this headline">ΒΆ</a></h1>
<p>[<a class="reference external" href="movie_demo.py">source code</a>]</p>
<div class="highlight-python"><div class="highlight"><pre><span class="c">#!/usr/bin/python</span>
<span class="c">#</span>
<span class="c"># Josh Lifton 2004</span>
<span class="c">#</span>
<span class="c"># Permission is hereby granted to use and abuse this document</span>
<span class="c"># so long as proper attribution is given.</span>
<span class="c">#</span>
<span class="c"># This Python script demonstrates how to use the numarray package</span>
<span class="c"># to generate and handle large arrays of data and how to use the</span>
<span class="c"># matplotlib package to generate plots from the data and then save</span>
<span class="c"># those plots as images. These images are then stitched together</span>
<span class="c"># by Mencoder to create a movie of the plotted data. This script</span>
<span class="c"># is for demonstration purposes only and is not intended to be</span>
<span class="c"># for general use. In particular, you will likely need to modify</span>
<span class="c"># the script to suit your own needs.</span>
<span class="c">#</span>
<span class="kn">import</span> <span class="nn">matplotlib</span>
<span class="n">matplotlib</span><span class="o">.</span><span class="n">use</span><span class="p">(</span><span class="s">'Agg'</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="kn">as</span> <span class="nn">plt</span> <span class="c"># For plotting graphs.</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">subprocess</span> <span class="c"># For issuing commands to the OS.</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">sys</span> <span class="c"># For determining the Python version.</span>
<span class="c">#</span>
<span class="c"># Print the version information for the machine, OS,</span>
<span class="c"># Python interpreter, and matplotlib. The version of</span>
<span class="c"># Mencoder is printed when it is called.</span>
<span class="c">#</span>
<span class="k">print</span> <span class="s">'Executing on'</span><span class="p">,</span> <span class="n">os</span><span class="o">.</span><span class="n">uname</span><span class="p">()</span>
<span class="k">print</span> <span class="s">'Python version'</span><span class="p">,</span> <span class="n">sys</span><span class="o">.</span><span class="n">version</span>
<span class="k">print</span> <span class="s">'matplotlib version'</span><span class="p">,</span> <span class="n">matplotlib</span><span class="o">.</span><span class="n">__version__</span>
<span class="n">not_found_msg</span> <span class="o">=</span> <span class="s">"""</span>
<span class="s">The mencoder command was not found;</span>
<span class="s">mencoder is used by this script to make an avi file from a set of pngs.</span>
<span class="s">It is typically not installed by default on linux distros because of</span>
<span class="s">legal restrictions, but it is widely available.</span>
<span class="s">"""</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">subprocess</span><span class="o">.</span><span class="n">check_call</span><span class="p">([</span><span class="s">'mencoder'</span><span class="p">])</span>
<span class="k">except</span> <span class="n">subprocess</span><span class="o">.</span><span class="n">CalledProcessError</span><span class="p">:</span>
<span class="k">print</span> <span class="s">"mencoder command was found"</span>
<span class="k">pass</span> <span class="c"># mencoder is found, but returns non-zero exit as expected</span>
<span class="c"># This is a quick and dirty check; it leaves some spurious output</span>
<span class="c"># for the user to puzzle over.</span>
<span class="k">except</span> <span class="ne">OSError</span><span class="p">:</span>
<span class="k">print</span> <span class="n">not_found_msg</span>
<span class="n">sys</span><span class="o">.</span><span class="n">exit</span><span class="p">(</span><span class="s">"quitting</span><span class="se">\n</span><span class="s">"</span><span class="p">)</span>
<span class="c">#</span>
<span class="c"># First, let's create some data to work with. In this example</span>
<span class="c"># we'll use a normalized Gaussian waveform whose mean and</span>
<span class="c"># standard deviation both increase linearly with time. Such a</span>
<span class="c"># waveform can be thought of as a propagating system that loses</span>
<span class="c"># coherence over time, as might happen to the probability</span>
<span class="c"># distribution of a clock subjected to independent, identically</span>
<span class="c"># distributed Gaussian noise at each time step.</span>
<span class="c">#</span>
<span class="k">print</span> <span class="s">'Initializing data set...'</span> <span class="c"># Let the user know what's happening.</span>
<span class="c"># Initialize variables needed to create and store the example data set.</span>
<span class="n">numberOfTimeSteps</span> <span class="o">=</span> <span class="mi">100</span> <span class="c"># Number of frames we want in the movie.</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="o">-</span><span class="mi">10</span><span class="p">,</span><span class="mi">10</span><span class="p">,</span><span class="mf">0.01</span><span class="p">)</span> <span class="c"># Values to be plotted on the x-axis.</span>
<span class="n">mean</span> <span class="o">=</span> <span class="o">-</span><span class="mi">6</span> <span class="c"># Initial mean of the Gaussian.</span>
<span class="n">stddev</span> <span class="o">=</span> <span class="mf">0.2</span> <span class="c"># Initial standard deviation.</span>
<span class="n">meaninc</span> <span class="o">=</span> <span class="mf">0.1</span> <span class="c"># Mean increment.</span>
<span class="n">stddevinc</span> <span class="o">=</span> <span class="mf">0.1</span> <span class="c"># Standard deviation increment.</span>
<span class="c"># Create an array of zeros and fill it with the example data.</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">numberOfTimeSteps</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)),</span> <span class="nb">float</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">numberOfTimeSteps</span><span class="p">)</span> <span class="p">:</span>
<span class="n">y</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">*</span><span class="n">stddev</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="p">((</span><span class="n">x</span><span class="o">-</span><span class="n">mean</span><span class="p">)</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">stddev</span><span class="p">))</span>
<span class="n">mean</span> <span class="o">=</span> <span class="n">mean</span> <span class="o">+</span> <span class="n">meaninc</span>
<span class="n">stddev</span> <span class="o">=</span> <span class="n">stddev</span> <span class="o">+</span> <span class="n">stddevinc</span>
<span class="k">print</span> <span class="s">'Done.'</span> <span class="c"># Let the user know what's happening.</span>
<span class="c">#</span>
<span class="c"># Now that we have an example data set (x,y) to work with, we can</span>
<span class="c"># start graphing it and saving the images.</span>
<span class="c">#</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="nb">len</span><span class="p">(</span><span class="n">y</span><span class="p">))</span> <span class="p">:</span>
<span class="c">#</span>
<span class="c"># The next four lines are just like MATLAB.</span>
<span class="c">#</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span><span class="n">y</span><span class="p">[</span><span class="n">i</span><span class="p">],</span><span class="s">'b.'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">axis</span><span class="p">((</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="n">x</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span><span class="o">-</span><span class="mf">0.25</span><span class="p">,</span><span class="mi">1</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s">'time (ms)'</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s">'probability density function'</span><span class="p">)</span>
<span class="c">#</span>
<span class="c"># Notice the use of LaTeX-like markup.</span>
<span class="c">#</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s">r'$\cal{N}(\mu, \sigma^2)$'</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="c">#</span>
<span class="c"># The file name indicates how the image will be saved and the</span>
<span class="c"># order it will appear in the movie. If you actually wanted each</span>
<span class="c"># graph to be displayed on the screen, you would include commands</span>
<span class="c"># such as show() and draw() here. See the matplotlib</span>
<span class="c"># documentation for details. In this case, we are saving the</span>
<span class="c"># images directly to a file without displaying them.</span>
<span class="c">#</span>
<span class="n">filename</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="s">'</span><span class="si">%03d</span><span class="s">'</span> <span class="o">%</span> <span class="n">i</span><span class="p">)</span> <span class="o">+</span> <span class="s">'.png'</span>
<span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">dpi</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span>
<span class="c">#</span>
<span class="c"># Let the user know what's happening.</span>
<span class="c">#</span>
<span class="k">print</span> <span class="s">'Wrote file'</span><span class="p">,</span> <span class="n">filename</span>
<span class="c">#</span>
<span class="c"># Clear the figure to make way for the next image.</span>
<span class="c">#</span>
<span class="n">plt</span><span class="o">.</span><span class="n">clf</span><span class="p">()</span>
<span class="c">#</span>
<span class="c"># Now that we have graphed images of the dataset, we will stitch them</span>
<span class="c"># together using Mencoder to create a movie. Each image will become</span>
<span class="c"># a single frame in the movie.</span>
<span class="c">#</span>
<span class="c"># We want to use Python to make what would normally be a command line</span>
<span class="c"># call to Mencoder. Specifically, the command line call we want to</span>
<span class="c"># emulate is (without the initial '#'):</span>
<span class="c"># mencoder mf://*.png -mf type=png:w=800:h=600:fps=25 -ovc lavc -lavcopts vcodec=mpeg4 -oac copy -o output.avi</span>
<span class="c"># See the MPlayer and Mencoder documentation for details.</span>
<span class="c">#</span>
<span class="n">command</span> <span class="o">=</span> <span class="p">(</span><span class="s">'mencoder'</span><span class="p">,</span>
<span class="s">'mf://*.png'</span><span class="p">,</span>
<span class="s">'-mf'</span><span class="p">,</span>
<span class="s">'type=png:w=800:h=600:fps=25'</span><span class="p">,</span>
<span class="s">'-ovc'</span><span class="p">,</span>
<span class="s">'lavc'</span><span class="p">,</span>
<span class="s">'-lavcopts'</span><span class="p">,</span>
<span class="s">'vcodec=mpeg4'</span><span class="p">,</span>
<span class="s">'-oac'</span><span class="p">,</span>
<span class="s">'copy'</span><span class="p">,</span>
<span class="s">'-o'</span><span class="p">,</span>
<span class="s">'output.avi'</span><span class="p">)</span>
<span class="c">#os.spawnvp(os.P_WAIT, 'mencoder', command)</span>
<span class="k">print</span> <span class="s">"</span><span class="se">\n\n</span><span class="s">about to execute:</span><span class="se">\n</span><span class="si">%s</span><span class="se">\n\n</span><span class="s">"</span> <span class="o">%</span> <span class="s">' '</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="n">subprocess</span><span class="o">.</span><span class="n">check_call</span><span class="p">(</span><span class="n">command</span><span class="p">)</span>
<span class="k">print</span> <span class="s">"</span><span class="se">\n\n</span><span class="s"> The movie was written to 'output.avi'"</span>
<span class="k">print</span> <span class="s">"</span><span class="se">\n\n</span><span class="s"> You may want to delete *.png now.</span><span class="se">\n\n</span><span class="s">"</span>
</pre></div>
</div>
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