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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<title>ClearMap.Analysis.Statistics — ClearMap 0.9.2 documentation</title>
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<h1>Source code for ClearMap.Analysis.Statistics</h1><div class="highlight"><pre>
<span class="c"># -*- coding: utf-8 -*-</span>
<span class="sd">"""</span>
<span class="sd">Create some statistics to test significant changes</span>
<span class="sd">in voxelized and labeled data</span>
<span class="sd">TODO: cleanup / make generic</span>
<span class="sd">"""</span>
<span class="c">#:copyright: Copyright 2015 by Christoph Kirst, The Rockefeller University, New York City</span>
<span class="c">#:license: GNU, see LICENSE.txt for details.</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="bp">self</span> <span class="o">=</span> <span class="n">sys</span><span class="o">.</span><span class="n">modules</span><span class="p">[</span><span class="n">__name__</span><span class="p">];</span>
<span class="kn">import</span> <span class="nn">numpy</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="kn">import</span> <span class="n">stats</span>
<span class="kn">import</span> <span class="nn">ClearMap.IO</span> <span class="kn">as</span> <span class="nn">io</span>
<span class="kn">import</span> <span class="nn">ClearMap.Analysis.Label</span> <span class="kn">as</span> <span class="nn">lbl</span>
<span class="kn">import</span> <span class="nn">ClearMap.Analysis.Tools.StatisticalTests</span> <span class="kn">as</span> <span class="nn">stats2</span>
<div class="viewcode-block" id="readDataGroup"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.readDataGroup">[docs]</a><span class="k">def</span> <span class="nf">readDataGroup</span><span class="p">(</span><span class="n">filenames</span><span class="p">,</span> <span class="n">combine</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">):</span>
<span class="sd">"""Turn a list of filenames for data into a numpy stack"""</span>
<span class="c">#check if stack already:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">filenames</span><span class="p">,</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">filenames</span><span class="p">;</span>
<span class="c">#read the individual files</span>
<span class="n">group</span> <span class="o">=</span> <span class="p">[];</span>
<span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">filenames</span><span class="p">:</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">readData</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">);</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,)</span> <span class="o">+</span> <span class="n">data</span><span class="o">.</span><span class="n">shape</span><span class="p">);</span>
<span class="n">group</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">);</span>
<span class="k">if</span> <span class="n">combine</span><span class="p">:</span>
<span class="k">return</span> <span class="n">numpy</span><span class="o">.</span><span class="n">vstack</span><span class="p">(</span><span class="n">group</span><span class="p">);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">group</span><span class="p">;</span></div>
<div class="viewcode-block" id="readPointsGroup"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.readPointsGroup">[docs]</a><span class="k">def</span> <span class="nf">readPointsGroup</span><span class="p">(</span><span class="n">filenames</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">):</span>
<span class="sd">"""Turn a list of filenames for points into a numpy stack"""</span>
<span class="c">#check if stack already:</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">filenames</span><span class="p">,</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
<span class="k">return</span> <span class="n">filenames</span><span class="p">;</span>
<span class="c">#read the individual files</span>
<span class="n">group</span> <span class="o">=</span> <span class="p">[];</span>
<span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">filenames</span><span class="p">:</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">readPoints</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">);</span>
<span class="c">#data = numpy.reshape(data, (1,) + data.shape);</span>
<span class="n">group</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">);</span>
<span class="k">return</span> <span class="n">group</span></div>
<span class="c">#return numpy.vstack(group);</span>
<div class="viewcode-block" id="tTestVoxelization"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.tTestVoxelization">[docs]</a><span class="k">def</span> <span class="nf">tTestVoxelization</span><span class="p">(</span><span class="n">group1</span><span class="p">,</span> <span class="n">group2</span><span class="p">,</span> <span class="n">signed</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">removeNaN</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">pcutoff</span> <span class="o">=</span> <span class="bp">None</span><span class="p">):</span>
<span class="sd">"""t-Test on differences between the individual voxels in group1 and group2, group is a array of voxelizations"""</span>
<span class="n">g1</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readDataGroup</span><span class="p">(</span><span class="n">group1</span><span class="p">);</span>
<span class="n">g2</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readDataGroup</span><span class="p">(</span><span class="n">group2</span><span class="p">);</span>
<span class="n">tvals</span><span class="p">,</span> <span class="n">pvals</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">ttest_ind</span><span class="p">(</span><span class="n">g1</span><span class="p">,</span> <span class="n">g2</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">equal_var</span> <span class="o">=</span> <span class="bp">True</span><span class="p">);</span>
<span class="c">#remove nans</span>
<span class="k">if</span> <span class="n">removeNaN</span><span class="p">:</span>
<span class="n">pi</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">pvals</span><span class="p">);</span>
<span class="n">pvals</span><span class="p">[</span><span class="n">pi</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">;</span>
<span class="n">tvals</span><span class="p">[</span><span class="n">pi</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
<span class="n">pvals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">cutoffPValues</span><span class="p">(</span><span class="n">pvals</span><span class="p">,</span> <span class="n">pcutoff</span> <span class="o">=</span> <span class="n">pcutoff</span><span class="p">);</span>
<span class="c">#return</span>
<span class="k">if</span> <span class="n">signed</span><span class="p">:</span>
<span class="k">return</span> <span class="n">pvals</span><span class="p">,</span> <span class="n">numpy</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">tvals</span><span class="p">);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">pvals</span><span class="p">;</span></div>
<div class="viewcode-block" id="cutoffPValues"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.cutoffPValues">[docs]</a><span class="k">def</span> <span class="nf">cutoffPValues</span><span class="p">(</span><span class="n">pvals</span><span class="p">,</span> <span class="n">pcutoff</span> <span class="o">=</span> <span class="mf">0.05</span><span class="p">):</span>
<span class="k">if</span> <span class="n">pcutoff</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">pvals</span><span class="p">;</span>
<span class="n">pvals2</span> <span class="o">=</span> <span class="n">pvals</span><span class="o">.</span><span class="n">copy</span><span class="p">();</span>
<span class="n">pvals2</span><span class="p">[</span><span class="n">pvals2</span> <span class="o">></span> <span class="n">pcutoff</span><span class="p">]</span> <span class="o">=</span> <span class="n">pcutoff</span><span class="p">;</span>
<span class="k">return</span> <span class="n">pvals2</span><span class="p">;</span></div>
<div class="viewcode-block" id="colorPValues"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.colorPValues">[docs]</a><span class="k">def</span> <span class="nf">colorPValues</span><span class="p">(</span><span class="n">pvals</span><span class="p">,</span> <span class="n">psign</span><span class="p">,</span> <span class="n">positive</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">],</span> <span class="n">negative</span> <span class="o">=</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">pcutoff</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">positivetrend</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</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">0</span><span class="p">],</span> <span class="n">negativetrend</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</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">pmax</span> <span class="o">=</span> <span class="bp">None</span><span class="p">):</span></div>
<span class="n">pvalsinv</span> <span class="o">=</span> <span class="n">pvals</span><span class="o">.</span><span class="n">copy</span><span class="p">();</span>
<span class="k">if</span> <span class="n">pmax</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">pmax</span> <span class="o">=</span> <span class="n">pvals</span><span class="o">.</span><span class="n">max</span><span class="p">();</span>
<span class="n">pvalsinv</span> <span class="o">=</span> <span class="n">pmax</span> <span class="o">-</span> <span class="n">pvalsinv</span><span class="p">;</span>
<span class="k">if</span> <span class="n">pcutoff</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span> <span class="c"># color given p values</span>
<span class="n">d</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">positive</span><span class="p">);</span>
<span class="n">ds</span> <span class="o">=</span> <span class="n">pvals</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">d</span><span class="p">,);</span>
<span class="n">pvc</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">ds</span><span class="p">);</span>
<span class="c">#color</span>
<span class="n">ids</span> <span class="o">=</span> <span class="n">psign</span> <span class="o">></span> <span class="mi">0</span><span class="p">;</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ids</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ids</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">positive</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="n">ids</span> <span class="o">=</span> <span class="n">psign</span> <span class="o"><</span> <span class="mi">0</span><span class="p">;</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ids</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ids</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">negative</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="k">return</span> <span class="n">pvc</span><span class="p">;</span>
<span class="k">else</span><span class="p">:</span> <span class="c"># split pvalues according to cutoff</span>
<span class="n">d</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">positivetrend</span><span class="p">);</span>
<span class="k">if</span> <span class="n">d</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">positive</span><span class="p">)</span> <span class="ow">or</span> <span class="n">d</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">negative</span><span class="p">)</span> <span class="ow">or</span> <span class="n">d</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">negativetrend</span><span class="p">)</span> <span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'colorPValues: postive, negative, postivetrend and negativetrend option must be equal length!'</span><span class="p">);</span>
<span class="n">ds</span> <span class="o">=</span> <span class="n">pvals</span><span class="o">.</span><span class="n">shape</span> <span class="o">+</span> <span class="p">(</span><span class="n">d</span><span class="p">,);</span>
<span class="n">pvc</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">ds</span><span class="p">);</span>
<span class="n">idc</span> <span class="o">=</span> <span class="n">pvals</span> <span class="o"><</span> <span class="n">pcutoff</span><span class="p">;</span>
<span class="n">ids</span> <span class="o">=</span> <span class="n">psign</span> <span class="o">></span> <span class="mi">0</span><span class="p">;</span>
<span class="c">##color </span>
<span class="c"># significant postive</span>
<span class="n">ii</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">ids</span><span class="p">,</span> <span class="n">idc</span><span class="p">);</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ii</span><span class="p">];</span>
<span class="n">w</span> <span class="o">=</span> <span class="n">positive</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ii</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">w</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="c">#non significant postive</span>
<span class="n">ii</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">ids</span><span class="p">,</span> <span class="n">numpy</span><span class="o">.</span><span class="n">negative</span><span class="p">(</span><span class="n">idc</span><span class="p">));</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ii</span><span class="p">];</span>
<span class="n">w</span> <span class="o">=</span> <span class="n">positivetrend</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ii</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">w</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="c"># significant negative</span>
<span class="n">ii</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">negative</span><span class="p">(</span><span class="n">ids</span><span class="p">),</span> <span class="n">idc</span><span class="p">);</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ii</span><span class="p">];</span>
<span class="n">w</span> <span class="o">=</span> <span class="n">negative</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ii</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">w</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="c">#non significant postive</span>
<span class="n">ii</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">numpy</span><span class="o">.</span><span class="n">negative</span><span class="p">(</span><span class="n">ids</span><span class="p">),</span> <span class="n">numpy</span><span class="o">.</span><span class="n">negative</span><span class="p">(</span><span class="n">idc</span><span class="p">))</span>
<span class="n">pvalsi</span> <span class="o">=</span> <span class="n">pvalsinv</span><span class="p">[</span><span class="n">ii</span><span class="p">];</span>
<span class="n">w</span> <span class="o">=</span> <span class="n">negativetrend</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">d</span><span class="p">):</span>
<span class="n">pvc</span><span class="p">[</span><span class="n">ii</span><span class="p">,</span> <span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">pvalsi</span> <span class="o">*</span> <span class="n">w</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="k">return</span> <span class="n">pvc</span><span class="p">;</span>
<div class="viewcode-block" id="mean"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.mean">[docs]</a><span class="k">def</span> <span class="nf">mean</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">):</span>
<span class="n">g</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readGroup</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">);</span>
<span class="k">return</span> <span class="n">g</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">);</span></div>
<div class="viewcode-block" id="std"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.std">[docs]</a><span class="k">def</span> <span class="nf">std</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">):</span>
<span class="n">g</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readGroup</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">);</span>
<span class="k">return</span> <span class="n">g</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">);</span></div>
<div class="viewcode-block" id="var"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.var">[docs]</a><span class="k">def</span> <span class="nf">var</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">):</span>
<span class="n">g</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">readGroup</span><span class="p">(</span><span class="n">group</span><span class="p">,</span> <span class="o">**</span><span class="n">args</span><span class="p">);</span>
<span class="k">return</span> <span class="n">g</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">);</span> </div>
<div class="viewcode-block" id="thresholdPoints"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.thresholdPoints">[docs]</a><span class="k">def</span> <span class="nf">thresholdPoints</span><span class="p">(</span><span class="n">points</span><span class="p">,</span> <span class="n">intensities</span><span class="p">,</span> <span class="n">threshold</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">row</span> <span class="o">=</span> <span class="mi">0</span><span class="p">):</span>
<span class="sd">"""Threshold points by intensities"""</span>
<span class="n">points</span><span class="p">,</span> <span class="n">intensities</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">readPoints</span><span class="p">((</span><span class="n">points</span><span class="p">,</span> <span class="n">intensities</span><span class="p">));</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">threshold</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
<span class="n">threshold</span> <span class="o">=</span> <span class="p">(</span><span class="n">threshold</span><span class="p">,</span> <span class="nb">all</span><span class="p">);</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">row</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">):</span>
<span class="n">row</span> <span class="o">=</span> <span class="p">(</span><span class="n">row</span><span class="p">,</span> <span class="n">row</span><span class="p">);</span>
<span class="k">if</span> <span class="n">intensities</span><span class="o">.</span><span class="n">ndim</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
<span class="n">i</span> <span class="o">=</span> <span class="n">intensities</span><span class="p">[:,</span><span class="n">row</span><span class="p">[</span><span class="mi">0</span><span class="p">]];</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">i</span> <span class="o">=</span> <span class="n">intensities</span><span class="p">;</span>
<span class="n">iids</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">i</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span> <span class="o">=</span> <span class="s">'bool'</span><span class="p">);</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">threshold</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="ow">is</span> <span class="nb">all</span><span class="p">:</span>
<span class="n">iids</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">iids</span><span class="p">,</span> <span class="n">i</span> <span class="o">>=</span> <span class="n">threshold</span><span class="p">[</span><span class="mi">0</span><span class="p">]);</span>
<span class="k">if</span> <span class="n">intensities</span><span class="o">.</span><span class="n">ndim</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
<span class="n">i</span> <span class="o">=</span> <span class="n">intensities</span><span class="p">[:,</span><span class="n">row</span><span class="p">[</span><span class="mi">1</span><span class="p">]];</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">threshold</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="ow">is</span> <span class="nb">all</span><span class="p">:</span>
<span class="n">iids</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">logical_and</span><span class="p">(</span><span class="n">iids</span><span class="p">,</span> <span class="n">i</span> <span class="o"><=</span> <span class="n">threshold</span><span class="p">[</span><span class="mi">1</span><span class="p">]);</span>
<span class="k">return</span> <span class="p">(</span><span class="n">points</span><span class="p">[</span><span class="n">iids</span><span class="p">,</span> <span class="o">...</span><span class="p">],</span> <span class="n">intensities</span><span class="p">[</span><span class="n">iids</span><span class="p">,</span> <span class="o">...</span><span class="p">]);</span></div>
<div class="viewcode-block" id="weightsFromPrecentiles"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.weightsFromPrecentiles">[docs]</a><span class="k">def</span> <span class="nf">weightsFromPrecentiles</span><span class="p">(</span><span class="n">intensities</span><span class="p">,</span> <span class="n">percentiles</span> <span class="o">=</span> <span class="p">[</span><span class="mi">25</span><span class="p">,</span><span class="mi">50</span><span class="p">,</span><span class="mi">75</span><span class="p">,</span><span class="mi">100</span><span class="p">]):</span>
<span class="n">perc</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">percentiles</span><span class="p">(</span><span class="n">intensities</span><span class="p">,</span> <span class="n">percentiles</span><span class="p">);</span>
<span class="n">weights</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">intensities</span><span class="o">.</span><span class="n">shape</span><span class="p">);</span>
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">perc</span><span class="p">:</span>
<span class="n">ii</span> <span class="o">=</span> <span class="n">intensities</span> <span class="o">></span> <span class="n">p</span><span class="p">;</span>
<span class="n">weights</span><span class="p">[</span><span class="n">ii</span><span class="p">]</span> <span class="o">=</span> <span class="n">weights</span><span class="p">[</span><span class="n">ii</span><span class="p">]</span> <span class="o">+</span> <span class="mi">1</span><span class="p">;</span>
<span class="k">return</span> <span class="n">weights</span><span class="p">;</span></div>
<span class="c"># needs clean up</span>
<div class="viewcode-block" id="countPointsGroupInRegions"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.countPointsGroupInRegions">[docs]</a><span class="k">def</span> <span class="nf">countPointsGroupInRegions</span><span class="p">(</span><span class="n">pointGroup</span><span class="p">,</span> <span class="n">labeledImage</span> <span class="o">=</span> <span class="n">lbl</span><span class="o">.</span><span class="n">DefaultLabeledImageFile</span><span class="p">,</span> <span class="n">intensityGroup</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">intensityRow</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="n">returnIds</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">returnCounts</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">collapse</span> <span class="o">=</span> <span class="bp">None</span><span class="p">):</span>
<span class="sd">"""Generates a table of counts for the various point datasets in pointGroup"""</span>
<span class="k">if</span> <span class="n">intensityGroup</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">counts</span> <span class="o">=</span> <span class="p">[</span><span class="n">lbl</span><span class="o">.</span><span class="n">countPointsInRegions</span><span class="p">(</span><span class="n">pointGroup</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">labeledImage</span> <span class="o">=</span> <span class="n">labeledImage</span><span class="p">,</span> <span class="n">sort</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">allIds</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">returnIds</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">returnCounts</span> <span class="o">=</span> <span class="n">returnCounts</span><span class="p">,</span> <span class="n">intensities</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">collapse</span> <span class="o">=</span> <span class="n">collapse</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="nb">len</span><span class="p">(</span><span class="n">pointGroup</span><span class="p">))];</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">counts</span> <span class="o">=</span> <span class="p">[</span><span class="n">lbl</span><span class="o">.</span><span class="n">countPointsInRegions</span><span class="p">(</span><span class="n">pointGroup</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">labeledImage</span> <span class="o">=</span> <span class="n">labeledImage</span><span class="p">,</span> <span class="n">sort</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">allIds</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">returnIds</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">returnCounts</span> <span class="o">=</span> <span class="n">returnCounts</span><span class="p">,</span>
<span class="n">intensities</span> <span class="o">=</span> <span class="n">intensityGroup</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">intensityRow</span> <span class="o">=</span> <span class="n">intensityRow</span><span class="p">,</span> <span class="n">collapse</span> <span class="o">=</span> <span class="n">collapse</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="nb">len</span><span class="p">(</span><span class="n">pointGroup</span><span class="p">))];</span>
<span class="k">if</span> <span class="n">returnCounts</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">intensityGroup</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">countsi</span> <span class="o">=</span> <span class="p">(</span><span class="n">c</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">counts</span><span class="p">);</span>
<span class="n">counts</span> <span class="o">=</span> <span class="p">(</span><span class="n">c</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">counts</span><span class="p">);</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">countsi</span> <span class="o">=</span> <span class="bp">None</span><span class="p">;</span>
<span class="n">counts</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">c</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">counts</span><span class="p">))</span><span class="o">.</span><span class="n">T</span><span class="p">;</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">countsi</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="n">countsi</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">vstack</span><span class="p">((</span><span class="n">c</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">countsi</span><span class="p">))</span><span class="o">.</span><span class="n">T</span><span class="p">;</span>
<span class="k">if</span> <span class="n">returnIds</span><span class="p">:</span>
<span class="n">ids</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">sort</span><span class="p">(</span><span class="n">lbl</span><span class="o">.</span><span class="n">Label</span><span class="o">.</span><span class="n">ids</span><span class="p">);</span>
<span class="c">#ids.shape = (1,) + ids.shape;</span>
<span class="c">#return numpy.concatenate((ids.T,counts), axis = 1</span>
<span class="k">if</span> <span class="n">countsi</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">ids</span><span class="p">,</span> <span class="n">counts</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">ids</span><span class="p">,</span> <span class="n">counts</span><span class="p">,</span> <span class="n">countsi</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="n">countsi</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="k">return</span> <span class="n">counts</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">counts</span><span class="p">,</span> <span class="n">countsi</span></div>
<span class="c"># needs clean up</span>
<div class="viewcode-block" id="tTestPointsInRegions"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.tTestPointsInRegions">[docs]</a><span class="k">def</span> <span class="nf">tTestPointsInRegions</span><span class="p">(</span><span class="n">pointCounts1</span><span class="p">,</span> <span class="n">pointCounts2</span><span class="p">,</span> <span class="n">labeledImage</span> <span class="o">=</span> <span class="n">lbl</span><span class="o">.</span><span class="n">DefaultLabeledImageFile</span><span class="p">,</span> <span class="n">signed</span> <span class="o">=</span> <span class="bp">False</span><span class="p">,</span> <span class="n">removeNaN</span> <span class="o">=</span> <span class="bp">True</span><span class="p">,</span> <span class="n">pcutoff</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">equal_var</span> <span class="o">=</span> <span class="bp">False</span><span class="p">):</span>
<span class="sd">"""t-Test on differences in counts of points in labeled regions"""</span>
<span class="c">#ids, p1 = countPointsGroupInRegions(pointGroup1, labeledImage = labeledImage, withIds = True);</span>
<span class="c">#p2 = countPointsGroupInRegions(pointGroup2, labeledImage = labeledImage, withIds = False); </span>
<span class="n">tvals</span><span class="p">,</span> <span class="n">pvals</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">ttest_ind</span><span class="p">(</span><span class="n">pointCounts1</span><span class="p">,</span> <span class="n">pointCounts2</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">equal_var</span> <span class="o">=</span> <span class="n">equal_var</span><span class="p">);</span>
<span class="c">#remove nans</span>
<span class="k">if</span> <span class="n">removeNaN</span><span class="p">:</span>
<span class="n">pi</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">pvals</span><span class="p">);</span>
<span class="n">pvals</span><span class="p">[</span><span class="n">pi</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">;</span>
<span class="n">tvals</span><span class="p">[</span><span class="n">pi</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
<span class="n">pvals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">cutoffPValues</span><span class="p">(</span><span class="n">pvals</span><span class="p">,</span> <span class="n">pcutoff</span> <span class="o">=</span> <span class="n">pcutoff</span><span class="p">);</span>
<span class="c">#pvals.shape = (1,) + pvals.shape;</span>
<span class="c">#ids.shape = (1,) + ids.shape;</span>
<span class="c">#pvals = numpy.concatenate((ids.T, pvals.T), axis = 1);</span>
<span class="k">if</span> <span class="n">signed</span><span class="p">:</span>
<span class="k">return</span> <span class="n">pvals</span><span class="p">,</span> <span class="n">numpy</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">tvals</span><span class="p">);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">pvals</span><span class="p">;</span></div>
<div class="viewcode-block" id="testCompletedCumulatives"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.testCompletedCumulatives">[docs]</a><span class="k">def</span> <span class="nf">testCompletedCumulatives</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">method</span> <span class="o">=</span> <span class="s">'AndersonDarling'</span><span class="p">,</span> <span class="n">offset</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">plot</span> <span class="o">=</span> <span class="bp">False</span><span class="p">):</span>
<span class="sd">"""Test if data sets have the same number / intensity distribution by adding max intensity counts to the smaller sized data sets and performing a distribution comparison test"""</span>
<span class="c">#idea: fill up data points to the same numbers at the high intensity values and use KS test</span>
<span class="c">#cf. work in progress on thoouroghly testing the differences in histograms</span>
<span class="c">#fill up the low count data</span>
<span class="n">n</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">size</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]);</span>
<span class="n">nm</span> <span class="o">=</span> <span class="n">n</span><span class="o">.</span><span class="n">max</span><span class="p">();</span>
<span class="n">m</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]);</span>
<span class="n">mm</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="n">max</span><span class="p">();</span>
<span class="n">k</span> <span class="o">=</span> <span class="n">n</span><span class="o">.</span><span class="n">size</span><span class="p">;</span>
<span class="c">#print nm, mm, k</span>
<span class="k">if</span> <span class="n">offset</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="c">#assume data starts at 0 !</span>
<span class="n">offset</span> <span class="o">=</span> <span class="n">mm</span> <span class="o">/</span> <span class="n">nm</span><span class="p">;</span> <span class="c">#ideall for all statistics this should be mm + eps to have as little influence as possible.</span>
<span class="n">datac</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</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">m</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
<span class="k">if</span> <span class="n">n</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o"><</span> <span class="n">nm</span><span class="p">:</span>
<span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">concatenate</span><span class="p">((</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">nm</span><span class="o">-</span><span class="n">n</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="n">mm</span> <span class="o">+</span> <span class="n">offset</span><span class="p">)));</span> <span class="c"># + 10E-5 * numpy.random.rand(nm-n[i])));</span>
<span class="c">#test by plotting</span>
<span class="k">if</span> <span class="n">plot</span> <span class="ow">is</span> <span class="bp">True</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="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">m</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
<span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">sort</span><span class="p">();</span>
<span class="n">plt</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">numpy</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">size</span><span class="p">));</span>
<span class="c">#perfomr the tests</span>
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'KolmogorovSmirnov'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'KS'</span><span class="p">:</span>
<span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">ks_2samp</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">datac</span><span class="p">[</span><span class="mi">1</span><span class="p">]);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'KolmogorovSmirnov only for 2 samples not </span><span class="si">%d</span><span class="s">'</span> <span class="o">%</span> <span class="n">k</span><span class="p">);</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'CramervonMises'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'CM'</span><span class="p">:</span>
<span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span><span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats2</span><span class="o">.</span><span class="n">testCramerVonMises2Sample</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">datac</span><span class="p">[</span><span class="mi">1</span><span class="p">]);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'CramervonMises only for 2 samples not </span><span class="si">%d</span><span class="s">'</span> <span class="o">%</span> <span class="n">k</span><span class="p">);</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'AndersonDarling'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'AD'</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span><span class="n">a</span><span class="p">,</span><span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">anderson_ksamp</span><span class="p">(</span><span class="n">datac</span><span class="p">);</span>
<span class="k">return</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">s</span><span class="p">);</span></div>
<div class="viewcode-block" id="testCompletedInvertedCumulatives"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.testCompletedInvertedCumulatives">[docs]</a><span class="k">def</span> <span class="nf">testCompletedInvertedCumulatives</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">method</span> <span class="o">=</span> <span class="s">'AndersonDarling'</span><span class="p">,</span> <span class="n">offset</span> <span class="o">=</span> <span class="bp">None</span><span class="p">,</span> <span class="n">plot</span> <span class="o">=</span> <span class="bp">False</span><span class="p">):</span>
<span class="sd">"""Test if data sets have the same number / intensity distribution by adding zero intensity counts to the smaller sized data sets and performing a distribution comparison test on the reversed cumulative distribution"""</span>
<span class="c">#idea: fill up data points to the same numbers at the high intensity values and use KS test</span>
<span class="c">#cf. work in progress on thoouroghly testing the differences in histograms</span>
<span class="c">#fill up the low count data</span>
<span class="n">n</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">size</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]);</span>
<span class="n">nm</span> <span class="o">=</span> <span class="n">n</span><span class="o">.</span><span class="n">max</span><span class="p">();</span>
<span class="n">m</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">x</span><span class="o">.</span><span class="n">max</span><span class="p">()</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]);</span>
<span class="n">mm</span> <span class="o">=</span> <span class="n">m</span><span class="o">.</span><span class="n">max</span><span class="p">();</span>
<span class="n">k</span> <span class="o">=</span> <span class="n">n</span><span class="o">.</span><span class="n">size</span><span class="p">;</span>
<span class="c">#print nm, mm, k</span>
<span class="k">if</span> <span class="n">offset</span> <span class="ow">is</span> <span class="bp">None</span><span class="p">:</span>
<span class="c">#assume data starts at 0 !</span>
<span class="n">offset</span> <span class="o">=</span> <span class="n">mm</span> <span class="o">/</span> <span class="n">nm</span><span class="p">;</span> <span class="c">#ideall for all statistics this should be mm + eps to have as little influence as possible.</span>
<span class="n">datac</span> <span class="o">=</span> <span class="p">[</span><span class="n">x</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</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">m</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
<span class="k">if</span> <span class="n">n</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o"><</span> <span class="n">nm</span><span class="p">:</span>
<span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">concatenate</span><span class="p">((</span><span class="o">-</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ones</span><span class="p">(</span><span class="n">nm</span><span class="o">-</span><span class="n">n</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">dtype</span> <span class="o">=</span> <span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="n">offset</span><span class="p">)));</span> <span class="c"># + 10E-5 * numpy.random.rand(nm-n[i])));</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">];</span>
<span class="c">#test by plotting</span>
<span class="k">if</span> <span class="n">plot</span> <span class="ow">is</span> <span class="bp">True</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="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">m</span><span class="o">.</span><span class="n">size</span><span class="p">):</span>
<span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">sort</span><span class="p">();</span>
<span class="n">plt</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">numpy</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="o">.</span><span class="n">size</span><span class="p">));</span>
<span class="c">#perfomr the tests</span>
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'KolmogorovSmirnov'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'KS'</span><span class="p">:</span>
<span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span> <span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">ks_2samp</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">datac</span><span class="p">[</span><span class="mi">1</span><span class="p">]);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'KolmogorovSmirnov only for 2 samples not </span><span class="si">%d</span><span class="s">'</span> <span class="o">%</span> <span class="n">k</span><span class="p">);</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'CramervonMises'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'CM'</span><span class="p">:</span>
<span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span><span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats2</span><span class="o">.</span><span class="n">testCramerVonMises2Sample</span><span class="p">(</span><span class="n">datac</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">datac</span><span class="p">[</span><span class="mi">1</span><span class="p">]);</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'CramervonMises only for 2 samples not </span><span class="si">%d</span><span class="s">'</span> <span class="o">%</span> <span class="n">k</span><span class="p">);</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'AndersonDarling'</span> <span class="ow">or</span> <span class="n">method</span> <span class="o">==</span> <span class="s">'AD'</span><span class="p">:</span>
<span class="p">(</span><span class="n">s</span><span class="p">,</span><span class="n">a</span><span class="p">,</span><span class="n">p</span><span class="p">)</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">anderson_ksamp</span><span class="p">(</span><span class="n">datac</span><span class="p">);</span>
<span class="k">return</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">s</span><span class="p">);</span></div>
<div class="viewcode-block" id="testCompletedCumulativesInSpheres"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.testCompletedCumulativesInSpheres">[docs]</a><span class="k">def</span> <span class="nf">testCompletedCumulativesInSpheres</span><span class="p">(</span><span class="n">points1</span><span class="p">,</span> <span class="n">intensities1</span><span class="p">,</span> <span class="n">points2</span><span class="p">,</span> <span class="n">intensities2</span><span class="p">,</span> <span class="n">dataSize</span> <span class="o">=</span> <span class="n">lbl</span><span class="o">.</span><span class="n">DefaultLabeledImageFile</span><span class="p">,</span> <span class="n">radius</span> <span class="o">=</span> <span class="mi">100</span><span class="p">,</span> <span class="n">method</span> <span class="o">=</span> <span class="s">'AndresonDarling'</span><span class="p">):</span>
<span class="sd">"""Performs completed cumulative distribution tests for each pixel using points in a ball centered at that cooridnates, returns 4 arrays p value, statistic value, number in each group"""</span>
<span class="c">#TODO: sinple implementation -> slow -> speed up</span>
<span class="n">dataSize</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">dataSize</span><span class="p">(</span><span class="n">dataSize</span><span class="p">);</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">dataSize</span><span class="p">)</span> <span class="o">!=</span> <span class="mi">3</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="s">'dataSize expected to be 3d'</span><span class="p">);</span>
<span class="c"># distances^2 to origin</span>
<span class="n">x1</span><span class="o">=</span> <span class="n">points1</span><span class="p">[:,</span><span class="mi">0</span><span class="p">];</span> <span class="n">y1</span> <span class="o">=</span> <span class="n">points1</span><span class="p">[:,</span><span class="mi">1</span><span class="p">];</span> <span class="n">z1</span> <span class="o">=</span> <span class="n">points1</span><span class="p">[:,</span><span class="mi">2</span><span class="p">];</span> <span class="n">i1</span> <span class="o">=</span> <span class="n">intensities1</span><span class="p">;</span>
<span class="n">d1</span> <span class="o">=</span> <span class="n">x1</span> <span class="o">*</span> <span class="n">x1</span> <span class="o">+</span> <span class="n">y1</span> <span class="o">*</span> <span class="n">y1</span> <span class="o">+</span> <span class="n">z1</span> <span class="o">*</span> <span class="n">z1</span><span class="p">;</span>
<span class="n">x2</span> <span class="o">=</span> <span class="n">points2</span><span class="p">[:,</span><span class="mi">0</span><span class="p">];</span> <span class="n">y2</span> <span class="o">=</span> <span class="n">points2</span><span class="p">[:,</span><span class="mi">1</span><span class="p">];</span> <span class="n">z2</span> <span class="o">=</span> <span class="n">points2</span><span class="p">[:,</span><span class="mi">2</span><span class="p">];</span> <span class="n">i2</span> <span class="o">=</span> <span class="n">intensities2</span><span class="p">;</span>
<span class="n">d2</span> <span class="o">=</span> <span class="n">x2</span> <span class="o">*</span> <span class="n">x2</span> <span class="o">+</span> <span class="n">y2</span> <span class="o">*</span> <span class="n">y2</span> <span class="o">+</span> <span class="n">z2</span> <span class="o">*</span> <span class="n">z2</span><span class="p">;</span>
<span class="n">r2</span> <span class="o">=</span> <span class="n">radius</span> <span class="o">*</span> <span class="n">radius</span><span class="p">;</span> <span class="c"># TODO: inhomogenous in 3d !</span>
<span class="n">p</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">dataSize</span><span class="p">);</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">dataSize</span><span class="p">);</span>
<span class="n">n1</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">dataSize</span><span class="p">,</span> <span class="n">dtype</span> <span class="o">=</span> <span class="s">'int'</span><span class="p">);</span>
<span class="n">n2</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">dataSize</span><span class="p">,</span> <span class="n">dtype</span> <span class="o">=</span> <span class="s">'int'</span><span class="p">);</span>
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dataSize</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
<span class="c">#print x</span>
<span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dataSize</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
<span class="c">#print y</span>
<span class="k">for</span> <span class="n">z</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">dataSize</span><span class="p">[</span><span class="mi">2</span><span class="p">]):</span>
<span class="c">#print z</span>
<span class="n">d11</span> <span class="o">=</span> <span class="n">d1</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="n">x</span> <span class="o">*</span> <span class="n">x1</span> <span class="o">+</span> <span class="n">y</span> <span class="o">*</span> <span class="n">y1</span> <span class="o">+</span> <span class="n">z</span> <span class="o">*</span> <span class="n">z1</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">x</span> <span class="o">+</span> <span class="n">y</span><span class="o">*</span><span class="n">y</span> <span class="o">+</span> <span class="n">z</span><span class="o">*</span><span class="n">z</span><span class="p">);</span>
<span class="n">d22</span> <span class="o">=</span> <span class="n">d2</span> <span class="o">-</span> <span class="mi">2</span> <span class="o">*</span> <span class="p">(</span><span class="n">x</span> <span class="o">*</span> <span class="n">x2</span> <span class="o">+</span> <span class="n">y</span> <span class="o">*</span> <span class="n">y2</span> <span class="o">+</span> <span class="n">z</span> <span class="o">*</span> <span class="n">z2</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">x</span> <span class="o">+</span> <span class="n">y</span><span class="o">*</span><span class="n">y</span> <span class="o">+</span> <span class="n">z</span><span class="o">*</span><span class="n">z</span><span class="p">);</span>
<span class="n">ii1</span> <span class="o">=</span> <span class="n">d11</span> <span class="o"><</span> <span class="n">r2</span><span class="p">;</span>
<span class="n">ii2</span> <span class="o">=</span> <span class="n">d22</span> <span class="o"><</span> <span class="n">r2</span><span class="p">;</span>
<span class="n">n1</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">z</span><span class="p">]</span> <span class="o">=</span> <span class="n">ii1</span><span class="o">.</span><span class="n">sum</span><span class="p">();</span>
<span class="n">n2</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">z</span><span class="p">]</span> <span class="o">=</span> <span class="n">ii2</span><span class="o">.</span><span class="n">sum</span><span class="p">();</span>
<span class="k">if</span> <span class="n">n1</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">z</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">n2</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">z</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
<span class="p">(</span><span class="n">pp</span><span class="p">,</span> <span class="n">ss</span><span class="p">)</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">testCompletedCumulatives</span><span class="p">((</span><span class="n">i1</span><span class="p">[</span><span class="n">ii1</span><span class="p">],</span> <span class="n">i2</span><span class="p">[</span><span class="n">ii2</span><span class="p">]),</span> <span class="n">method</span> <span class="o">=</span> <span class="n">method</span><span class="p">);</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">pp</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span> <span class="n">ss</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
<span class="n">p</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">z</span><span class="p">]</span> <span class="o">=</span> <span class="n">pp</span><span class="p">;</span>
<span class="n">s</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">z</span><span class="p">]</span> <span class="o">=</span> <span class="n">ss</span><span class="p">;</span>
<span class="k">return</span> <span class="p">(</span><span class="n">p</span><span class="p">,</span><span class="n">s</span><span class="p">,</span><span class="n">n1</span><span class="p">,</span><span class="n">n2</span><span class="p">);</span></div>
<div class="viewcode-block" id="test"><a class="viewcode-back" href="../../../api/ClearMap.Analysis.html#ClearMap.Analysis.Statistics.test">[docs]</a><span class="k">def</span> <span class="nf">test</span><span class="p">():</span>
<span class="sd">"""Test the statistics array"""</span>
<span class="kn">import</span> <span class="nn">ClearMap.Analysis.Statistics</span> <span class="kn">as</span> <span class="nn">self</span>
<span class="nb">reload</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">numpy</span><span class="o">,</span> <span class="nn">os</span>
<span class="c">#x = stats.norm.rvs(loc=5,scale=1,size=1500)</span>
<span class="c">#y = stats.norm.rvs(loc=-5,scale=1,size=1500)</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">ones</span><span class="p">((</span><span class="mi">5</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">20</span><span class="p">));</span>
<span class="n">s</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">:</span><span class="mi">3</span><span class="p">,</span> <span class="p">:]</span> <span class="o">=</span> <span class="o">-</span> <span class="mi">1</span><span class="p">;</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">20</span><span class="p">);</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">numpy</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">rand</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span><span class="mi">4</span><span class="p">,</span><span class="mi">20</span><span class="p">)</span> <span class="o">+</span> <span class="n">s</span><span class="p">;</span>
<span class="c"># print stats.ttest_ind(x,y, axis = 0, equal_var = False);</span>
<span class="n">pvals</span><span class="p">,</span> <span class="n">psign</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tTestVoxelization</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">signed</span> <span class="o">=</span> <span class="bp">True</span><span class="p">);</span>
<span class="k">print</span> <span class="n">pvals</span>
<span class="n">pvalscol</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">colorPValues</span><span class="p">(</span><span class="n">pvals</span><span class="p">,</span> <span class="n">psign</span><span class="p">,</span> <span class="n">positive</span> <span class="o">=</span> <span class="p">[</span><span class="mi">255</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">],</span> <span class="n">negative</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">255</span><span class="p">,</span><span class="mi">0</span><span class="p">])</span>
<span class="kn">import</span> <span class="nn">ClearMap.Visualization.Plot</span> <span class="kn">as</span> <span class="nn">plt</span>
<span class="n">plt</span><span class="o">.</span><span class="n">plotTiling</span><span class="p">(</span><span class="n">pvalscol</span><span class="p">)</span>
<span class="c"># test points</span>
<span class="kn">import</span> <span class="nn">ClearMap.Settings</span> <span class="kn">as</span> <span class="nn">settings</span>
<span class="n">pf</span> <span class="o">=</span> <span class="n">os</span><span class="o">.</span><span class="n">path</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">settings</span><span class="o">.</span><span class="n">ClearMapPath</span><span class="p">,</span> <span class="s">'Test/Synthetic/cells_transformed_to_reference.csv'</span><span class="p">);</span>
<span class="n">pg</span> <span class="o">=</span> <span class="p">(</span><span class="n">pf</span><span class="p">,</span><span class="n">pf</span><span class="p">);</span>
<span class="n">pc</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">countPointsGroupInRegions</span><span class="p">(</span><span class="n">pg</span><span class="p">);</span>
<span class="n">pvals</span><span class="p">,</span> <span class="n">tvals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">tTestPointsInRegions</span><span class="p">(</span><span class="n">pg</span><span class="p">,</span> <span class="n">pg</span><span class="p">,</span> <span class="n">signed</span> <span class="o">=</span> <span class="bp">True</span><span class="p">);</span></div>
<span class="k">if</span> <span class="n">__name__</span> <span class="o">==</span> <span class="s">"__main__"</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">test</span><span class="p">();</span>
</pre></div>
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