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<section id="spapros-ev-probesetevaluator-load-results">
<h1>spapros.ev.ProbesetEvaluator.load_results<a class="headerlink" href="#spapros-ev-probesetevaluator-load-results" title="Permalink to this heading"></a></h1>
<dl class="py method">
<dt class="sig sig-object py" id="spapros.ev.ProbesetEvaluator.load_results">
<span class="sig-prename descclassname"><span class="pre">ProbesetEvaluator.</span></span><span class="sig-name descname"><span class="pre">load_results</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">directories</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reference_dir</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">['shared',</span> <span class="pre">'pre',</span> <span class="pre">'main',</span> <span class="pre">'summary']</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">set_ids</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">verbosity</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#spapros.ev.ProbesetEvaluator.load_results" title="Permalink to this definition"></a></dt>
<dd><p>Load existing results from files of one or multiple evaluation output directories</p>
<p>In case of multiple directories we assume that the different evaluations were done with the same parameters. You
can control which metrics are loaded by setting <code class="xref py py-attr docutils literal notranslate"><span class="pre">ProbesetEvaluator.metrics</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>directories</strong> (<em>Optional</em><em>[</em><em>Union</em><em>[</em><em>str</em><em>, </em><em>List</em><em>[</em><em>str</em><em>]</em><em>]</em><em>]</em>) – Directory or list of directories of previous evaluations. If <cite>None</cite> is given it’s set to
<code class="xref py py-attr docutils literal notranslate"><span class="pre">ProbesetEvaluator.dir</span></code>.</p></li>
<li><p><strong>reference_dir</strong> (<em>Optional</em><em>[</em><em>str</em><em>]</em>) – Directory with reference results. If <cite>None</cite> is given it’s set to <code class="xref py py-attr docutils literal notranslate"><span class="pre">ProbesetEvaluator.ref_dir</span></code>.</p></li>
<li><p><strong>steps</strong> (<em>List</em><em>[</em><em>str</em><em>]</em>) – <dl class="simple">
<dt>The results steps that are loaded. These include</dt><dd><ul>
<li><p><cite>’shared’</cite> - computations on the reference gene set</p></li>
<li><p><cite>’pre’</cite> - computations on the selected gene set independent of the results on the reference gene set</p></li>
<li><p><cite>’main’</cite> - computations on the selected gene set taking into account the reference gene set results</p></li>
<li><p><cite>’summary’</cite> - summary metrics</p></li>
</ul>
</dd>
</dl>
</p></li>
<li><p><strong>set_ids</strong> (<em>Optional</em><em>[</em><em>List</em><em>[</em><em>str</em><em>]</em><em>]</em>) – Optionally only load the results for a subset of set ids.</p></li>
<li><p><strong>verbosity</strong> (<em>int</em>) – Verbosity level.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>pd.DataFrame</dt><dd><p>A boolean table that indicates which results were loaded for each set_id. Note that some metrics don’t
have result files for certain steps.</p>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p><em>DataFrame</em></p>
</dd>
</dl>
<p class="rubric">Examples</p>
<p>Load results from a previous evaluation</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">spapros</span> <span class="k">as</span> <span class="nn">sp</span>
<span class="n">adata</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ut</span><span class="o">.</span><span class="n">get_processed_pbmc_data</span><span class="p">()</span>
<span class="n">selections</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">se</span><span class="o">.</span><span class="n">select_reference_probesets</span><span class="p">(</span><span class="n">adata</span><span class="p">,</span> <span class="n">methods</span><span class="o">=</span><span class="p">[</span><span class="s2">"DE"</span><span class="p">,</span> <span class="s2">"HVG"</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">evaluator</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ev</span><span class="o">.</span><span class="n">ProbesetEvaluator</span><span class="p">(</span><span class="n">adata</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">results_dir</span><span class="o">=</span><span class="s2">"eval_results"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">set_id</span><span class="p">,</span> <span class="n">df</span> <span class="ow">in</span> <span class="n">selections</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">gene_set</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s2">"selection"</span><span class="p">]]</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">to_list</span><span class="p">()</span>
<span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate_probeset</span><span class="p">(</span><span class="n">gene_set</span><span class="p">,</span> <span class="n">set_id</span><span class="o">=</span><span class="n">set_id</span><span class="p">)</span>
<span class="k">del</span> <span class="n">evaluator</span>
<span class="n">evaluator</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ev</span><span class="o">.</span><span class="n">ProbesetEvaluator</span><span class="p">(</span><span class="n">adata</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">results_dir</span><span class="o">=</span><span class="s2">"eval_results"</span><span class="p">)</span>
<span class="n">df_info</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">load_results</span><span class="p">()</span>
</pre></div>
</div>
<p>Load results from previous evaluations that were distributed in two directories</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">spapros</span> <span class="k">as</span> <span class="nn">sp</span>
<span class="n">adata</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ut</span><span class="o">.</span><span class="n">get_processed_pbmc_data</span><span class="p">()</span>
<span class="n">selections</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">se</span><span class="o">.</span><span class="n">select_reference_probesets</span><span class="p">(</span>
<span class="n">adata</span><span class="p">,</span> <span class="n">methods</span><span class="o">=</span><span class="p">[</span><span class="s2">"DE"</span><span class="p">,</span> <span class="s2">"HVG"</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">evaluator</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ev</span><span class="o">.</span><span class="n">ProbesetEvaluator</span><span class="p">(</span>
<span class="n">adata</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">results_dir</span><span class="o">=</span><span class="s2">"eval_results1"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">set_id</span><span class="p">,</span> <span class="n">df</span> <span class="ow">in</span> <span class="n">selections</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">gene_set</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s2">"selection"</span><span class="p">]]</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">to_list</span><span class="p">()</span>
<span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate_probeset</span><span class="p">(</span><span class="n">gene_set</span><span class="p">,</span> <span class="n">set_id</span><span class="o">=</span><span class="n">set_id</span><span class="p">)</span>
<span class="n">selections</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">se</span><span class="o">.</span><span class="n">select_reference_probesets</span><span class="p">(</span>
<span class="n">adata</span><span class="p">,</span> <span class="n">methods</span><span class="o">=</span><span class="p">[</span><span class="s2">"PCA"</span><span class="p">,</span> <span class="s2">"random"</span><span class="p">],</span> <span class="n">n</span><span class="o">=</span><span class="mi">30</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="n">evaluator</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ev</span><span class="o">.</span><span class="n">ProbesetEvaluator</span><span class="p">(</span>
<span class="n">adata</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">results_dir</span><span class="o">=</span><span class="s2">"eval_results2"</span><span class="p">)</span>
<span class="k">for</span> <span class="n">set_id</span><span class="p">,</span> <span class="n">df</span> <span class="ow">in</span> <span class="n">selections</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
<span class="n">gene_set</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s2">"selection"</span><span class="p">]]</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">to_list</span><span class="p">()</span>
<span class="n">evaluator</span><span class="o">.</span><span class="n">evaluate_probeset</span><span class="p">(</span><span class="n">gene_set</span><span class="p">,</span> <span class="n">set_id</span><span class="o">=</span><span class="n">set_id</span><span class="p">)</span>
<span class="n">evaluator</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">ev</span><span class="o">.</span><span class="n">ProbesetEvaluator</span><span class="p">(</span><span class="n">adata</span><span class="p">,</span> <span class="n">verbosity</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
<span class="n">df_info</span> <span class="o">=</span> <span class="n">evaluator</span><span class="o">.</span><span class="n">load_results</span><span class="p">(</span>
<span class="n">directories</span><span class="o">=</span><span class="p">[</span><span class="s1">'./eval_results1/'</span><span class="p">,</span> <span class="s1">'./eval_results2/'</span><span class="p">],</span> <span class="n">reference_dir</span><span class="o">=</span><span class="s2">"./eval_results1/references"</span><span class="p">)</span>
</pre></div>
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