[skip ci] Updates

ersilia-os · Jun 20, 2024 · c6dc2e1 · c6dc2e1
1 parent 65f3538
commit c6dc2e1
Show file tree

Hide file tree

Showing 6 changed files with 36 additions and 52 deletions.
diff --git a/_modules/ersilia/core/tracking.html b/_modules/ersilia/core/tracking.html
@@ -425,45 +425,49 @@ <h1>Source code for ersilia.core.tracking</h1><div class="highlight"><pre>
  <span class="n">tracemalloc</span><span class="o">.</span><span class="n">start</span><span class="p">()</span>
  <span class="bp">self</span><span class="o">.</span><span class="n">memory_usage_start</span> <span class="o">=</span> <span class="n">tracemalloc</span><span class="o">.</span><span class="n">get_traced_memory</span><span class="p">()[</span><span class="mi">0</span><span class="p">]</span></div>
 
-
-<div class="viewcode-block" id="RunTracker.stats"><a class="viewcode-back" href="../../../source/autodoc/ersilia.core.html#ersilia.core.tracking.RunTracker.stats">[docs]</a> <span class="k">def</span> <span class="nf">stats</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">result</span><span class="p">):</span>
-<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
-<span class="sd"> Stats function: calculates the basic statistics of the output file from a model. This includes the</span>
-<span class="sd"> mode (if applicable), minimum, maximum, and standard deviation.</span>
+
+
+<span class="c1"># TODO: see the following link for more details</span>
+<span class="c1"># https://github.com/ersilia-os/ersilia/issues/1165?notification_referrer_id=NT_kwDOAsB0trQxMTEyNTc5MDIxNzo0NjE2NzIyMg#issuecomment-2178596998</span>
+
+<span class="c1"># def stats(self, result):</span>
+<span class="c1"># &quot;&quot;&quot;</span>
+<span class="c1"># Stats function: calculates the basic statistics of the output file from a model. This includes the</span>
+<span class="c1"># mode (if applicable), minimum, maximum, and standard deviation.</span>
 
-<span class="sd"> :param result: The path to the model&#39;s output file.</span>
-<span class="sd"> :return: A dictionary containing the stats for each column of the result.</span>
-<span class="sd"> &quot;&quot;&quot;</span>
+<span class="c1"># :param result: The path to the model&#39;s output file.</span>
+<span class="c1"># :return: A dictionary containing the stats for each column of the result.</span>
+<span class="c1"># &quot;&quot;&quot;</span>
 
- <span class="n">data</span> <span class="o">=</span> <span class="n">read_csv</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
+<span class="c1"># data = read_csv(result)</span>
 
  <span class="c1"># drop first two columns (key, input)</span>
-  <span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
-  <span class="n">row</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;key&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
-  <span class="n">row</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;input&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+<span class="c1">#  for row in data:</span>
+<span class="c1">#  row.pop(&#39;key&#39;, None)</span>
+<span class="c1">#  row.pop(&#39;input&#39;, None)</span>
 
  <span class="c1"># Convert data to a column-oriented format</span>
- <span class="n">columns</span> <span class="o">=</span> <span class="n">defaultdict</span><span class="p">(</span><span class="nb">list</span><span class="p">)</span>
-  <span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
-  <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">row</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-  <span class="n">columns</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">float</span><span class="p">(</span><span class="n">value</span><span class="p">))</span>
+<span class="c1"># columns = defaultdict(list)</span>
+<span class="c1">#  for row in data:</span>
+<span class="c1">#  for key, value in row.items():</span>
+<span class="c1">#  columns[key].append(float(value))</span>
 
  <span class="c1"># Calculate statistics</span>
- <span class="n">stats</span> <span class="o">=</span> <span class="p">{}</span>
-  <span class="k">for</span> <span class="n">column</span><span class="p">,</span> <span class="n">values</span> <span class="ow">in</span> <span class="n">columns</span><span class="o">.</span><span class="n">items</span><span class="p">():</span>
-  <span class="n">column_stats</span> <span class="o">=</span> <span class="p">{}</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;mean&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">statistics</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
-  <span class="k">try</span><span class="p">:</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;mode&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">statistics</span><span class="o">.</span><span class="n">mode</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
-  <span class="k">except</span> <span class="n">statistics</span><span class="o">.</span><span class="n">StatisticsError</span><span class="p">:</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;mode&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;min&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;max&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
-  <span class="n">column_stats</span><span class="p">[</span><span class="s2">&quot;std&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">statistics</span><span class="o">.</span><span class="n">stdev</span><span class="p">(</span><span class="n">values</span><span class="p">)</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">values</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">1</span> <span class="k">else</span> <span class="mi">0</span>
-
-  <span class="n">stats</span><span class="p">[</span><span class="n">column</span><span class="p">]</span> <span class="o">=</span> <span class="n">column_stats</span>
-
-  <span class="k">return</span> <span class="n">stats</span></div>
+<span class="c1"># stats = {}</span>
+<span class="c1">#  for column, values in columns.items():</span>
+<span class="c1">#  column_stats = {}</span>
+<span class="c1">#  column_stats[&quot;mean&quot;] = statistics.mean(values)</span>
+<span class="c1">#  try:</span>
+<span class="c1">#  column_stats[&quot;mode&quot;] = statistics.mode(values)</span>
+<span class="c1">#  except statistics.StatisticsError:</span>
+<span class="c1">#  column_stats[&quot;mode&quot;] = None</span>
+<span class="c1">#  column_stats[&quot;min&quot;] = min(values)</span>
+<span class="c1">#  column_stats[&quot;max&quot;] = max(values)</span>
+<span class="c1">#  column_stats[&quot;std&quot;] = statistics.stdev(values) if len(values) &gt; 1 else 0</span>
+<span class="c1">#</span>
+<span class="c1">#  stats[column] = column_stats</span>
+
+<span class="c1">#  return stats</span>
 
 
 <div class="viewcode-block" id="RunTracker.get_file_sizes"><a class="viewcode-back" href="../../../source/autodoc/ersilia.core.html#ersilia.core.tracking.RunTracker.get_file_sizes">[docs]</a> <span class="k">def</span> <span class="nf">get_file_sizes</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">input_file</span><span class="p">,</span> <span class="n">output_file</span><span class="p">):</span>
@@ -590,8 +594,6 @@ <h1>Source code for ersilia.core.tracking</h1><div class="highlight"><pre>
  <span class="n">json_dict</span><span class="p">[</span><span class="s2">&quot;nan_count&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">nan_count</span>
 
  <span class="n">json_dict</span><span class="p">[</span><span class="s2">&quot;check_types&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">check_types</span><span class="p">(</span><span class="n">result_data</span><span class="p">,</span> <span class="n">meta</span><span class="p">[</span><span class="s2">&quot;metadata&quot;</span><span class="p">])</span>
-
- <span class="n">json_dict</span><span class="p">[</span><span class="s2">&quot;stats&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">stats</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
 
  <span class="n">json_dict</span><span class="p">[</span><span class="s2">&quot;file_sizes&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_file_sizes</span><span class="p">(</span><span class="n">input_data</span><span class="p">,</span> <span class="n">result_data</span><span class="p">)</span>
 

diff --git a/genindex.html b/genindex.html
@@ -4051,8 +4051,6 @@ <h2 id="S">S</h2>
  <li><a href="source/autodoc/ersilia.core.html#ersilia.core.tracking.RunTracker.start_tracking">start_tracking() (ersilia.core.tracking.RunTracker method)</a>
 </li>
  <li><a href="source/autodoc/ersilia.utils.html#ersilia.utils.conda.SimpleConda.startswith">startswith() (ersilia.utils.conda.SimpleConda method)</a>
-</li>
- <li><a href="source/autodoc/ersilia.core.html#ersilia.core.tracking.RunTracker.stats">stats() (ersilia.core.tracking.RunTracker method)</a>
 </li>
  <li><a href="source/autodoc/ersilia.hub.content.html#ersilia.hub.content.card.BaseInformation.status">status (ersilia.hub.content.card.BaseInformation property)</a>
 </li>

diff --git a/objects.inv b/objects.inv
diff --git a/searchindex.js b/searchindex.js
diff --git a/source/autodoc/ersilia.core.html b/source/autodoc/ersilia.core.html
@@ -358,21 +358,6 @@ <h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this
 Currently necessary for tracking the runtime and memory usage of a run.</p>
 </dd></dl>
 
-<dl class="py method">
-<dt class="sig sig-object py" id="ersilia.core.tracking.RunTracker.stats">
-<span class="sig-name descname"><span class="pre">stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">result</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/ersilia/core/tracking.html#RunTracker.stats"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#ersilia.core.tracking.RunTracker.stats" title="Permalink to this definition"></a></dt>
-<dd><p>Stats function: calculates the basic statistics of the output file from a model. This includes the
-mode (if applicable), minimum, maximum, and standard deviation.</p>
-<dl class="field-list simple">
-<dt class="field-odd">Parameters<span class="colon">:</span></dt>
-<dd class="field-odd"><p><strong>result</strong> – The path to the model’s output file.</p>
-</dd>
-<dt class="field-even">Returns<span class="colon">:</span></dt>
-<dd class="field-even"><p>A dictionary containing the stats for each column of the result.</p>
-</dd>
-</dl>
-</dd></dl>
-
 <dl class="py method">
 <dt class="sig sig-object py" id="ersilia.core.tracking.RunTracker.track">
 <span class="sig-name descname"><span class="pre">track</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">input</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">result</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">meta</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/ersilia/core/tracking.html#RunTracker.track"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#ersilia.core.tracking.RunTracker.track" title="Permalink to this definition"></a></dt>

diff --git a/source/autodoc/ersilia.html b/source/autodoc/ersilia.html
@@ -287,7 +287,6 @@ <h2>Subpackages<a class="headerlink" href="#subpackages" title="Permalink to thi
 <li class="toctree-l4"><a class="reference internal" href="ersilia.core.html#ersilia.core.tracking.RunTracker.log_meta"><code class="docutils literal notranslate"><span class="pre">RunTracker.log_meta()</span></code></a></li>
 <li class="toctree-l4"><a class="reference internal" href="ersilia.core.html#ersilia.core.tracking.RunTracker.log_result"><code class="docutils literal notranslate"><span class="pre">RunTracker.log_result()</span></code></a></li>
 <li class="toctree-l4"><a class="reference internal" href="ersilia.core.html#ersilia.core.tracking.RunTracker.start_tracking"><code class="docutils literal notranslate"><span class="pre">RunTracker.start_tracking()</span></code></a></li>
-<li class="toctree-l4"><a class="reference internal" href="ersilia.core.html#ersilia.core.tracking.RunTracker.stats"><code class="docutils literal notranslate"><span class="pre">RunTracker.stats()</span></code></a></li>
 <li class="toctree-l4"><a class="reference internal" href="ersilia.core.html#ersilia.core.tracking.RunTracker.track"><code class="docutils literal notranslate"><span class="pre">RunTracker.track()</span></code></a></li>
 </ul>
 </li>