deploy: 06ca9cf

cavalab · Dec 21, 2023 · 56a0f48 · 56a0f48
1 parent dfac4e8
commit 56a0f48
Showing 1 changed file with 15 additions and 9 deletions.
diff --git a/_modules/fomo/estimator.html b/_modules/fomo/estimator.html
@@ -240,6 +240,7 @@ <h1>Source code for fomo.estimator</h1><div class="highlight"><pre>
 <span class="kn">import</span> <span class="nn">math</span>
 <span class="kn">import</span> <span class="nn">uuid</span> 
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
 <span class="kn">from</span> <span class="nn">sklearn.base</span> <span class="kn">import</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">ClassifierMixin</span><span class="p">,</span> <span class="n">RegressorMixin</span>
 <span class="kn">from</span> <span class="nn">sklearn.utils.validation</span> <span class="kn">import</span> <span class="n">check_X_y</span><span class="p">,</span> <span class="n">check_array</span><span class="p">,</span> <span class="n">check_is_fitted</span>
 <span class="kn">from</span> <span class="nn">sklearn.utils.multiclass</span> <span class="kn">import</span> <span class="n">unique_labels</span>
@@ -545,11 +546,7 @@ <h1>Source code for fomo.estimator</h1><div class="highlight"><pre>
         <span class="n">check_is_fitted</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s1">&#39;is_fitted_&#39;</span><span class="p">)</span>
         <span class="n">I</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">I_</span>
         <span class="n">F</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_signed_F</span><span class="p">()</span>
-        <span class="n">axis_labels</span> <span class="o">=</span> <span class="p">(</span>
-            <span class="p">[</span> <span class="n">am</span><span class="o">.</span><span class="n">_score_func</span><span class="o">.</span><span class="vm">__name__</span> <span class="k">for</span> <span class="n">am</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">accuracy_metrics_</span> <span class="p">]</span> 
-            <span class="o">+</span> <span class="p">[</span> <span class="n">fn</span><span class="o">.</span><span class="vm">__name__</span> <span class="k">for</span> <span class="n">fn</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">fairness_metrics_</span> <span class="p">]</span>
-        <span class="p">)</span>
-        <span class="n">axis_labels</span> <span class="o">=</span> <span class="p">[</span><span class="n">al</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;_&#39;</span><span class="p">,</span><span class="s1">&#39; &#39;</span><span class="p">)</span> <span class="k">for</span> <span class="n">al</span> <span class="ow">in</span> <span class="n">axis_labels</span><span class="p">]</span>
+        <span class="n">axis_labels</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_objective_names</span><span class="p">()</span>
         <span class="n">plot</span> <span class="o">=</span> <span class="p">(</span>
             <span class="n">Scatter</span><span class="p">()</span>
             <span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">F</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s1">&#39;Candidate models&#39;</span><span class="p">)</span>
@@ -573,12 +570,21 @@ <h1>Source code for fomo.estimator</h1><div class="highlight"><pre>
                 <span class="n">F</span><span class="p">[:,</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">F</span><span class="p">[:,</span><span class="n">i</span><span class="p">]</span><span class="o">*</span><span class="n">m</span><span class="o">.</span><span class="n">_sign</span>
         <span class="k">return</span> <span class="n">F</span>
 
+    <span class="k">def</span> <span class="nf">_get_objective_names</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;Returns names of functions defining the objectives&quot;&quot;&quot;</span>
+        <span class="n">labels</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="p">[</span> <span class="n">m</span><span class="o">.</span><span class="n">_score_func</span><span class="o">.</span><span class="vm">__name__</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">accuracy_metrics_</span> <span class="p">]</span> 
+            <span class="o">+</span> <span class="p">[</span> <span class="n">fn</span><span class="o">.</span><span class="vm">__name__</span> <span class="k">for</span> <span class="n">fn</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">fairness_metrics_</span> <span class="p">]</span>
+        <span class="p">)</span>
+        <span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="n">l</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">&#39;_&#39;</span><span class="p">,</span><span class="s1">&#39; &#39;</span><span class="p">)</span> <span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">labels</span><span class="p">]</span>
+        <span class="k">return</span> <span class="n">labels</span>
+
     <span class="k">def</span> <span class="nf">get_pareto_points</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;Return a Pandas dataframe of the Pareto archive points&quot;&quot;&quot;</span>
-        <span class="n">archive</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">_get_signed_F</span><span class="p">(),</span> 
-            <span class="n">columns</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">accuracy_metrics_</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">fairness_metrics_</span>
-        <span class="p">)</span>
+        <span class="n">F</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_signed_F</span><span class="p">()</span> 
+        <span class="n">I</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">I_</span>
+        <span class="n">archive</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">F</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">_get_objective_names</span><span class="p">())</span>
+        <span class="n">archive</span><span class="p">[</span><span class="s1">&#39;chosen&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[</span><span class="nb">all</span><span class="p">(</span><span class="n">f</span><span class="o">==</span><span class="n">F</span><span class="p">[</span><span class="n">I</span><span class="p">])</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">F</span><span class="p">]</span>
         <span class="k">return</span> <span class="n">archive</span>
 
 <div class="viewcode-block" id="FomoClassifier">