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Enhance tests coverage and report output

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Ricardo Montañana Gómez
2024-04-30 14:00:24 +02:00
parent b4a222b100
commit 3c7382a93a
947 changed files with 376596 additions and 3921 deletions
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html/bayesnet/feature_selection/FCBF.cc.gcov.html
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@@ -37,7 +37,7 @@
</tr>
<tr>
<td class="headerItem">Test Date:</td>
<td class="headerValue">2024-04-29 20:48:03</td>
<td class="headerValue">2024-04-30 13:59:18</td>
<td></td>
<td class="headerItem">Functions:</td>
<td class="headerCovTableEntryHi">100.0&nbsp;%</td>
@@ -70,45 +70,45 @@
<span id="L8"><span class="lineNum"> 8</span> : #include &quot;FCBF.h&quot;</span>
<span id="L9"><span class="lineNum"> 9</span> : namespace bayesnet {</span>
<span id="L10"><span class="lineNum"> 10</span> : </span>
<span id="L11"><span class="lineNum"> 11</span> <span class="tlaGNC tlaBgGNC"> 78 : FCBF::FCBF(const torch::Tensor&amp; samples, const std::vector&lt;std::string&gt;&amp; features, const std::string&amp; className, const int maxFeatures, const int classNumStates, const torch::Tensor&amp; weights, const double threshold) :</span></span>
<span id="L12"><span class="lineNum"> 12</span> <span class="tlaGNC"> 78 : FeatureSelect(samples, features, className, maxFeatures, classNumStates, weights), threshold(threshold)</span></span>
<span id="L11"><span class="lineNum"> 11</span> <span class="tlaGNC tlaBgGNC"> 48 : FCBF::FCBF(const torch::Tensor&amp; samples, const std::vector&lt;std::string&gt;&amp; features, const std::string&amp; className, const int maxFeatures, const int classNumStates, const torch::Tensor&amp; weights, const double threshold) :</span></span>
<span id="L12"><span class="lineNum"> 12</span> <span class="tlaGNC"> 48 : FeatureSelect(samples, features, className, maxFeatures, classNumStates, weights), threshold(threshold)</span></span>
<span id="L13"><span class="lineNum"> 13</span> : {</span>
<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 78 : if (threshold &lt; 1e-7) {</span></span>
<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 22 : throw std::invalid_argument(&quot;Threshold cannot be less than 1e-7&quot;);</span></span>
<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 48 : if (threshold &lt; 1e-7) {</span></span>
<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 14 : throw std::invalid_argument(&quot;Threshold cannot be less than 1e-7&quot;);</span></span>
<span id="L16"><span class="lineNum"> 16</span> : }</span>
<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 78 : }</span></span>
<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 56 : void FCBF::fit()</span></span>
<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 48 : }</span></span>
<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 34 : void FCBF::fit()</span></span>
<span id="L19"><span class="lineNum"> 19</span> : {</span>
<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 56 : initialize();</span></span>
<span id="L21"><span class="lineNum"> 21</span> <span class="tlaGNC"> 56 : computeSuLabels();</span></span>
<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 56 : auto featureOrder = argsort(suLabels); // sort descending order</span></span>
<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 56 : auto featureOrderCopy = featureOrder;</span></span>
<span id="L24"><span class="lineNum"> 24</span> <span class="tlaGNC"> 472 : for (const auto&amp; feature : featureOrder) {</span></span>
<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 34 : initialize();</span></span>
<span id="L21"><span class="lineNum"> 21</span> <span class="tlaGNC"> 34 : computeSuLabels();</span></span>
<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 34 : auto featureOrder = argsort(suLabels); // sort descending order</span></span>
<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 34 : auto featureOrderCopy = featureOrder;</span></span>
<span id="L24"><span class="lineNum"> 24</span> <span class="tlaGNC"> 284 : for (const auto&amp; feature : featureOrder) {</span></span>
<span id="L25"><span class="lineNum"> 25</span> : // Don't self compare</span>
<span id="L26"><span class="lineNum"> 26</span> <span class="tlaGNC"> 416 : featureOrderCopy.erase(featureOrderCopy.begin());</span></span>
<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 416 : if (suLabels.at(feature) == 0.0) {</span></span>
<span id="L26"><span class="lineNum"> 26</span> <span class="tlaGNC"> 250 : featureOrderCopy.erase(featureOrderCopy.begin());</span></span>
<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 250 : if (suLabels.at(feature) == 0.0) {</span></span>
<span id="L28"><span class="lineNum"> 28</span> : // The feature has been removed from the list</span>
<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 180 : continue;</span></span>
<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 108 : continue;</span></span>
<span id="L30"><span class="lineNum"> 30</span> : }</span>
<span id="L31"><span class="lineNum"> 31</span> <span class="tlaGNC"> 236 : if (suLabels.at(feature) &lt; threshold) {</span></span>
<span id="L31"><span class="lineNum"> 31</span> <span class="tlaGNC"> 142 : if (suLabels.at(feature) &lt; threshold) {</span></span>
<span id="L32"><span class="lineNum"> 32</span> <span class="tlaUNC tlaBgUNC"> 0 : break;</span></span>
<span id="L33"><span class="lineNum"> 33</span> : }</span>
<span id="L34"><span class="lineNum"> 34</span> : // Remove redundant features</span>
<span id="L35"><span class="lineNum"> 35</span> <span class="tlaGNC tlaBgGNC"> 1307 : for (const auto&amp; featureCopy : featureOrderCopy) {</span></span>
<span id="L36"><span class="lineNum"> 36</span> <span class="tlaGNC"> 1071 : double value = computeSuFeatures(feature, featureCopy);</span></span>
<span id="L37"><span class="lineNum"> 37</span> <span class="tlaGNC"> 1071 : if (value &gt;= suLabels.at(featureCopy)) {</span></span>
<span id="L35"><span class="lineNum"> 35</span> <span class="tlaGNC tlaBgGNC"> 781 : for (const auto&amp; featureCopy : featureOrderCopy) {</span></span>
<span id="L36"><span class="lineNum"> 36</span> <span class="tlaGNC"> 639 : double value = computeSuFeatures(feature, featureCopy);</span></span>
<span id="L37"><span class="lineNum"> 37</span> <span class="tlaGNC"> 639 : if (value &gt;= suLabels.at(featureCopy)) {</span></span>
<span id="L38"><span class="lineNum"> 38</span> : // Remove feature from list</span>
<span id="L39"><span class="lineNum"> 39</span> <span class="tlaGNC"> 373 : suLabels[featureCopy] = 0.0;</span></span>
<span id="L39"><span class="lineNum"> 39</span> <span class="tlaGNC"> 221 : suLabels[featureCopy] = 0.0;</span></span>
<span id="L40"><span class="lineNum"> 40</span> : }</span>
<span id="L41"><span class="lineNum"> 41</span> : }</span>
<span id="L42"><span class="lineNum"> 42</span> <span class="tlaGNC"> 236 : selectedFeatures.push_back(feature);</span></span>
<span id="L43"><span class="lineNum"> 43</span> <span class="tlaGNC"> 236 : selectedScores.push_back(suLabels[feature]);</span></span>
<span id="L44"><span class="lineNum"> 44</span> <span class="tlaGNC"> 236 : if (selectedFeatures.size() == maxFeatures) {</span></span>
<span id="L42"><span class="lineNum"> 42</span> <span class="tlaGNC"> 142 : selectedFeatures.push_back(feature);</span></span>
<span id="L43"><span class="lineNum"> 43</span> <span class="tlaGNC"> 142 : selectedScores.push_back(suLabels[feature]);</span></span>
<span id="L44"><span class="lineNum"> 44</span> <span class="tlaGNC"> 142 : if (selectedFeatures.size() == maxFeatures) {</span></span>
<span id="L45"><span class="lineNum"> 45</span> <span class="tlaUNC tlaBgUNC"> 0 : break;</span></span>
<span id="L46"><span class="lineNum"> 46</span> : }</span>
<span id="L47"><span class="lineNum"> 47</span> : }</span>
<span id="L48"><span class="lineNum"> 48</span> <span class="tlaGNC tlaBgGNC"> 56 : fitted = true;</span></span>
<span id="L49"><span class="lineNum"> 49</span> <span class="tlaGNC"> 56 : }</span></span>
<span id="L48"><span class="lineNum"> 48</span> <span class="tlaGNC tlaBgGNC"> 34 : fitted = true;</span></span>
<span id="L49"><span class="lineNum"> 49</span> <span class="tlaGNC"> 34 : }</span></span>
<span id="L50"><span class="lineNum"> 50</span> : }</span>
</pre>
</td>