Enhance tests coverage and report output
This commit is contained in:
@@ -37,7 +37,7 @@
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</tr>
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<tr>
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<td class="headerItem">Test Date:</td>
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<td class="headerValue">2024-04-29 20:48:03</td>
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<td class="headerValue">2024-04-30 13:59:18</td>
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<td></td>
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<td class="headerItem">Functions:</td>
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<td class="headerCovTableEntryHi">100.0 %</td>
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@@ -70,46 +70,46 @@
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<span id="L8"><span class="lineNum"> 8</span> : #include "bayesnet/utils/bayesnetUtils.h"</span>
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<span id="L9"><span class="lineNum"> 9</span> : #include "CFS.h"</span>
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<span id="L10"><span class="lineNum"> 10</span> : namespace bayesnet {</span>
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<span id="L11"><span class="lineNum"> 11</span> <span class="tlaGNC tlaBgGNC"> 70 : void CFS::fit()</span></span>
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<span id="L11"><span class="lineNum"> 11</span> <span class="tlaGNC tlaBgGNC"> 40 : void CFS::fit()</span></span>
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<span id="L12"><span class="lineNum"> 12</span> : {</span>
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<span id="L13"><span class="lineNum"> 13</span> <span class="tlaGNC"> 70 : initialize();</span></span>
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<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 70 : computeSuLabels();</span></span>
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<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 70 : auto featureOrder = argsort(suLabels); // sort descending order</span></span>
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<span id="L16"><span class="lineNum"> 16</span> <span class="tlaGNC"> 70 : auto continueCondition = true;</span></span>
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<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 70 : auto feature = featureOrder[0];</span></span>
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<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 70 : selectedFeatures.push_back(feature);</span></span>
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<span id="L19"><span class="lineNum"> 19</span> <span class="tlaGNC"> 70 : selectedScores.push_back(suLabels[feature]);</span></span>
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<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 70 : featureOrder.erase(featureOrder.begin());</span></span>
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<span id="L21"><span class="lineNum"> 21</span> <span class="tlaGNC"> 398 : while (continueCondition) {</span></span>
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<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 328 : double merit = std::numeric_limits<double>::lowest();</span></span>
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<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 328 : int bestFeature = -1;</span></span>
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<span id="L24"><span class="lineNum"> 24</span> <span class="tlaGNC"> 1929 : for (auto feature : featureOrder) {</span></span>
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<span id="L25"><span class="lineNum"> 25</span> <span class="tlaGNC"> 1601 : selectedFeatures.push_back(feature);</span></span>
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<span id="L13"><span class="lineNum"> 13</span> <span class="tlaGNC"> 40 : initialize();</span></span>
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<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 40 : computeSuLabels();</span></span>
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<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 40 : auto featureOrder = argsort(suLabels); // sort descending order</span></span>
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<span id="L16"><span class="lineNum"> 16</span> <span class="tlaGNC"> 40 : auto continueCondition = true;</span></span>
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<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 40 : auto feature = featureOrder[0];</span></span>
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<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 40 : selectedFeatures.push_back(feature);</span></span>
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<span id="L19"><span class="lineNum"> 19</span> <span class="tlaGNC"> 40 : selectedScores.push_back(suLabels[feature]);</span></span>
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<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 40 : featureOrder.erase(featureOrder.begin());</span></span>
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<span id="L21"><span class="lineNum"> 21</span> <span class="tlaGNC"> 226 : while (continueCondition) {</span></span>
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<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 186 : double merit = std::numeric_limits<double>::lowest();</span></span>
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<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 186 : int bestFeature = -1;</span></span>
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<span id="L24"><span class="lineNum"> 24</span> <span class="tlaGNC"> 1083 : for (auto feature : featureOrder) {</span></span>
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<span id="L25"><span class="lineNum"> 25</span> <span class="tlaGNC"> 897 : selectedFeatures.push_back(feature);</span></span>
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<span id="L26"><span class="lineNum"> 26</span> : // Compute merit with selectedFeatures</span>
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<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 1601 : auto meritNew = computeMeritCFS();</span></span>
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<span id="L28"><span class="lineNum"> 28</span> <span class="tlaGNC"> 1601 : if (meritNew > merit) {</span></span>
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<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 663 : merit = meritNew;</span></span>
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<span id="L30"><span class="lineNum"> 30</span> <span class="tlaGNC"> 663 : bestFeature = feature;</span></span>
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<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 897 : auto meritNew = computeMeritCFS();</span></span>
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<span id="L28"><span class="lineNum"> 28</span> <span class="tlaGNC"> 897 : if (meritNew > merit) {</span></span>
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<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 379 : merit = meritNew;</span></span>
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<span id="L30"><span class="lineNum"> 30</span> <span class="tlaGNC"> 379 : bestFeature = feature;</span></span>
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<span id="L31"><span class="lineNum"> 31</span> : }</span>
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<span id="L32"><span class="lineNum"> 32</span> <span class="tlaGNC"> 1601 : selectedFeatures.pop_back();</span></span>
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<span id="L32"><span class="lineNum"> 32</span> <span class="tlaGNC"> 897 : selectedFeatures.pop_back();</span></span>
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<span id="L33"><span class="lineNum"> 33</span> : }</span>
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<span id="L34"><span class="lineNum"> 34</span> <span class="tlaGNC"> 328 : if (bestFeature == -1) {</span></span>
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<span id="L34"><span class="lineNum"> 34</span> <span class="tlaGNC"> 186 : if (bestFeature == -1) {</span></span>
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<span id="L35"><span class="lineNum"> 35</span> : // meritNew has to be nan due to constant features</span>
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<span id="L36"><span class="lineNum"> 36</span> <span class="tlaUNC tlaBgUNC"> 0 : break;</span></span>
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<span id="L37"><span class="lineNum"> 37</span> : }</span>
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<span id="L38"><span class="lineNum"> 38</span> <span class="tlaGNC tlaBgGNC"> 328 : selectedFeatures.push_back(bestFeature);</span></span>
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<span id="L39"><span class="lineNum"> 39</span> <span class="tlaGNC"> 328 : selectedScores.push_back(merit);</span></span>
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<span id="L40"><span class="lineNum"> 40</span> <span class="tlaGNC"> 328 : featureOrder.erase(remove(featureOrder.begin(), featureOrder.end(), bestFeature), featureOrder.end());</span></span>
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<span id="L41"><span class="lineNum"> 41</span> <span class="tlaGNC"> 328 : continueCondition = computeContinueCondition(featureOrder);</span></span>
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<span id="L38"><span class="lineNum"> 38</span> <span class="tlaGNC tlaBgGNC"> 186 : selectedFeatures.push_back(bestFeature);</span></span>
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<span id="L39"><span class="lineNum"> 39</span> <span class="tlaGNC"> 186 : selectedScores.push_back(merit);</span></span>
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<span id="L40"><span class="lineNum"> 40</span> <span class="tlaGNC"> 186 : featureOrder.erase(remove(featureOrder.begin(), featureOrder.end(), bestFeature), featureOrder.end());</span></span>
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<span id="L41"><span class="lineNum"> 41</span> <span class="tlaGNC"> 186 : continueCondition = computeContinueCondition(featureOrder);</span></span>
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<span id="L42"><span class="lineNum"> 42</span> : }</span>
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<span id="L43"><span class="lineNum"> 43</span> <span class="tlaGNC"> 70 : fitted = true;</span></span>
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<span id="L44"><span class="lineNum"> 44</span> <span class="tlaGNC"> 70 : }</span></span>
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<span id="L45"><span class="lineNum"> 45</span> <span class="tlaGNC"> 328 : bool CFS::computeContinueCondition(const std::vector<int>& featureOrder)</span></span>
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<span id="L43"><span class="lineNum"> 43</span> <span class="tlaGNC"> 40 : fitted = true;</span></span>
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<span id="L44"><span class="lineNum"> 44</span> <span class="tlaGNC"> 40 : }</span></span>
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<span id="L45"><span class="lineNum"> 45</span> <span class="tlaGNC"> 186 : bool CFS::computeContinueCondition(const std::vector<int>& featureOrder)</span></span>
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<span id="L46"><span class="lineNum"> 46</span> : {</span>
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<span id="L47"><span class="lineNum"> 47</span> <span class="tlaGNC"> 328 : if (selectedFeatures.size() == maxFeatures || featureOrder.size() == 0) {</span></span>
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<span id="L48"><span class="lineNum"> 48</span> <span class="tlaGNC"> 11 : return false;</span></span>
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<span id="L47"><span class="lineNum"> 47</span> <span class="tlaGNC"> 186 : if (selectedFeatures.size() == maxFeatures || featureOrder.size() == 0) {</span></span>
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<span id="L48"><span class="lineNum"> 48</span> <span class="tlaGNC"> 7 : return false;</span></span>
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<span id="L49"><span class="lineNum"> 49</span> : }</span>
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<span id="L50"><span class="lineNum"> 50</span> <span class="tlaGNC"> 317 : if (selectedScores.size() >= 5) {</span></span>
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<span id="L50"><span class="lineNum"> 50</span> <span class="tlaGNC"> 179 : if (selectedScores.size() >= 5) {</span></span>
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<span id="L51"><span class="lineNum"> 51</span> : /*</span>
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<span id="L52"><span class="lineNum"> 52</span> : "To prevent the best first search from exploring the entire</span>
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<span id="L53"><span class="lineNum"> 53</span> : feature subset search space, a stopping criterion is imposed.</span>
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@@ -117,25 +117,25 @@
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<span id="L55"><span class="lineNum"> 55</span> : subsets show no improvement over the current best subset."</span>
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<span id="L56"><span class="lineNum"> 56</span> : as stated in Mark A.Hall Thesis</span>
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<span id="L57"><span class="lineNum"> 57</span> : */</span>
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<span id="L58"><span class="lineNum"> 58</span> <span class="tlaGNC"> 118 : double item_ant = std::numeric_limits<double>::lowest();</span></span>
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<span id="L59"><span class="lineNum"> 59</span> <span class="tlaGNC"> 118 : int num = 0;</span></span>
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<span id="L60"><span class="lineNum"> 60</span> <span class="tlaGNC"> 118 : std::vector<double> lastFive(selectedScores.end() - 5, selectedScores.end());</span></span>
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<span id="L61"><span class="lineNum"> 61</span> <span class="tlaGNC"> 472 : for (auto item : lastFive) {</span></span>
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<span id="L62"><span class="lineNum"> 62</span> <span class="tlaGNC"> 413 : if (item_ant == std::numeric_limits<double>::lowest()) {</span></span>
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<span id="L63"><span class="lineNum"> 63</span> <span class="tlaGNC"> 118 : item_ant = item;</span></span>
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<span id="L58"><span class="lineNum"> 58</span> <span class="tlaGNC"> 66 : double item_ant = std::numeric_limits<double>::lowest();</span></span>
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<span id="L59"><span class="lineNum"> 59</span> <span class="tlaGNC"> 66 : int num = 0;</span></span>
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<span id="L60"><span class="lineNum"> 60</span> <span class="tlaGNC"> 66 : std::vector<double> lastFive(selectedScores.end() - 5, selectedScores.end());</span></span>
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<span id="L61"><span class="lineNum"> 61</span> <span class="tlaGNC"> 264 : for (auto item : lastFive) {</span></span>
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<span id="L62"><span class="lineNum"> 62</span> <span class="tlaGNC"> 231 : if (item_ant == std::numeric_limits<double>::lowest()) {</span></span>
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<span id="L63"><span class="lineNum"> 63</span> <span class="tlaGNC"> 66 : item_ant = item;</span></span>
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<span id="L64"><span class="lineNum"> 64</span> : }</span>
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<span id="L65"><span class="lineNum"> 65</span> <span class="tlaGNC"> 413 : if (item > item_ant) {</span></span>
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<span id="L66"><span class="lineNum"> 66</span> <span class="tlaGNC"> 59 : break;</span></span>
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<span id="L65"><span class="lineNum"> 65</span> <span class="tlaGNC"> 231 : if (item > item_ant) {</span></span>
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<span id="L66"><span class="lineNum"> 66</span> <span class="tlaGNC"> 33 : break;</span></span>
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<span id="L67"><span class="lineNum"> 67</span> : } else {</span>
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<span id="L68"><span class="lineNum"> 68</span> <span class="tlaGNC"> 354 : num++;</span></span>
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<span id="L69"><span class="lineNum"> 69</span> <span class="tlaGNC"> 354 : item_ant = item;</span></span>
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<span id="L68"><span class="lineNum"> 68</span> <span class="tlaGNC"> 198 : num++;</span></span>
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<span id="L69"><span class="lineNum"> 69</span> <span class="tlaGNC"> 198 : item_ant = item;</span></span>
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<span id="L70"><span class="lineNum"> 70</span> : }</span>
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<span id="L71"><span class="lineNum"> 71</span> : }</span>
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<span id="L72"><span class="lineNum"> 72</span> <span class="tlaGNC"> 118 : if (num == 5) {</span></span>
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<span id="L73"><span class="lineNum"> 73</span> <span class="tlaGNC"> 59 : return false;</span></span>
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<span id="L72"><span class="lineNum"> 72</span> <span class="tlaGNC"> 66 : if (num == 5) {</span></span>
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<span id="L73"><span class="lineNum"> 73</span> <span class="tlaGNC"> 33 : return false;</span></span>
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<span id="L74"><span class="lineNum"> 74</span> : }</span>
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<span id="L75"><span class="lineNum"> 75</span> <span class="tlaGNC"> 118 : }</span></span>
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<span id="L76"><span class="lineNum"> 76</span> <span class="tlaGNC"> 258 : return true;</span></span>
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<span id="L75"><span class="lineNum"> 75</span> <span class="tlaGNC"> 66 : }</span></span>
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<span id="L76"><span class="lineNum"> 76</span> <span class="tlaGNC"> 146 : return true;</span></span>
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<span id="L77"><span class="lineNum"> 77</span> : }</span>
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<span id="L78"><span class="lineNum"> 78</span> : }</span>
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</pre>
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