225 lines
22 KiB
HTML
225 lines
22 KiB
HTML
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<title>LCOV - BayesNet Coverage Report - bayesnet/network/Node.cc</title>
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<tr><td class="title">LCOV - code coverage report</td></tr>
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<td width="10%" class="headerItem">Current view:</td>
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<td width="10%" class="headerValue"><a href="../../index.html" target="_parent">top level</a> - <a href="index.html" target="_parent">bayesnet/network</a> - Node.cc<span style="font-size: 80%;"> (source / <a href="Node.cc.func-c.html">functions</a>)</span></td>
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<td width="5%"></td>
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<td width="5%"></td>
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<td width="5%" class="headerCovTableHead">Coverage</td>
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<td width="5%" class="headerCovTableHead" title="Covered + Uncovered code">Total</td>
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<td width="5%" class="headerCovTableHead" title="Exercised code only">Hit</td>
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</tr>
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<tr>
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<td class="headerItem">Test:</td>
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<td class="headerValue">BayesNet Coverage Report</td>
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<td></td>
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<td class="headerItem">Lines:</td>
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<td class="headerCovTableEntryHi">100.0 %</td>
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<td class="headerCovTableEntry">88</td>
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<td class="headerCovTableEntry">88</td>
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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">2024-05-06 17:54:04</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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<td class="headerCovTableEntry">20</td>
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<td class="headerCovTableEntry">20</td>
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</tr>
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<tr>
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<td class="headerItem">Legend:</td>
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<td class="headerValueLeg"> Lines:
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<span class="coverLegendCov">hit</span>
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<span class="coverLegendNoCov">not hit</span>
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</td>
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<td></td>
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</tr>
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<tr><td><img src="../../glass.png" width=3 height=3 alt=""></td></tr>
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<td><br></td>
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<pre class="sourceHeading"> Line data Source code</pre>
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<pre class="source">
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<span id="L1"><span class="lineNum"> 1</span> : // ***************************************************************</span>
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<span id="L2"><span class="lineNum"> 2</span> : // SPDX-FileCopyrightText: Copyright 2024 Ricardo Montañana Gómez</span>
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<span id="L3"><span class="lineNum"> 3</span> : // SPDX-FileType: SOURCE</span>
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<span id="L4"><span class="lineNum"> 4</span> : // SPDX-License-Identifier: MIT</span>
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<span id="L5"><span class="lineNum"> 5</span> : // ***************************************************************</span>
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<span id="L6"><span class="lineNum"> 6</span> : </span>
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<span id="L7"><span class="lineNum"> 7</span> : #include "Node.h"</span>
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<span id="L8"><span class="lineNum"> 8</span> : </span>
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<span id="L9"><span class="lineNum"> 9</span> : namespace bayesnet {</span>
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<span id="L10"><span class="lineNum"> 10</span> : </span>
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<span id="L11"><span class="lineNum"> 11</span> <span class="tlaGNC tlaBgGNC"> 31339 : Node::Node(const std::string& name)</span></span>
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<span id="L12"><span class="lineNum"> 12</span> <span class="tlaGNC"> 31339 : : name(name)</span></span>
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<span id="L13"><span class="lineNum"> 13</span> : {</span>
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<span id="L14"><span class="lineNum"> 14</span> <span class="tlaGNC"> 31339 : }</span></span>
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<span id="L15"><span class="lineNum"> 15</span> <span class="tlaGNC"> 9 : void Node::clear()</span></span>
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<span id="L16"><span class="lineNum"> 16</span> : {</span>
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<span id="L17"><span class="lineNum"> 17</span> <span class="tlaGNC"> 9 : parents.clear();</span></span>
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<span id="L18"><span class="lineNum"> 18</span> <span class="tlaGNC"> 9 : children.clear();</span></span>
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<span id="L19"><span class="lineNum"> 19</span> <span class="tlaGNC"> 9 : cpTable = torch::Tensor();</span></span>
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<span id="L20"><span class="lineNum"> 20</span> <span class="tlaGNC"> 9 : dimensions.clear();</span></span>
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<span id="L21"><span class="lineNum"> 21</span> <span class="tlaGNC"> 9 : numStates = 0;</span></span>
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<span id="L22"><span class="lineNum"> 22</span> <span class="tlaGNC"> 9 : }</span></span>
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<span id="L23"><span class="lineNum"> 23</span> <span class="tlaGNC"> 150429643 : std::string Node::getName() const</span></span>
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<span id="L24"><span class="lineNum"> 24</span> : {</span>
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<span id="L25"><span class="lineNum"> 25</span> <span class="tlaGNC"> 150429643 : return name;</span></span>
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<span id="L26"><span class="lineNum"> 26</span> : }</span>
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<span id="L27"><span class="lineNum"> 27</span> <span class="tlaGNC"> 59262 : void Node::addParent(Node* parent)</span></span>
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<span id="L28"><span class="lineNum"> 28</span> : {</span>
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<span id="L29"><span class="lineNum"> 29</span> <span class="tlaGNC"> 59262 : parents.push_back(parent);</span></span>
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<span id="L30"><span class="lineNum"> 30</span> <span class="tlaGNC"> 59262 : }</span></span>
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<span id="L31"><span class="lineNum"> 31</span> <span class="tlaGNC"> 17 : void Node::removeParent(Node* parent)</span></span>
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<span id="L32"><span class="lineNum"> 32</span> : {</span>
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<span id="L33"><span class="lineNum"> 33</span> <span class="tlaGNC"> 17 : parents.erase(std::remove(parents.begin(), parents.end(), parent), parents.end());</span></span>
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<span id="L34"><span class="lineNum"> 34</span> <span class="tlaGNC"> 17 : }</span></span>
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<span id="L35"><span class="lineNum"> 35</span> <span class="tlaGNC"> 17 : void Node::removeChild(Node* child)</span></span>
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<span id="L36"><span class="lineNum"> 36</span> : {</span>
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<span id="L37"><span class="lineNum"> 37</span> <span class="tlaGNC"> 17 : children.erase(std::remove(children.begin(), children.end(), child), children.end());</span></span>
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<span id="L38"><span class="lineNum"> 38</span> <span class="tlaGNC"> 17 : }</span></span>
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<span id="L39"><span class="lineNum"> 39</span> <span class="tlaGNC"> 59235 : void Node::addChild(Node* child)</span></span>
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<span id="L40"><span class="lineNum"> 40</span> : {</span>
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<span id="L41"><span class="lineNum"> 41</span> <span class="tlaGNC"> 59235 : children.push_back(child);</span></span>
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<span id="L42"><span class="lineNum"> 42</span> <span class="tlaGNC"> 59235 : }</span></span>
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<span id="L43"><span class="lineNum"> 43</span> <span class="tlaGNC"> 5087 : std::vector<Node*>& Node::getParents()</span></span>
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<span id="L44"><span class="lineNum"> 44</span> : {</span>
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<span id="L45"><span class="lineNum"> 45</span> <span class="tlaGNC"> 5087 : return parents;</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"> 77571 : std::vector<Node*>& Node::getChildren()</span></span>
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<span id="L48"><span class="lineNum"> 48</span> : {</span>
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<span id="L49"><span class="lineNum"> 49</span> <span class="tlaGNC"> 77571 : return children;</span></span>
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<span id="L50"><span class="lineNum"> 50</span> : }</span>
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<span id="L51"><span class="lineNum"> 51</span> <span class="tlaGNC"> 64124 : int Node::getNumStates() const</span></span>
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<span id="L52"><span class="lineNum"> 52</span> : {</span>
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<span id="L53"><span class="lineNum"> 53</span> <span class="tlaGNC"> 64124 : return numStates;</span></span>
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<span id="L54"><span class="lineNum"> 54</span> : }</span>
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<span id="L55"><span class="lineNum"> 55</span> <span class="tlaGNC"> 32864 : void Node::setNumStates(int numStates)</span></span>
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<span id="L56"><span class="lineNum"> 56</span> : {</span>
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<span id="L57"><span class="lineNum"> 57</span> <span class="tlaGNC"> 32864 : this->numStates = numStates;</span></span>
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<span id="L58"><span class="lineNum"> 58</span> <span class="tlaGNC"> 32864 : }</span></span>
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<span id="L59"><span class="lineNum"> 59</span> <span class="tlaGNC"> 429 : torch::Tensor& Node::getCPT()</span></span>
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<span id="L60"><span class="lineNum"> 60</span> : {</span>
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<span id="L61"><span class="lineNum"> 61</span> <span class="tlaGNC"> 429 : return cpTable;</span></span>
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<span id="L62"><span class="lineNum"> 62</span> : }</span>
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<span id="L63"><span class="lineNum"> 63</span> : /*</span>
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<span id="L64"><span class="lineNum"> 64</span> : The MinFill criterion is a heuristic for variable elimination.</span>
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<span id="L65"><span class="lineNum"> 65</span> : The variable that minimizes the number of edges that need to be added to the graph to make it triangulated.</span>
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<span id="L66"><span class="lineNum"> 66</span> : This is done by counting the number of edges that need to be added to the graph if the variable is eliminated.</span>
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<span id="L67"><span class="lineNum"> 67</span> : The variable with the minimum number of edges is chosen.</span>
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<span id="L68"><span class="lineNum"> 68</span> : Here this is done computing the length of the combinations of the node neighbors taken 2 by 2.</span>
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<span id="L69"><span class="lineNum"> 69</span> : */</span>
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<span id="L70"><span class="lineNum"> 70</span> <span class="tlaGNC"> 45 : unsigned Node::minFill()</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"> 45 : std::unordered_set<std::string> neighbors;</span></span>
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<span id="L73"><span class="lineNum"> 73</span> <span class="tlaGNC"> 117 : for (auto child : children) {</span></span>
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<span id="L74"><span class="lineNum"> 74</span> <span class="tlaGNC"> 72 : neighbors.emplace(child->getName());</span></span>
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<span id="L75"><span class="lineNum"> 75</span> : }</span>
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<span id="L76"><span class="lineNum"> 76</span> <span class="tlaGNC"> 108 : for (auto parent : parents) {</span></span>
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<span id="L77"><span class="lineNum"> 77</span> <span class="tlaGNC"> 63 : neighbors.emplace(parent->getName());</span></span>
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<span id="L78"><span class="lineNum"> 78</span> : }</span>
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<span id="L79"><span class="lineNum"> 79</span> <span class="tlaGNC"> 45 : auto source = std::vector<std::string>(neighbors.begin(), neighbors.end());</span></span>
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<span id="L80"><span class="lineNum"> 80</span> <span class="tlaGNC"> 90 : return combinations(source).size();</span></span>
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<span id="L81"><span class="lineNum"> 81</span> <span class="tlaGNC"> 45 : }</span></span>
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<span id="L82"><span class="lineNum"> 82</span> <span class="tlaGNC"> 45 : std::vector<std::pair<std::string, std::string>> Node::combinations(const std::vector<std::string>& source)</span></span>
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<span id="L83"><span class="lineNum"> 83</span> : {</span>
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<span id="L84"><span class="lineNum"> 84</span> <span class="tlaGNC"> 45 : std::vector<std::pair<std::string, std::string>> result;</span></span>
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<span id="L85"><span class="lineNum"> 85</span> <span class="tlaGNC"> 180 : for (int i = 0; i < source.size(); ++i) {</span></span>
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<span id="L86"><span class="lineNum"> 86</span> <span class="tlaGNC"> 135 : std::string temp = source[i];</span></span>
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<span id="L87"><span class="lineNum"> 87</span> <span class="tlaGNC"> 279 : for (int j = i + 1; j < source.size(); ++j) {</span></span>
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<span id="L88"><span class="lineNum"> 88</span> <span class="tlaGNC"> 144 : result.push_back({ temp, source[j] });</span></span>
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<span id="L89"><span class="lineNum"> 89</span> : }</span>
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<span id="L90"><span class="lineNum"> 90</span> <span class="tlaGNC"> 135 : }</span></span>
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<span id="L91"><span class="lineNum"> 91</span> <span class="tlaGNC"> 90 : return result;</span></span>
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<span id="L92"><span class="lineNum"> 92</span> <span class="tlaGNC"> 45 : }</span></span>
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<span id="L93"><span class="lineNum"> 93</span> <span class="tlaGNC"> 32894 : void Node::computeCPT(const torch::Tensor& dataset, const std::vector<std::string>& features, const double laplaceSmoothing, const torch::Tensor& weights)</span></span>
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<span id="L94"><span class="lineNum"> 94</span> : {</span>
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<span id="L95"><span class="lineNum"> 95</span> <span class="tlaGNC"> 32894 : dimensions.clear();</span></span>
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<span id="L96"><span class="lineNum"> 96</span> : // Get dimensions of the CPT</span>
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<span id="L97"><span class="lineNum"> 97</span> <span class="tlaGNC"> 32894 : dimensions.push_back(numStates);</span></span>
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<span id="L98"><span class="lineNum"> 98</span> <span class="tlaGNC"> 94914 : transform(parents.begin(), parents.end(), back_inserter(dimensions), [](const auto& parent) { return parent->getNumStates(); });</span></span>
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<span id="L99"><span class="lineNum"> 99</span> : // Create a tensor of zeros with the dimensions of the CPT</span>
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<span id="L100"><span class="lineNum"> 100</span> <span class="tlaGNC"> 32894 : cpTable = torch::zeros(dimensions, torch::kFloat) + laplaceSmoothing;</span></span>
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<span id="L101"><span class="lineNum"> 101</span> : // Fill table with counts</span>
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<span id="L102"><span class="lineNum"> 102</span> <span class="tlaGNC"> 32894 : auto pos = find(features.begin(), features.end(), name);</span></span>
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<span id="L103"><span class="lineNum"> 103</span> <span class="tlaGNC"> 32894 : if (pos == features.end()) {</span></span>
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<span id="L104"><span class="lineNum"> 104</span> <span class="tlaGNC"> 8 : throw std::logic_error("Feature " + name + " not found in dataset");</span></span>
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<span id="L105"><span class="lineNum"> 105</span> : }</span>
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<span id="L106"><span class="lineNum"> 106</span> <span class="tlaGNC"> 32886 : int name_index = pos - features.begin();</span></span>
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<span id="L107"><span class="lineNum"> 107</span> <span class="tlaGNC"> 11221522 : for (int n_sample = 0; n_sample < dataset.size(1); ++n_sample) {</span></span>
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<span id="L108"><span class="lineNum"> 108</span> <span class="tlaGNC"> 11188649 : c10::List<c10::optional<at::Tensor>> coordinates;</span></span>
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<span id="L109"><span class="lineNum"> 109</span> <span class="tlaGNC"> 33565947 : coordinates.push_back(dataset.index({ name_index, n_sample }));</span></span>
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<span id="L110"><span class="lineNum"> 110</span> <span class="tlaGNC"> 32200749 : for (auto parent : parents) {</span></span>
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<span id="L111"><span class="lineNum"> 111</span> <span class="tlaGNC"> 21012113 : pos = find(features.begin(), features.end(), parent->getName());</span></span>
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<span id="L112"><span class="lineNum"> 112</span> <span class="tlaGNC"> 21012113 : if (pos == features.end()) {</span></span>
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<span id="L113"><span class="lineNum"> 113</span> <span class="tlaGNC"> 13 : throw std::logic_error("Feature parent " + parent->getName() + " not found in dataset");</span></span>
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<span id="L114"><span class="lineNum"> 114</span> : }</span>
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<span id="L115"><span class="lineNum"> 115</span> <span class="tlaGNC"> 21012100 : int parent_index = pos - features.begin();</span></span>
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<span id="L116"><span class="lineNum"> 116</span> <span class="tlaGNC"> 63036300 : coordinates.push_back(dataset.index({ parent_index, n_sample }));</span></span>
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<span id="L117"><span class="lineNum"> 117</span> : }</span>
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<span id="L118"><span class="lineNum"> 118</span> : // Increment the count of the corresponding coordinate</span>
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<span id="L119"><span class="lineNum"> 119</span> <span class="tlaGNC"> 22377272 : cpTable.index_put_({ coordinates }, cpTable.index({ coordinates }) + weights.index({ n_sample }).item<double>());</span></span>
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<span id="L120"><span class="lineNum"> 120</span> <span class="tlaGNC"> 11188649 : }</span></span>
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<span id="L121"><span class="lineNum"> 121</span> : // Normalize the counts</span>
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<span id="L122"><span class="lineNum"> 122</span> <span class="tlaGNC"> 32873 : cpTable = cpTable / cpTable.sum(0);</span></span>
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<span id="L123"><span class="lineNum"> 123</span> <span class="tlaGNC"> 43422258 : }</span></span>
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<span id="L124"><span class="lineNum"> 124</span> <span class="tlaGNC"> 69151761 : float Node::getFactorValue(std::map<std::string, int>& evidence)</span></span>
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<span id="L125"><span class="lineNum"> 125</span> : {</span>
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<span id="L126"><span class="lineNum"> 126</span> <span class="tlaGNC"> 69151761 : c10::List<c10::optional<at::Tensor>> coordinates;</span></span>
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<span id="L127"><span class="lineNum"> 127</span> : // following predetermined order of indices in the cpTable (see Node.h)</span>
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<span id="L128"><span class="lineNum"> 128</span> <span class="tlaGNC"> 69151761 : coordinates.push_back(at::tensor(evidence[name]));</span></span>
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<span id="L129"><span class="lineNum"> 129</span> <span class="tlaGNC"> 198453273 : transform(parents.begin(), parents.end(), std::back_inserter(coordinates), [&evidence](const auto& parent) { return at::tensor(evidence[parent->getName()]); });</span></span>
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<span id="L130"><span class="lineNum"> 130</span> <span class="tlaGNC"> 138303522 : return cpTable.index({ coordinates }).item<float>();</span></span>
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<span id="L131"><span class="lineNum"> 131</span> <span class="tlaGNC"> 69151761 : }</span></span>
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<span id="L132"><span class="lineNum"> 132</span> <span class="tlaGNC"> 732 : std::vector<std::string> Node::graph(const std::string& className)</span></span>
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<span id="L133"><span class="lineNum"> 133</span> : {</span>
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<span id="L134"><span class="lineNum"> 134</span> <span class="tlaGNC"> 732 : auto output = std::vector<std::string>();</span></span>
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<span id="L135"><span class="lineNum"> 135</span> <span class="tlaGNC"> 732 : auto suffix = name == className ? ", fontcolor=red, fillcolor=lightblue, style=filled " : "";</span></span>
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<span id="L136"><span class="lineNum"> 136</span> <span class="tlaGNC"> 732 : output.push_back(name + " [shape=circle" + suffix + "] \n");</span></span>
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<span id="L137"><span class="lineNum"> 137</span> <span class="tlaGNC"> 1840 : transform(children.begin(), children.end(), back_inserter(output), [this](const auto& child) { return name + " -> " + child->getName(); });</span></span>
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<span id="L138"><span class="lineNum"> 138</span> <span class="tlaGNC"> 1464 : return output;</span></span>
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<span id="L139"><span class="lineNum"> 139</span> <span class="tlaGNC"> 732 : }</span></span>
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<span id="L140"><span class="lineNum"> 140</span> : }</span>
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</pre>
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</td>
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</table>
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<br>
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<table width="100%" border=0 cellspacing=0 cellpadding=0>
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<tr><td class="ruler"><img src="../../glass.png" width=3 height=3 alt=""></td></tr>
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<tr><td class="versionInfo">Generated by: <a href="https://github.com//linux-test-project/lcov" target="_parent">LCOV version 2.0-1</a></td></tr>
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