mirror of
https://github.com/TheAlgorithms/C-Plus-Plus.git
synced 2026-03-22 21:01:50 +08:00
648 lines
94 KiB
HTML
648 lines
94 KiB
HTML
<!-- HTML header for doxygen 1.12.0-->
|
|
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "https://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
|
<html xmlns="http://www.w3.org/1999/xhtml" lang="en-US">
|
|
<head>
|
|
<meta http-equiv="Content-Type" content="text/xhtml;charset=UTF-8"/>
|
|
<meta http-equiv="X-UA-Compatible" content="IE=11"/>
|
|
<meta name="generator" content="Doxygen 1.14.0"/>
|
|
<meta name="viewport" content="width=device-width, initial-scale=1"/>
|
|
<title>TheAlgorithms/C++: machine_learning/kohonen_som_topology.cpp Source File</title>
|
|
<link rel="icon" href="../../favicon.svg" type="image/x-icon" />
|
|
<link href="../../tabs.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="../../jquery.js"></script>
|
|
<script type="text/javascript" src="../../dynsections.js"></script>
|
|
<script type="text/javascript" src="https://cdn.jsdelivr.net/npm/@xpack-3rd-party/doxygen-awesome-css@2.2.0-1/doxygen-awesome-darkmode-toggle.js"></script>
|
|
<script type="text/javascript">
|
|
DoxygenAwesomeDarkModeToggle.init()
|
|
</script>
|
|
<script type="text/javascript" src="../../clipboard.js"></script>
|
|
<link href="../../navtree.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="../../navtreedata.js"></script>
|
|
<script type="text/javascript" src="../../navtree.js"></script>
|
|
<script type="text/javascript" src="../../cookie.js"></script>
|
|
<link href="../../search/search.css" rel="stylesheet" type="text/css"/>
|
|
<script type="text/javascript" src="../../search/searchdata.js"></script>
|
|
<script type="text/javascript" src="../../search/search.js"></script>
|
|
<script type="text/javascript">
|
|
window.MathJax = {
|
|
options: {
|
|
ignoreHtmlClass: 'tex2jax_ignore',
|
|
processHtmlClass: 'tex2jax_process'
|
|
},
|
|
loader: {
|
|
load: ['[tex]/ams']
|
|
},
|
|
tex: {
|
|
macros: {},
|
|
packages: ['base','configmacros','ams']
|
|
}
|
|
};
|
|
</script>
|
|
<script type="text/javascript" id="MathJax-script" async="async" src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml.js"></script>
|
|
<link href="../../doxygen.css" rel="stylesheet" type="text/css" />
|
|
<link href="../../doxygen-awesome.css" rel="stylesheet" type="text/css"/>
|
|
</head>
|
|
<body>
|
|
<div id="top"><!-- do not remove this div, it is closed by doxygen! -->
|
|
<div id="titlearea">
|
|
<table cellspacing="0" cellpadding="0">
|
|
<tbody>
|
|
<tr id="projectrow">
|
|
<td id="projectlogo"><img alt="Logo" src="../../project_logo.png"/></td>
|
|
<td id="projectalign">
|
|
<div id="projectname">TheAlgorithms/C++<span id="projectnumber"> 1.0.0</span>
|
|
</div>
|
|
<div id="projectbrief">All the algorithms implemented in C++</div>
|
|
</td>
|
|
</tr>
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
<!-- end header part -->
|
|
<!-- Generated by Doxygen 1.14.0 -->
|
|
<script type="text/javascript">
|
|
var searchBox = new SearchBox("searchBox", "../../search/",'.html');
|
|
</script>
|
|
<script type="text/javascript">
|
|
$(function() { codefold.init(); });
|
|
</script>
|
|
<script type="text/javascript" src="../../menudata.js"></script>
|
|
<script type="text/javascript" src="../../menu.js"></script>
|
|
<script type="text/javascript">
|
|
$(function() {
|
|
initMenu('../../',true,false,'search.php','Search',true);
|
|
$(function() { init_search(); });
|
|
});
|
|
</script>
|
|
<div id="main-nav"></div>
|
|
</div><!-- top -->
|
|
<div id="side-nav" class="ui-resizable side-nav-resizable">
|
|
<div id="nav-tree">
|
|
<div id="nav-tree-contents">
|
|
<div id="nav-sync" class="sync"></div>
|
|
</div>
|
|
</div>
|
|
<div id="splitbar" style="-moz-user-select:none;"
|
|
class="ui-resizable-handle">
|
|
</div>
|
|
</div>
|
|
<script type="text/javascript">
|
|
$(function(){initNavTree('d4/def/kohonen__som__topology_8cpp_source.html','../../',''); });
|
|
</script>
|
|
<div id="container">
|
|
<div id="doc-content">
|
|
<!-- window showing the filter options -->
|
|
<div id="MSearchSelectWindow"
|
|
onmouseover="return searchBox.OnSearchSelectShow()"
|
|
onmouseout="return searchBox.OnSearchSelectHide()"
|
|
onkeydown="return searchBox.OnSearchSelectKey(event)">
|
|
</div>
|
|
|
|
<!-- iframe showing the search results (closed by default) -->
|
|
<div id="MSearchResultsWindow">
|
|
<div id="MSearchResults">
|
|
<div class="SRPage">
|
|
<div id="SRIndex">
|
|
<div id="SRResults"></div>
|
|
<div class="SRStatus" id="Loading">Loading...</div>
|
|
<div class="SRStatus" id="Searching">Searching...</div>
|
|
<div class="SRStatus" id="NoMatches">No Matches</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="header">
|
|
<div class="headertitle"><div class="title">kohonen_som_topology.cpp</div></div>
|
|
</div><!--header-->
|
|
<div class="contents">
|
|
<a href="../../d4/def/kohonen__som__topology_8cpp.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a id="l00001" name="l00001"></a><span class="lineno"> 1</span></div>
|
|
<div class="line"><a id="l00026" name="l00026"></a><span class="lineno"> 26</span><span class="preprocessor">#define _USE_MATH_DEFINES </span><span class="comment">//< required for MS Visual C++</span></div>
|
|
<div class="line"><a id="l00027" name="l00027"></a><span class="lineno"> 27</span><span class="preprocessor">#include <algorithm></span></div>
|
|
<div class="line"><a id="l00028" name="l00028"></a><span class="lineno"> 28</span><span class="preprocessor">#include <array></span></div>
|
|
<div class="line"><a id="l00029" name="l00029"></a><span class="lineno"> 29</span><span class="preprocessor">#include <cerrno></span></div>
|
|
<div class="line"><a id="l00030" name="l00030"></a><span class="lineno"> 30</span><span class="preprocessor">#include <cmath></span></div>
|
|
<div class="line"><a id="l00031" name="l00031"></a><span class="lineno"> 31</span><span class="preprocessor">#include <cstdlib></span></div>
|
|
<div class="line"><a id="l00032" name="l00032"></a><span class="lineno"> 32</span><span class="preprocessor">#include <cstring></span></div>
|
|
<div class="line"><a id="l00033" name="l00033"></a><span class="lineno"> 33</span><span class="preprocessor">#include <ctime></span></div>
|
|
<div class="line"><a id="l00034" name="l00034"></a><span class="lineno"> 34</span><span class="preprocessor">#include <fstream></span></div>
|
|
<div class="line"><a id="l00035" name="l00035"></a><span class="lineno"> 35</span><span class="preprocessor">#include <iostream></span></div>
|
|
<div class="line"><a id="l00036" name="l00036"></a><span class="lineno"> 36</span><span class="preprocessor">#include <valarray></span></div>
|
|
<div class="line"><a id="l00037" name="l00037"></a><span class="lineno"> 37</span><span class="preprocessor">#include <vector></span></div>
|
|
<div class="line"><a id="l00038" name="l00038"></a><span class="lineno"> 38</span><span class="preprocessor">#ifdef _OPENMP </span><span class="comment">// check if OpenMP based parallellization is available</span></div>
|
|
<div class="line"><a id="l00039" name="l00039"></a><span class="lineno"> 39</span><span class="preprocessor">#include <omp.h></span></div>
|
|
<div class="line"><a id="l00040" name="l00040"></a><span class="lineno"> 40</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00041" name="l00041"></a><span class="lineno"> 41</span></div>
|
|
<div class="foldopen" id="foldopen00053" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00053" name="l00053"></a><span class="lineno"><a class="line" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485"> 53</a></span><span class="keywordtype">double</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(<span class="keywordtype">double</span> a, <span class="keywordtype">double</span> b) {</div>
|
|
<div class="line"><a id="l00054" name="l00054"></a><span class="lineno"> 54</span> <span class="keywordflow">return</span> ((b - a) * (std::rand() % 100) / 100.f) + a;</div>
|
|
<div class="line"><a id="l00055" name="l00055"></a><span class="lineno"> 55</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00056" name="l00056"></a><span class="lineno"> 56</span></div>
|
|
<div class="foldopen" id="foldopen00065" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00065" name="l00065"></a><span class="lineno"><a class="line" href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c"> 65</a></span><span class="keywordtype">int</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c">save_2d_data</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> *fname,</div>
|
|
<div class="line"><a id="l00066" name="l00066"></a><span class="lineno"> 66</span> <span class="keyword">const</span> std::vector<std::valarray<double>> &X) {</div>
|
|
<div class="line"><a id="l00067" name="l00067"></a><span class="lineno"> 67</span> <span class="keywordtype">size_t</span> num_points = X.size(); <span class="comment">// number of rows</span></div>
|
|
<div class="line"><a id="l00068" name="l00068"></a><span class="lineno"> 68</span> <span class="keywordtype">size_t</span> num_features = X[0].size(); <span class="comment">// number of columns</span></div>
|
|
<div class="line"><a id="l00069" name="l00069"></a><span class="lineno"> 69</span> </div>
|
|
<div class="line"><a id="l00070" name="l00070"></a><span class="lineno"> 70</span> std::ofstream fp;</div>
|
|
<div class="line"><a id="l00071" name="l00071"></a><span class="lineno"> 71</span> fp.open(fname);</div>
|
|
<div class="line"><a id="l00072" name="l00072"></a><span class="lineno"> 72</span> <span class="keywordflow">if</span> (!fp.is_open()) {</div>
|
|
<div class="line"><a id="l00073" name="l00073"></a><span class="lineno"> 73</span> <span class="comment">// error with opening file to write</span></div>
|
|
<div class="line"><a id="l00074" name="l00074"></a><span class="lineno"> 74</span> std::cerr << <span class="stringliteral">"Error opening file "</span> << fname << <span class="stringliteral">": "</span></div>
|
|
<div class="line"><a id="l00075" name="l00075"></a><span class="lineno"> 75</span> << std::strerror(errno) << <span class="stringliteral">"\n"</span>;</div>
|
|
<div class="line"><a id="l00076" name="l00076"></a><span class="lineno"> 76</span> <span class="keywordflow">return</span> -1;</div>
|
|
<div class="line"><a id="l00077" name="l00077"></a><span class="lineno"> 77</span> }</div>
|
|
<div class="line"><a id="l00078" name="l00078"></a><span class="lineno"> 78</span> </div>
|
|
<div class="line"><a id="l00079" name="l00079"></a><span class="lineno"> 79</span> <span class="comment">// for each point in the array</span></div>
|
|
<div class="line"><a id="l00080" name="l00080"></a><span class="lineno"> 80</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < num_points; i++) {</div>
|
|
<div class="line"><a id="l00081" name="l00081"></a><span class="lineno"> 81</span> <span class="comment">// for each feature in the array</span></div>
|
|
<div class="line"><a id="l00082" name="l00082"></a><span class="lineno"> 82</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < num_features; j++) {</div>
|
|
<div class="line"><a id="l00083" name="l00083"></a><span class="lineno"> 83</span> fp << X[i][j]; <span class="comment">// print the feature value</span></div>
|
|
<div class="line"><a id="l00084" name="l00084"></a><span class="lineno"> 84</span> <span class="keywordflow">if</span> (j < num_features - 1) { <span class="comment">// if not the last feature</span></div>
|
|
<div class="line"><a id="l00085" name="l00085"></a><span class="lineno"> 85</span> fp << <span class="stringliteral">","</span>; <span class="comment">// suffix comma</span></div>
|
|
<div class="line"><a id="l00086" name="l00086"></a><span class="lineno"> 86</span> }</div>
|
|
<div class="line"><a id="l00087" name="l00087"></a><span class="lineno"> 87</span> }</div>
|
|
<div class="line"><a id="l00088" name="l00088"></a><span class="lineno"> 88</span> <span class="keywordflow">if</span> (i < num_points - 1) { <span class="comment">// if not the last row</span></div>
|
|
<div class="line"><a id="l00089" name="l00089"></a><span class="lineno"> 89</span> fp << <span class="stringliteral">"\n"</span>; <span class="comment">// start a new line</span></div>
|
|
<div class="line"><a id="l00090" name="l00090"></a><span class="lineno"> 90</span> }</div>
|
|
<div class="line"><a id="l00091" name="l00091"></a><span class="lineno"> 91</span> }</div>
|
|
<div class="line"><a id="l00092" name="l00092"></a><span class="lineno"> 92</span> </div>
|
|
<div class="line"><a id="l00093" name="l00093"></a><span class="lineno"> 93</span> fp.close();</div>
|
|
<div class="line"><a id="l00094" name="l00094"></a><span class="lineno"> 94</span> <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a id="l00095" name="l00095"></a><span class="lineno"> 95</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00096" name="l00096"></a><span class="lineno"> 96</span></div>
|
|
<div class="foldopen" id="foldopen00105" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00105" name="l00105"></a><span class="lineno"><a class="line" href="../../d9/d66/group__machine__learning.html#ga60f9186ccb682724a8792a2bf81e9b9e"> 105</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#ga60f9186ccb682724a8792a2bf81e9b9e">get_min_2d</a>(<span class="keyword">const</span> std::vector<std::valarray<double>> &X, <span class="keywordtype">double</span> *val,</div>
|
|
<div class="line"><a id="l00106" name="l00106"></a><span class="lineno"> 106</span> <span class="keywordtype">int</span> *x_idx, <span class="keywordtype">int</span> *y_idx) {</div>
|
|
<div class="line"><a id="l00107" name="l00107"></a><span class="lineno"> 107</span> val[0] = INFINITY; <span class="comment">// initial min value</span></div>
|
|
<div class="line"><a id="l00108" name="l00108"></a><span class="lineno"> 108</span> <span class="keywordtype">size_t</span> N = X.size();</div>
|
|
<div class="line"><a id="l00109" name="l00109"></a><span class="lineno"> 109</span> </div>
|
|
<div class="line"><a id="l00110" name="l00110"></a><span class="lineno"> 110</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < N; i++) { <span class="comment">// traverse each x-index</span></div>
|
|
<div class="line"><a id="l00111" name="l00111"></a><span class="lineno"> 111</span> <span class="keyword">auto</span> result = std::min_element(std::begin(X[i]), std::end(X[i]));</div>
|
|
<div class="line"><a id="l00112" name="l00112"></a><span class="lineno"> 112</span> <span class="keywordtype">double</span> d_min = *result;</div>
|
|
<div class="line"><a id="l00113" name="l00113"></a><span class="lineno"> 113</span> std::ptrdiff_t j = std::distance(std::begin(X[i]), result);</div>
|
|
<div class="line"><a id="l00114" name="l00114"></a><span class="lineno"> 114</span> </div>
|
|
<div class="line"><a id="l00115" name="l00115"></a><span class="lineno"> 115</span> <span class="keywordflow">if</span> (d_min < val[0]) { <span class="comment">// if a lower value is found</span></div>
|
|
<div class="line"><a id="l00116" name="l00116"></a><span class="lineno"> 116</span> <span class="comment">// save the value and its index</span></div>
|
|
<div class="line"><a id="l00117" name="l00117"></a><span class="lineno"> 117</span> x_idx[0] = i;</div>
|
|
<div class="line"><a id="l00118" name="l00118"></a><span class="lineno"> 118</span> y_idx[0] = j;</div>
|
|
<div class="line"><a id="l00119" name="l00119"></a><span class="lineno"> 119</span> val[0] = d_min;</div>
|
|
<div class="line"><a id="l00120" name="l00120"></a><span class="lineno"> 120</span> }</div>
|
|
<div class="line"><a id="l00121" name="l00121"></a><span class="lineno"> 121</span> }</div>
|
|
<div class="line"><a id="l00122" name="l00122"></a><span class="lineno"> 122</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00123" name="l00123"></a><span class="lineno"> 123</span></div>
|
|
<div class="line"><a id="l00127" name="l00127"></a><span class="lineno"> 127</span><span class="keyword">namespace </span><a class="code hl_namespace" href="../../d8/d77/namespacemachine__learning.html">machine_learning</a> {</div>
|
|
<div class="line"><a id="l00129" name="l00129"></a><span class="lineno"><a class="line" href="../../d8/d77/namespacemachine__learning.html#a7220dbb7fa896d83bfb7a50e4fce1786"> 129</a></span><span class="keyword">constexpr</span> <span class="keywordtype">double</span> <a class="code hl_variable" href="../../d8/d77/namespacemachine__learning.html#a7220dbb7fa896d83bfb7a50e4fce1786">MIN_DISTANCE</a> = 1e-4;</div>
|
|
<div class="line"><a id="l00130" name="l00130"></a><span class="lineno"> 130</span></div>
|
|
<div class="foldopen" id="foldopen00142" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00142" name="l00142"></a><span class="lineno"><a class="line" href="../../d8/d77/namespacemachine__learning.html#aa72a53c88203fde278f1fe6c3afe5b07"> 142</a></span><span class="keywordtype">int</span> <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="keyword">const</span> <span class="keywordtype">char</span> *fname,</div>
|
|
<div class="line"><a id="l00143" name="l00143"></a><span class="lineno"> 143</span> <span class="keyword">const</span> std::vector<std::vector<std::valarray<double>>> &W) {</div>
|
|
<div class="line"><a id="l00144" name="l00144"></a><span class="lineno"> 144</span> std::ofstream fp(fname);</div>
|
|
<div class="line"><a id="l00145" name="l00145"></a><span class="lineno"> 145</span> <span class="keywordflow">if</span> (!fp) { <span class="comment">// error with fopen</span></div>
|
|
<div class="line"><a id="l00146" name="l00146"></a><span class="lineno"> 146</span> std::cerr << <span class="stringliteral">"File error ("</span> << fname << <span class="stringliteral">"): "</span> << std::strerror(errno)</div>
|
|
<div class="line"><a id="l00147" name="l00147"></a><span class="lineno"> 147</span> << std::endl;</div>
|
|
<div class="line"><a id="l00148" name="l00148"></a><span class="lineno"> 148</span> <span class="keywordflow">return</span> -1;</div>
|
|
<div class="line"><a id="l00149" name="l00149"></a><span class="lineno"> 149</span> }</div>
|
|
<div class="line"><a id="l00150" name="l00150"></a><span class="lineno"> 150</span> </div>
|
|
<div class="line"><a id="l00151" name="l00151"></a><span class="lineno"> 151</span> <span class="comment">// neighborhood range</span></div>
|
|
<div class="line"><a id="l00152" name="l00152"></a><span class="lineno"> 152</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> R = 1;</div>
|
|
<div class="line"><a id="l00153" name="l00153"></a><span class="lineno"> 153</span> </div>
|
|
<div class="line"><a id="l00154" name="l00154"></a><span class="lineno"> 154</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < W.size(); i++) { <span class="comment">// for each x</span></div>
|
|
<div class="line"><a id="l00155" name="l00155"></a><span class="lineno"> 155</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> j = 0; j < W[0].size(); j++) { <span class="comment">// for each y</span></div>
|
|
<div class="line"><a id="l00156" name="l00156"></a><span class="lineno"> 156</span> <span class="keywordtype">double</span> distance = 0.f;</div>
|
|
<div class="line"><a id="l00157" name="l00157"></a><span class="lineno"> 157</span> </div>
|
|
<div class="line"><a id="l00158" name="l00158"></a><span class="lineno"> 158</span> <span class="keywordtype">int</span> from_x = std::max<int>(0, i - R);</div>
|
|
<div class="line"><a id="l00159" name="l00159"></a><span class="lineno"> 159</span> <span class="keywordtype">int</span> to_x = std::min<int>(W.size(), i + R + 1);</div>
|
|
<div class="line"><a id="l00160" name="l00160"></a><span class="lineno"> 160</span> <span class="keywordtype">int</span> from_y = std::max<int>(0, j - R);</div>
|
|
<div class="line"><a id="l00161" name="l00161"></a><span class="lineno"> 161</span> <span class="keywordtype">int</span> to_y = std::min<int>(W[0].size(), j + R + 1);</div>
|
|
<div class="line"><a id="l00162" name="l00162"></a><span class="lineno"> 162</span> <span class="keywordtype">int</span> l = 0, m = 0;</div>
|
|
<div class="line"><a id="l00163" name="l00163"></a><span class="lineno"> 163</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00164" name="l00164"></a><span class="lineno"> 164</span><span class="preprocessor">#pragma omp parallel for reduction(+ : distance)</span></div>
|
|
<div class="line"><a id="l00165" name="l00165"></a><span class="lineno"> 165</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00166" name="l00166"></a><span class="lineno"> 166</span> <span class="keywordflow">for</span> (l = from_x; l < to_x; l++) { <span class="comment">// scan neighborhoor in x</span></div>
|
|
<div class="line"><a id="l00167" name="l00167"></a><span class="lineno"> 167</span> <span class="keywordflow">for</span> (m = from_y; m < to_y; m++) { <span class="comment">// scan neighborhood in y</span></div>
|
|
<div class="line"><a id="l00168" name="l00168"></a><span class="lineno"> 168</span> <span class="keyword">auto</span> d = W[i][j] - W[l][m];</div>
|
|
<div class="line"><a id="l00169" name="l00169"></a><span class="lineno"> 169</span> <span class="keywordtype">double</span> d2 = std::pow(d, 2).sum();</div>
|
|
<div class="line"><a id="l00170" name="l00170"></a><span class="lineno"> 170</span> distance += std::sqrt(d2);</div>
|
|
<div class="line"><a id="l00171" name="l00171"></a><span class="lineno"> 171</span> <span class="comment">// distance += d2;</span></div>
|
|
<div class="line"><a id="l00172" name="l00172"></a><span class="lineno"> 172</span> }</div>
|
|
<div class="line"><a id="l00173" name="l00173"></a><span class="lineno"> 173</span> }</div>
|
|
<div class="line"><a id="l00174" name="l00174"></a><span class="lineno"> 174</span> </div>
|
|
<div class="line"><a id="l00175" name="l00175"></a><span class="lineno"> 175</span> distance /= R * R; <span class="comment">// mean distance from neighbors</span></div>
|
|
<div class="line"><a id="l00176" name="l00176"></a><span class="lineno"> 176</span> fp << distance; <span class="comment">// print the mean separation</span></div>
|
|
<div class="line"><a id="l00177" name="l00177"></a><span class="lineno"> 177</span> <span class="keywordflow">if</span> (j < W[0].size() - 1) { <span class="comment">// if not the last column</span></div>
|
|
<div class="line"><a id="l00178" name="l00178"></a><span class="lineno"> 178</span> fp << <span class="charliteral">','</span>; <span class="comment">// suffix comma</span></div>
|
|
<div class="line"><a id="l00179" name="l00179"></a><span class="lineno"> 179</span> }</div>
|
|
<div class="line"><a id="l00180" name="l00180"></a><span class="lineno"> 180</span> }</div>
|
|
<div class="line"><a id="l00181" name="l00181"></a><span class="lineno"> 181</span> <span class="keywordflow">if</span> (i < W.size() - 1) { <span class="comment">// if not the last row</span></div>
|
|
<div class="line"><a id="l00182" name="l00182"></a><span class="lineno"> 182</span> fp << <span class="charliteral">'\n'</span>; <span class="comment">// start a new line</span></div>
|
|
<div class="line"><a id="l00183" name="l00183"></a><span class="lineno"> 183</span> }</div>
|
|
<div class="line"><a id="l00184" name="l00184"></a><span class="lineno"> 184</span> }</div>
|
|
<div class="line"><a id="l00185" name="l00185"></a><span class="lineno"> 185</span> </div>
|
|
<div class="line"><a id="l00186" name="l00186"></a><span class="lineno"> 186</span> fp.close();</div>
|
|
<div class="line"><a id="l00187" name="l00187"></a><span class="lineno"> 187</span> <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a id="l00188" name="l00188"></a><span class="lineno"> 188</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00189" name="l00189"></a><span class="lineno"> 189</span></div>
|
|
<div class="foldopen" id="foldopen00200" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00200" name="l00200"></a><span class="lineno"><a class="line" href="../../d8/d77/namespacemachine__learning.html#ae868ad43698a1d69ba46ea3827d7d2c3"> 200</a></span><span class="keywordtype">double</span> <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ae868ad43698a1d69ba46ea3827d7d2c3">update_weights</a>(<span class="keyword">const</span> std::valarray<double> &X,</div>
|
|
<div class="line"><a id="l00201" name="l00201"></a><span class="lineno"> 201</span> std::vector<std::vector<std::valarray<double>>> *W,</div>
|
|
<div class="line"><a id="l00202" name="l00202"></a><span class="lineno"> 202</span> std::vector<std::valarray<double>> *D, <span class="keywordtype">double</span> alpha,</div>
|
|
<div class="line"><a id="l00203" name="l00203"></a><span class="lineno"> 203</span> <span class="keywordtype">int</span> R) {</div>
|
|
<div class="line"><a id="l00204" name="l00204"></a><span class="lineno"> 204</span> <span class="keywordtype">int</span> x = 0, y = 0;</div>
|
|
<div class="line"><a id="l00205" name="l00205"></a><span class="lineno"> 205</span> <span class="keywordtype">int</span> num_out_x = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(W->size()); <span class="comment">// output nodes - in X</span></div>
|
|
<div class="line"><a id="l00206" name="l00206"></a><span class="lineno"> 206</span> <span class="keywordtype">int</span> num_out_y = <span class="keyword">static_cast<</span><span class="keywordtype">int</span><span class="keyword">></span>(W[0][0].size()); <span class="comment">// output nodes - in Y</span></div>
|
|
<div class="line"><a id="l00207" name="l00207"></a><span class="lineno"> 207</span> <span class="comment">// int num_features = static_cast<int>(W[0][0][0].size()); // features =</span></div>
|
|
<div class="line"><a id="l00208" name="l00208"></a><span class="lineno"> 208</span> <span class="comment">// in Z</span></div>
|
|
<div class="line"><a id="l00209" name="l00209"></a><span class="lineno"> 209</span> <span class="keywordtype">double</span> d_min = 0.f;</div>
|
|
<div class="line"><a id="l00210" name="l00210"></a><span class="lineno"> 210</span> </div>
|
|
<div class="line"><a id="l00211" name="l00211"></a><span class="lineno"> 211</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00212" name="l00212"></a><span class="lineno"> 212</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00213" name="l00213"></a><span class="lineno"> 213</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00214" name="l00214"></a><span class="lineno"> 214</span> <span class="comment">// step 1: for each output point</span></div>
|
|
<div class="line"><a id="l00215" name="l00215"></a><span class="lineno"> 215</span> <span class="keywordflow">for</span> (x = 0; x < num_out_x; x++) {</div>
|
|
<div class="line"><a id="l00216" name="l00216"></a><span class="lineno"> 216</span> <span class="keywordflow">for</span> (y = 0; y < num_out_y; y++) {</div>
|
|
<div class="line"><a id="l00217" name="l00217"></a><span class="lineno"> 217</span> (*D)[x][y] = 0.f;</div>
|
|
<div class="line"><a id="l00218" name="l00218"></a><span class="lineno"> 218</span> <span class="comment">// compute Euclidian distance of each output</span></div>
|
|
<div class="line"><a id="l00219" name="l00219"></a><span class="lineno"> 219</span> <span class="comment">// point from the current sample</span></div>
|
|
<div class="line"><a id="l00220" name="l00220"></a><span class="lineno"> 220</span> <span class="keyword">auto</span> d = ((*W)[x][y] - X);</div>
|
|
<div class="line"><a id="l00221" name="l00221"></a><span class="lineno"> 221</span> (*D)[x][y] = (d * d).<a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#a6f1c98c016ad34ff3d9f39372161bd35">sum</a>();</div>
|
|
<div class="line"><a id="l00222" name="l00222"></a><span class="lineno"> 222</span> (*D)[x][y] = std::sqrt((*D)[x][y]);</div>
|
|
<div class="line"><a id="l00223" name="l00223"></a><span class="lineno"> 223</span> }</div>
|
|
<div class="line"><a id="l00224" name="l00224"></a><span class="lineno"> 224</span> }</div>
|
|
<div class="line"><a id="l00225" name="l00225"></a><span class="lineno"> 225</span> </div>
|
|
<div class="line"><a id="l00226" name="l00226"></a><span class="lineno"> 226</span> <span class="comment">// step 2: get closest node i.e., node with snallest Euclidian distance</span></div>
|
|
<div class="line"><a id="l00227" name="l00227"></a><span class="lineno"> 227</span> <span class="comment">// to the current pattern</span></div>
|
|
<div class="line"><a id="l00228" name="l00228"></a><span class="lineno"> 228</span> <span class="keywordtype">int</span> d_min_x = 0, d_min_y = 0;</div>
|
|
<div class="line"><a id="l00229" name="l00229"></a><span class="lineno"> 229</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#ga60f9186ccb682724a8792a2bf81e9b9e">get_min_2d</a>(*D, &d_min, &d_min_x, &d_min_y);</div>
|
|
<div class="line"><a id="l00230" name="l00230"></a><span class="lineno"> 230</span> </div>
|
|
<div class="line"><a id="l00231" name="l00231"></a><span class="lineno"> 231</span> <span class="comment">// step 3a: get the neighborhood range</span></div>
|
|
<div class="line"><a id="l00232" name="l00232"></a><span class="lineno"> 232</span> <span class="keywordtype">int</span> from_x = std::max(0, d_min_x - R);</div>
|
|
<div class="line"><a id="l00233" name="l00233"></a><span class="lineno"> 233</span> <span class="keywordtype">int</span> to_x = std::min(num_out_x, d_min_x + R + 1);</div>
|
|
<div class="line"><a id="l00234" name="l00234"></a><span class="lineno"> 234</span> <span class="keywordtype">int</span> from_y = std::max(0, d_min_y - R);</div>
|
|
<div class="line"><a id="l00235" name="l00235"></a><span class="lineno"> 235</span> <span class="keywordtype">int</span> to_y = std::min(num_out_y, d_min_y + R + 1);</div>
|
|
<div class="line"><a id="l00236" name="l00236"></a><span class="lineno"> 236</span> </div>
|
|
<div class="line"><a id="l00237" name="l00237"></a><span class="lineno"> 237</span> <span class="comment">// step 3b: update the weights of nodes in the</span></div>
|
|
<div class="line"><a id="l00238" name="l00238"></a><span class="lineno"> 238</span> <span class="comment">// neighborhood</span></div>
|
|
<div class="line"><a id="l00239" name="l00239"></a><span class="lineno"> 239</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00240" name="l00240"></a><span class="lineno"> 240</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00241" name="l00241"></a><span class="lineno"> 241</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00242" name="l00242"></a><span class="lineno"> 242</span> <span class="keywordflow">for</span> (x = from_x; x < to_x; x++) {</div>
|
|
<div class="line"><a id="l00243" name="l00243"></a><span class="lineno"> 243</span> <span class="keywordflow">for</span> (y = from_y; y < to_y; y++) {</div>
|
|
<div class="line"><a id="l00244" name="l00244"></a><span class="lineno"> 244</span> <span class="comment">/* you can enable the following normalization if needed.</span></div>
|
|
<div class="line"><a id="l00245" name="l00245"></a><span class="lineno"> 245</span><span class="comment"> personally, I found it detrimental to convergence */</span></div>
|
|
<div class="line"><a id="l00246" name="l00246"></a><span class="lineno"> 246</span> <span class="comment">// const double s2pi = sqrt(2.f * M_PI);</span></div>
|
|
<div class="line"><a id="l00247" name="l00247"></a><span class="lineno"> 247</span> <span class="comment">// double normalize = 1.f / (alpha * s2pi);</span></div>
|
|
<div class="line"><a id="l00248" name="l00248"></a><span class="lineno"> 248</span> </div>
|
|
<div class="line"><a id="l00249" name="l00249"></a><span class="lineno"> 249</span> <span class="comment">/* apply scaling inversely proportional to distance from the</span></div>
|
|
<div class="line"><a id="l00250" name="l00250"></a><span class="lineno"> 250</span><span class="comment"> current node */</span></div>
|
|
<div class="line"><a id="l00251" name="l00251"></a><span class="lineno"> 251</span> <span class="keywordtype">double</span> d2 =</div>
|
|
<div class="line"><a id="l00252" name="l00252"></a><span class="lineno"> 252</span> (d_min_x - x) * (d_min_x - x) + (d_min_y - y) * (d_min_y - y);</div>
|
|
<div class="line"><a id="l00253" name="l00253"></a><span class="lineno"> 253</span> <span class="keywordtype">double</span> scale_factor = std::exp(-d2 / (2.f * alpha * alpha));</div>
|
|
<div class="line"><a id="l00254" name="l00254"></a><span class="lineno"> 254</span> </div>
|
|
<div class="line"><a id="l00255" name="l00255"></a><span class="lineno"> 255</span> (*W)[x][y] += (X - (*W)[x][y]) * alpha * scale_factor;</div>
|
|
<div class="line"><a id="l00256" name="l00256"></a><span class="lineno"> 256</span> }</div>
|
|
<div class="line"><a id="l00257" name="l00257"></a><span class="lineno"> 257</span> }</div>
|
|
<div class="line"><a id="l00258" name="l00258"></a><span class="lineno"> 258</span> <span class="keywordflow">return</span> d_min;</div>
|
|
<div class="line"><a id="l00259" name="l00259"></a><span class="lineno"> 259</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00260" name="l00260"></a><span class="lineno"> 260</span></div>
|
|
<div class="foldopen" id="foldopen00269" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00269" name="l00269"></a><span class="lineno"><a class="line" href="../../d8/d77/namespacemachine__learning.html#ac43d294e21a0c4fa33c53757df054576"> 269</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ac43d294e21a0c4fa33c53757df054576">kohonen_som</a>(<span class="keyword">const</span> std::vector<std::valarray<double>> &X,</div>
|
|
<div class="line"><a id="l00270" name="l00270"></a><span class="lineno"> 270</span> std::vector<std::vector<std::valarray<double>>> *W,</div>
|
|
<div class="line"><a id="l00271" name="l00271"></a><span class="lineno"> 271</span> <span class="keywordtype">double</span> alpha_min) {</div>
|
|
<div class="line"><a id="l00272" name="l00272"></a><span class="lineno"> 272</span> <span class="keywordtype">size_t</span> num_samples = X.size(); <span class="comment">// number of rows</span></div>
|
|
<div class="line"><a id="l00273" name="l00273"></a><span class="lineno"> 273</span> <span class="comment">// size_t num_features = X[0].size(); // number of columns</span></div>
|
|
<div class="line"><a id="l00274" name="l00274"></a><span class="lineno"> 274</span> <span class="keywordtype">size_t</span> num_out = W->size(); <span class="comment">// output matrix size</span></div>
|
|
<div class="line"><a id="l00275" name="l00275"></a><span class="lineno"> 275</span> <span class="keywordtype">size_t</span> R = num_out >> 2, iter = 0;</div>
|
|
<div class="line"><a id="l00276" name="l00276"></a><span class="lineno"> 276</span> <span class="keywordtype">double</span> alpha = 1.f;</div>
|
|
<div class="line"><a id="l00277" name="l00277"></a><span class="lineno"> 277</span> </div>
|
|
<div class="line"><a id="l00278" name="l00278"></a><span class="lineno"> 278</span> std::vector<std::valarray<double>> D(num_out);</div>
|
|
<div class="line"><a id="l00279" name="l00279"></a><span class="lineno"> 279</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < num_out; i++) D[i] = std::valarray<double>(num_out);</div>
|
|
<div class="line"><a id="l00280" name="l00280"></a><span class="lineno"> 280</span> </div>
|
|
<div class="line"><a id="l00281" name="l00281"></a><span class="lineno"> 281</span> <span class="keywordtype">double</span> dmin = 1.f; <span class="comment">// average minimum distance of all samples</span></div>
|
|
<div class="line"><a id="l00282" name="l00282"></a><span class="lineno"> 282</span> <span class="keywordtype">double</span> past_dmin = 1.f; <span class="comment">// average minimum distance of all samples</span></div>
|
|
<div class="line"><a id="l00283" name="l00283"></a><span class="lineno"> 283</span> <span class="keywordtype">double</span> dmin_ratio = 1.f; <span class="comment">// change per step</span></div>
|
|
<div class="line"><a id="l00284" name="l00284"></a><span class="lineno"> 284</span> </div>
|
|
<div class="line"><a id="l00285" name="l00285"></a><span class="lineno"> 285</span> <span class="comment">// Loop alpha from 1 to slpha_min</span></div>
|
|
<div class="line"><a id="l00286" name="l00286"></a><span class="lineno"> 286</span> <span class="keywordflow">for</span> (; alpha > 0 && dmin_ratio > 1e-5; alpha -= 1e-4, iter++) {</div>
|
|
<div class="line"><a id="l00287" name="l00287"></a><span class="lineno"> 287</span> <span class="comment">// Loop for each sample pattern in the data set</span></div>
|
|
<div class="line"><a id="l00288" name="l00288"></a><span class="lineno"> 288</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> sample = 0; sample < num_samples; sample++) {</div>
|
|
<div class="line"><a id="l00289" name="l00289"></a><span class="lineno"> 289</span> <span class="comment">// update weights for the current input pattern sample</span></div>
|
|
<div class="line"><a id="l00290" name="l00290"></a><span class="lineno"> 290</span> dmin += <a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ae868ad43698a1d69ba46ea3827d7d2c3">update_weights</a>(X[sample], W, &D, alpha, R);</div>
|
|
<div class="line"><a id="l00291" name="l00291"></a><span class="lineno"> 291</span> }</div>
|
|
<div class="line"><a id="l00292" name="l00292"></a><span class="lineno"> 292</span> </div>
|
|
<div class="line"><a id="l00293" name="l00293"></a><span class="lineno"> 293</span> <span class="comment">// every 100th iteration, reduce the neighborhood range</span></div>
|
|
<div class="line"><a id="l00294" name="l00294"></a><span class="lineno"> 294</span> <span class="keywordflow">if</span> (iter % 300 == 0 && R > 1) {</div>
|
|
<div class="line"><a id="l00295" name="l00295"></a><span class="lineno"> 295</span> R--;</div>
|
|
<div class="line"><a id="l00296" name="l00296"></a><span class="lineno"> 296</span> }</div>
|
|
<div class="line"><a id="l00297" name="l00297"></a><span class="lineno"> 297</span> </div>
|
|
<div class="line"><a id="l00298" name="l00298"></a><span class="lineno"> 298</span> dmin /= num_samples;</div>
|
|
<div class="line"><a id="l00299" name="l00299"></a><span class="lineno"> 299</span> </div>
|
|
<div class="line"><a id="l00300" name="l00300"></a><span class="lineno"> 300</span> <span class="comment">// termination condition variable -> % change in minimum distance</span></div>
|
|
<div class="line"><a id="l00301" name="l00301"></a><span class="lineno"> 301</span> dmin_ratio = (past_dmin - dmin) / past_dmin;</div>
|
|
<div class="line"><a id="l00302" name="l00302"></a><span class="lineno"> 302</span> <span class="keywordflow">if</span> (dmin_ratio < 0) {</div>
|
|
<div class="line"><a id="l00303" name="l00303"></a><span class="lineno"> 303</span> dmin_ratio = 1.f;</div>
|
|
<div class="line"><a id="l00304" name="l00304"></a><span class="lineno"> 304</span> }</div>
|
|
<div class="line"><a id="l00305" name="l00305"></a><span class="lineno"> 305</span> past_dmin = dmin;</div>
|
|
<div class="line"><a id="l00306" name="l00306"></a><span class="lineno"> 306</span> </div>
|
|
<div class="line"><a id="l00307" name="l00307"></a><span class="lineno"> 307</span> std::cout << <span class="stringliteral">"iter: "</span> << iter << <span class="stringliteral">"\t alpha: "</span> << alpha << <span class="stringliteral">"\t R: "</span> << R</div>
|
|
<div class="line"><a id="l00308" name="l00308"></a><span class="lineno"> 308</span> << <span class="stringliteral">"\t d_min: "</span> << dmin_ratio << <span class="stringliteral">"\r"</span>;</div>
|
|
<div class="line"><a id="l00309" name="l00309"></a><span class="lineno"> 309</span> }</div>
|
|
<div class="line"><a id="l00310" name="l00310"></a><span class="lineno"> 310</span> </div>
|
|
<div class="line"><a id="l00311" name="l00311"></a><span class="lineno"> 311</span> std::cout << <span class="stringliteral">"\n"</span>;</div>
|
|
<div class="line"><a id="l00312" name="l00312"></a><span class="lineno"> 312</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00313" name="l00313"></a><span class="lineno"> 313</span> </div>
|
|
<div class="line"><a id="l00314" name="l00314"></a><span class="lineno"> 314</span>} <span class="comment">// namespace machine_learning</span></div>
|
|
<div class="line"><a id="l00315" name="l00315"></a><span class="lineno"> 315</span> </div>
|
|
<div class="line"><a id="l00316" name="l00316"></a><span class="lineno"> 316</span><span class="keyword">using </span><a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#ac43d294e21a0c4fa33c53757df054576">machine_learning::kohonen_som</a>;</div>
|
|
<div class="line"><a id="l00317" name="l00317"></a><span class="lineno"> 317</span><span class="keyword">using </span><a class="code hl_function" href="../../d8/d77/namespacemachine__learning.html#aa72a53c88203fde278f1fe6c3afe5b07">machine_learning::save_u_matrix</a>;</div>
|
|
<div class="line"><a id="l00318" name="l00318"></a><span class="lineno"> 318</span></div>
|
|
<div class="line"><a id="l00320" name="l00320"></a><span class="lineno"> 320</span></div>
|
|
<div class="foldopen" id="foldopen00330" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00330" name="l00330"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a48efb079040c7aaa3a4917a0e486cba9"> 330</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a48efb079040c7aaa3a4917a0e486cba9">test_2d_classes</a>(std::vector<std::valarray<double>> *<a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>) {</div>
|
|
<div class="line"><a id="l00331" name="l00331"></a><span class="lineno"> 331</span> <span class="keyword">const</span> <span class="keywordtype">int</span> N = <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>->size();</div>
|
|
<div class="line"><a id="l00332" name="l00332"></a><span class="lineno"> 332</span> <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
|
|
<div class="line"><a id="l00333" name="l00333"></a><span class="lineno"> 333</span> <span class="keywordtype">int</span> i = 0;</div>
|
|
<div class="line"><a id="l00334" name="l00334"></a><span class="lineno"> 334</span> <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
|
|
<div class="line"><a id="l00335" name="l00335"></a><span class="lineno"> 335</span> std::array<std::array<double, 2>, num_classes> centres = {</div>
|
|
<div class="line"><a id="l00336" name="l00336"></a><span class="lineno"> 336</span> <span class="comment">// centres of each class cluster</span></div>
|
|
<div class="line"><a id="l00337" name="l00337"></a><span class="lineno"> 337</span> std::array<double, 2>({.5, .5}), <span class="comment">// centre of class 1</span></div>
|
|
<div class="line"><a id="l00338" name="l00338"></a><span class="lineno"> 338</span> std::array<double, 2>({.5, -.5}), <span class="comment">// centre of class 2</span></div>
|
|
<div class="line"><a id="l00339" name="l00339"></a><span class="lineno"> 339</span> std::array<double, 2>({-.5, .5}), <span class="comment">// centre of class 3</span></div>
|
|
<div class="line"><a id="l00340" name="l00340"></a><span class="lineno"> 340</span> std::array<double, 2>({-.5, -.5}) <span class="comment">// centre of class 4</span></div>
|
|
<div class="line"><a id="l00341" name="l00341"></a><span class="lineno"> 341</span> };</div>
|
|
<div class="line"><a id="l00342" name="l00342"></a><span class="lineno"> 342</span> </div>
|
|
<div class="line"><a id="l00343" name="l00343"></a><span class="lineno"> 343</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00344" name="l00344"></a><span class="lineno"> 344</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00345" name="l00345"></a><span class="lineno"> 345</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00346" name="l00346"></a><span class="lineno"> 346</span> <span class="keywordflow">for</span> (i = 0; i < N; i++) {</div>
|
|
<div class="line"><a id="l00347" name="l00347"></a><span class="lineno"> 347</span> <span class="comment">// select a random class for the point</span></div>
|
|
<div class="line"><a id="l00348" name="l00348"></a><span class="lineno"> 348</span> <span class="keywordtype">int</span> cls = std::rand() % num_classes;</div>
|
|
<div class="line"><a id="l00349" name="l00349"></a><span class="lineno"> 349</span> </div>
|
|
<div class="line"><a id="l00350" name="l00350"></a><span class="lineno"> 350</span> <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
|
|
<div class="line"><a id="l00351" name="l00351"></a><span class="lineno"> 351</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
|
|
<div class="line"><a id="l00352" name="l00352"></a><span class="lineno"> 352</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
|
|
<div class="line"><a id="l00353" name="l00353"></a><span class="lineno"> 353</span> </div>
|
|
<div class="line"><a id="l00354" name="l00354"></a><span class="lineno"> 354</span> <span class="comment">/* The follosing can also be used</span></div>
|
|
<div class="line"><a id="l00355" name="l00355"></a><span class="lineno"> 355</span><span class="comment"> for (int j = 0; j < 2; j++)</span></div>
|
|
<div class="line"><a id="l00356" name="l00356"></a><span class="lineno"> 356</span><span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
|
|
<div class="line"><a id="l00357" name="l00357"></a><span class="lineno"> 357</span><span class="comment"> */</span></div>
|
|
<div class="line"><a id="l00358" name="l00358"></a><span class="lineno"> 358</span> }</div>
|
|
<div class="line"><a id="l00359" name="l00359"></a><span class="lineno"> 359</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00360" name="l00360"></a><span class="lineno"> 360</span></div>
|
|
<div class="foldopen" id="foldopen00369" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00369" name="l00369"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0"> 369</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a>() {</div>
|
|
<div class="line"><a id="l00370" name="l00370"></a><span class="lineno"> 370</span> <span class="keywordtype">int</span> j = 0, N = 300;</div>
|
|
<div class="line"><a id="l00371" name="l00371"></a><span class="lineno"> 371</span> <span class="keywordtype">int</span> features = 2;</div>
|
|
<div class="line"><a id="l00372" name="l00372"></a><span class="lineno"> 372</span> <span class="keywordtype">int</span> num_out = 30;</div>
|
|
<div class="line"><a id="l00373" name="l00373"></a><span class="lineno"> 373</span> std::vector<std::valarray<double>> X(N);</div>
|
|
<div class="line"><a id="l00374" name="l00374"></a><span class="lineno"> 374</span> std::vector<std::vector<std::valarray<double>>> W(num_out);</div>
|
|
<div class="line"><a id="l00375" name="l00375"></a><span class="lineno"> 375</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < std::max(num_out, N); i++) {</div>
|
|
<div class="line"><a id="l00376" name="l00376"></a><span class="lineno"> 376</span> <span class="comment">// loop till max(N, num_out)</span></div>
|
|
<div class="line"><a id="l00377" name="l00377"></a><span class="lineno"> 377</span> <span class="keywordflow">if</span> (i < N) { <span class="comment">// only add new arrays if i < N</span></div>
|
|
<div class="line"><a id="l00378" name="l00378"></a><span class="lineno"> 378</span> X[i] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00379" name="l00379"></a><span class="lineno"> 379</span> }</div>
|
|
<div class="line"><a id="l00380" name="l00380"></a><span class="lineno"> 380</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
|
|
<div class="line"><a id="l00381" name="l00381"></a><span class="lineno"> 381</span> W[i] = std::vector<std::valarray<double>>(num_out);</div>
|
|
<div class="line"><a id="l00382" name="l00382"></a><span class="lineno"> 382</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
|
|
<div class="line"><a id="l00383" name="l00383"></a><span class="lineno"> 383</span> W[i][k] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00384" name="l00384"></a><span class="lineno"> 384</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00385" name="l00385"></a><span class="lineno"> 385</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00386" name="l00386"></a><span class="lineno"> 386</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00387" name="l00387"></a><span class="lineno"> 387</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
|
|
<div class="line"><a id="l00388" name="l00388"></a><span class="lineno"> 388</span> <span class="comment">// preallocate with random initial weights</span></div>
|
|
<div class="line"><a id="l00389" name="l00389"></a><span class="lineno"> 389</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
|
|
<div class="line"><a id="l00390" name="l00390"></a><span class="lineno"> 390</span> }</div>
|
|
<div class="line"><a id="l00391" name="l00391"></a><span class="lineno"> 391</span> }</div>
|
|
<div class="line"><a id="l00392" name="l00392"></a><span class="lineno"> 392</span> }</div>
|
|
<div class="line"><a id="l00393" name="l00393"></a><span class="lineno"> 393</span> }</div>
|
|
<div class="line"><a id="l00394" name="l00394"></a><span class="lineno"> 394</span> </div>
|
|
<div class="line"><a id="l00395" name="l00395"></a><span class="lineno"> 395</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a48efb079040c7aaa3a4917a0e486cba9">test_2d_classes</a>(&X); <span class="comment">// create test data around circumference of a circle</span></div>
|
|
<div class="line"><a id="l00396" name="l00396"></a><span class="lineno"> 396</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c">save_2d_data</a>(<span class="stringliteral">"test1.csv"</span>, X); <span class="comment">// save test data points</span></div>
|
|
<div class="line"><a id="l00397" name="l00397"></a><span class="lineno"> 397</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w11.csv"</span>, W); <span class="comment">// save initial random weights</span></div>
|
|
<div class="line"><a id="l00398" name="l00398"></a><span class="lineno"> 398</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#ac43d294e21a0c4fa33c53757df054576">kohonen_som</a>(X, &W, 1e-4); <span class="comment">// train the SOM</span></div>
|
|
<div class="line"><a id="l00399" name="l00399"></a><span class="lineno"> 399</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w12.csv"</span>, W); <span class="comment">// save the resultant weights</span></div>
|
|
<div class="line"><a id="l00400" name="l00400"></a><span class="lineno"> 400</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00401" name="l00401"></a><span class="lineno"> 401</span></div>
|
|
<div class="foldopen" id="foldopen00411" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00411" name="l00411"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a1302662a56ebf67a21249270b017297e"> 411</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a1302662a56ebf67a21249270b017297e">test_3d_classes1</a>(std::vector<std::valarray<double>> *<a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>) {</div>
|
|
<div class="line"><a id="l00412" name="l00412"></a><span class="lineno"> 412</span> <span class="keyword">const</span> <span class="keywordtype">size_t</span> N = <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>->size();</div>
|
|
<div class="line"><a id="l00413" name="l00413"></a><span class="lineno"> 413</span> <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.3; <span class="comment">// radius of cluster</span></div>
|
|
<div class="line"><a id="l00414" name="l00414"></a><span class="lineno"> 414</span> <span class="keywordtype">int</span> i = 0;</div>
|
|
<div class="line"><a id="l00415" name="l00415"></a><span class="lineno"> 415</span> <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 4;</div>
|
|
<div class="line"><a id="l00416" name="l00416"></a><span class="lineno"> 416</span> <span class="keyword">const</span> std::array<std::array<double, 3>, num_classes> centres = {</div>
|
|
<div class="line"><a id="l00417" name="l00417"></a><span class="lineno"> 417</span> <span class="comment">// centres of each class cluster</span></div>
|
|
<div class="line"><a id="l00418" name="l00418"></a><span class="lineno"> 418</span> std::array<double, 3>({.5, .5, .5}), <span class="comment">// centre of class 1</span></div>
|
|
<div class="line"><a id="l00419" name="l00419"></a><span class="lineno"> 419</span> std::array<double, 3>({.5, -.5, -.5}), <span class="comment">// centre of class 2</span></div>
|
|
<div class="line"><a id="l00420" name="l00420"></a><span class="lineno"> 420</span> std::array<double, 3>({-.5, .5, .5}), <span class="comment">// centre of class 3</span></div>
|
|
<div class="line"><a id="l00421" name="l00421"></a><span class="lineno"> 421</span> std::array<double, 3>({-.5, -.5 - .5}) <span class="comment">// centre of class 4</span></div>
|
|
<div class="line"><a id="l00422" name="l00422"></a><span class="lineno"> 422</span> };</div>
|
|
<div class="line"><a id="l00423" name="l00423"></a><span class="lineno"> 423</span> </div>
|
|
<div class="line"><a id="l00424" name="l00424"></a><span class="lineno"> 424</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00425" name="l00425"></a><span class="lineno"> 425</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00426" name="l00426"></a><span class="lineno"> 426</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00427" name="l00427"></a><span class="lineno"> 427</span> <span class="keywordflow">for</span> (i = 0; i < N; i++) {</div>
|
|
<div class="line"><a id="l00428" name="l00428"></a><span class="lineno"> 428</span> <span class="comment">// select a random class for the point</span></div>
|
|
<div class="line"><a id="l00429" name="l00429"></a><span class="lineno"> 429</span> <span class="keywordtype">int</span> cls = std::rand() % num_classes;</div>
|
|
<div class="line"><a id="l00430" name="l00430"></a><span class="lineno"> 430</span> </div>
|
|
<div class="line"><a id="l00431" name="l00431"></a><span class="lineno"> 431</span> <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
|
|
<div class="line"><a id="l00432" name="l00432"></a><span class="lineno"> 432</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
|
|
<div class="line"><a id="l00433" name="l00433"></a><span class="lineno"> 433</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
|
|
<div class="line"><a id="l00434" name="l00434"></a><span class="lineno"> 434</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
|
|
<div class="line"><a id="l00435" name="l00435"></a><span class="lineno"> 435</span> </div>
|
|
<div class="line"><a id="l00436" name="l00436"></a><span class="lineno"> 436</span> <span class="comment">/* The follosing can also be used</span></div>
|
|
<div class="line"><a id="l00437" name="l00437"></a><span class="lineno"> 437</span><span class="comment"> for (int j = 0; j < 3; j++)</span></div>
|
|
<div class="line"><a id="l00438" name="l00438"></a><span class="lineno"> 438</span><span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
|
|
<div class="line"><a id="l00439" name="l00439"></a><span class="lineno"> 439</span><span class="comment"> */</span></div>
|
|
<div class="line"><a id="l00440" name="l00440"></a><span class="lineno"> 440</span> }</div>
|
|
<div class="line"><a id="l00441" name="l00441"></a><span class="lineno"> 441</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00442" name="l00442"></a><span class="lineno"> 442</span></div>
|
|
<div class="foldopen" id="foldopen00451" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00451" name="l00451"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0"> 451</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a>() {</div>
|
|
<div class="line"><a id="l00452" name="l00452"></a><span class="lineno"> 452</span> <span class="keywordtype">int</span> j = 0, N = 300;</div>
|
|
<div class="line"><a id="l00453" name="l00453"></a><span class="lineno"> 453</span> <span class="keywordtype">int</span> features = 3;</div>
|
|
<div class="line"><a id="l00454" name="l00454"></a><span class="lineno"> 454</span> <span class="keywordtype">int</span> num_out = 30;</div>
|
|
<div class="line"><a id="l00455" name="l00455"></a><span class="lineno"> 455</span> std::vector<std::valarray<double>> X(N);</div>
|
|
<div class="line"><a id="l00456" name="l00456"></a><span class="lineno"> 456</span> std::vector<std::vector<std::valarray<double>>> W(num_out);</div>
|
|
<div class="line"><a id="l00457" name="l00457"></a><span class="lineno"> 457</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < std::max(num_out, N); i++) {</div>
|
|
<div class="line"><a id="l00458" name="l00458"></a><span class="lineno"> 458</span> <span class="comment">// loop till max(N, num_out)</span></div>
|
|
<div class="line"><a id="l00459" name="l00459"></a><span class="lineno"> 459</span> <span class="keywordflow">if</span> (i < N) { <span class="comment">// only add new arrays if i < N</span></div>
|
|
<div class="line"><a id="l00460" name="l00460"></a><span class="lineno"> 460</span> X[i] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00461" name="l00461"></a><span class="lineno"> 461</span> }</div>
|
|
<div class="line"><a id="l00462" name="l00462"></a><span class="lineno"> 462</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
|
|
<div class="line"><a id="l00463" name="l00463"></a><span class="lineno"> 463</span> W[i] = std::vector<std::valarray<double>>(num_out);</div>
|
|
<div class="line"><a id="l00464" name="l00464"></a><span class="lineno"> 464</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
|
|
<div class="line"><a id="l00465" name="l00465"></a><span class="lineno"> 465</span> W[i][k] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00466" name="l00466"></a><span class="lineno"> 466</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00467" name="l00467"></a><span class="lineno"> 467</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00468" name="l00468"></a><span class="lineno"> 468</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00469" name="l00469"></a><span class="lineno"> 469</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
|
|
<div class="line"><a id="l00470" name="l00470"></a><span class="lineno"> 470</span> <span class="comment">// preallocate with random initial weights</span></div>
|
|
<div class="line"><a id="l00471" name="l00471"></a><span class="lineno"> 471</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
|
|
<div class="line"><a id="l00472" name="l00472"></a><span class="lineno"> 472</span> }</div>
|
|
<div class="line"><a id="l00473" name="l00473"></a><span class="lineno"> 473</span> }</div>
|
|
<div class="line"><a id="l00474" name="l00474"></a><span class="lineno"> 474</span> }</div>
|
|
<div class="line"><a id="l00475" name="l00475"></a><span class="lineno"> 475</span> }</div>
|
|
<div class="line"><a id="l00476" name="l00476"></a><span class="lineno"> 476</span> </div>
|
|
<div class="line"><a id="l00477" name="l00477"></a><span class="lineno"> 477</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a1302662a56ebf67a21249270b017297e">test_3d_classes1</a>(&X); <span class="comment">// create test data around circumference of a circle</span></div>
|
|
<div class="line"><a id="l00478" name="l00478"></a><span class="lineno"> 478</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c">save_2d_data</a>(<span class="stringliteral">"test2.csv"</span>, X); <span class="comment">// save test data points</span></div>
|
|
<div class="line"><a id="l00479" name="l00479"></a><span class="lineno"> 479</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w21.csv"</span>, W); <span class="comment">// save initial random weights</span></div>
|
|
<div class="line"><a id="l00480" name="l00480"></a><span class="lineno"> 480</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#ac43d294e21a0c4fa33c53757df054576">kohonen_som</a>(X, &W, 1e-4); <span class="comment">// train the SOM</span></div>
|
|
<div class="line"><a id="l00481" name="l00481"></a><span class="lineno"> 481</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w22.csv"</span>, W); <span class="comment">// save the resultant weights</span></div>
|
|
<div class="line"><a id="l00482" name="l00482"></a><span class="lineno"> 482</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00483" name="l00483"></a><span class="lineno"> 483</span></div>
|
|
<div class="foldopen" id="foldopen00493" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00493" name="l00493"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a4b7ab643f6a5002f991837de46f70653"> 493</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a4b7ab643f6a5002f991837de46f70653">test_3d_classes2</a>(std::vector<std::valarray<double>> *<a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>) {</div>
|
|
<div class="line"><a id="l00494" name="l00494"></a><span class="lineno"> 494</span> <span class="keyword">const</span> <span class="keywordtype">size_t</span> N = <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>->size();</div>
|
|
<div class="line"><a id="l00495" name="l00495"></a><span class="lineno"> 495</span> <span class="keyword">const</span> <span class="keywordtype">double</span> R = 0.2; <span class="comment">// radius of cluster</span></div>
|
|
<div class="line"><a id="l00496" name="l00496"></a><span class="lineno"> 496</span> <span class="keywordtype">int</span> i = 0;</div>
|
|
<div class="line"><a id="l00497" name="l00497"></a><span class="lineno"> 497</span> <span class="keyword">const</span> <span class="keywordtype">int</span> num_classes = 8;</div>
|
|
<div class="line"><a id="l00498" name="l00498"></a><span class="lineno"> 498</span> <span class="keyword">const</span> std::array<std::array<double, 3>, num_classes> centres = {</div>
|
|
<div class="line"><a id="l00499" name="l00499"></a><span class="lineno"> 499</span> <span class="comment">// centres of each class cluster</span></div>
|
|
<div class="line"><a id="l00500" name="l00500"></a><span class="lineno"> 500</span> std::array<double, 3>({.5, .5, .5}), <span class="comment">// centre of class 1</span></div>
|
|
<div class="line"><a id="l00501" name="l00501"></a><span class="lineno"> 501</span> std::array<double, 3>({.5, .5, -.5}), <span class="comment">// centre of class 2</span></div>
|
|
<div class="line"><a id="l00502" name="l00502"></a><span class="lineno"> 502</span> std::array<double, 3>({.5, -.5, .5}), <span class="comment">// centre of class 3</span></div>
|
|
<div class="line"><a id="l00503" name="l00503"></a><span class="lineno"> 503</span> std::array<double, 3>({.5, -.5, -.5}), <span class="comment">// centre of class 4</span></div>
|
|
<div class="line"><a id="l00504" name="l00504"></a><span class="lineno"> 504</span> std::array<double, 3>({-.5, .5, .5}), <span class="comment">// centre of class 5</span></div>
|
|
<div class="line"><a id="l00505" name="l00505"></a><span class="lineno"> 505</span> std::array<double, 3>({-.5, .5, -.5}), <span class="comment">// centre of class 6</span></div>
|
|
<div class="line"><a id="l00506" name="l00506"></a><span class="lineno"> 506</span> std::array<double, 3>({-.5, -.5, .5}), <span class="comment">// centre of class 7</span></div>
|
|
<div class="line"><a id="l00507" name="l00507"></a><span class="lineno"> 507</span> std::array<double, 3>({-.5, -.5, -.5}) <span class="comment">// centre of class 8</span></div>
|
|
<div class="line"><a id="l00508" name="l00508"></a><span class="lineno"> 508</span> };</div>
|
|
<div class="line"><a id="l00509" name="l00509"></a><span class="lineno"> 509</span> </div>
|
|
<div class="line"><a id="l00510" name="l00510"></a><span class="lineno"> 510</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00511" name="l00511"></a><span class="lineno"> 511</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00512" name="l00512"></a><span class="lineno"> 512</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00513" name="l00513"></a><span class="lineno"> 513</span> <span class="keywordflow">for</span> (i = 0; i < N; i++) {</div>
|
|
<div class="line"><a id="l00514" name="l00514"></a><span class="lineno"> 514</span> <span class="comment">// select a random class for the point</span></div>
|
|
<div class="line"><a id="l00515" name="l00515"></a><span class="lineno"> 515</span> <span class="keywordtype">int</span> cls = std::rand() % num_classes;</div>
|
|
<div class="line"><a id="l00516" name="l00516"></a><span class="lineno"> 516</span> </div>
|
|
<div class="line"><a id="l00517" name="l00517"></a><span class="lineno"> 517</span> <span class="comment">// create random coordinates (x,y,z) around the centre of the class</span></div>
|
|
<div class="line"><a id="l00518" name="l00518"></a><span class="lineno"> 518</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][0] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][0] - R, centres[cls][0] + R);</div>
|
|
<div class="line"><a id="l00519" name="l00519"></a><span class="lineno"> 519</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][1] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][1] - R, centres[cls][1] + R);</div>
|
|
<div class="line"><a id="l00520" name="l00520"></a><span class="lineno"> 520</span> <a class="code hl_variable" href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a>[0][i][2] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(centres[cls][2] - R, centres[cls][2] + R);</div>
|
|
<div class="line"><a id="l00521" name="l00521"></a><span class="lineno"> 521</span> </div>
|
|
<div class="line"><a id="l00522" name="l00522"></a><span class="lineno"> 522</span> <span class="comment">/* The follosing can also be used</span></div>
|
|
<div class="line"><a id="l00523" name="l00523"></a><span class="lineno"> 523</span><span class="comment"> for (int j = 0; j < 3; j++)</span></div>
|
|
<div class="line"><a id="l00524" name="l00524"></a><span class="lineno"> 524</span><span class="comment"> data[i][j] = _random(centres[class][j] - R, centres[class][j] + R);</span></div>
|
|
<div class="line"><a id="l00525" name="l00525"></a><span class="lineno"> 525</span><span class="comment"> */</span></div>
|
|
<div class="line"><a id="l00526" name="l00526"></a><span class="lineno"> 526</span> }</div>
|
|
<div class="line"><a id="l00527" name="l00527"></a><span class="lineno"> 527</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00528" name="l00528"></a><span class="lineno"> 528</span></div>
|
|
<div class="foldopen" id="foldopen00537" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00537" name="l00537"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e"> 537</a></span><span class="keywordtype">void</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a>() {</div>
|
|
<div class="line"><a id="l00538" name="l00538"></a><span class="lineno"> 538</span> <span class="keywordtype">int</span> j = 0, N = 500;</div>
|
|
<div class="line"><a id="l00539" name="l00539"></a><span class="lineno"> 539</span> <span class="keywordtype">int</span> features = 3;</div>
|
|
<div class="line"><a id="l00540" name="l00540"></a><span class="lineno"> 540</span> <span class="keywordtype">int</span> num_out = 30;</div>
|
|
<div class="line"><a id="l00541" name="l00541"></a><span class="lineno"> 541</span> std::vector<std::valarray<double>> X(N);</div>
|
|
<div class="line"><a id="l00542" name="l00542"></a><span class="lineno"> 542</span> std::vector<std::vector<std::valarray<double>>> W(num_out);</div>
|
|
<div class="line"><a id="l00543" name="l00543"></a><span class="lineno"> 543</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < std::max(num_out, N); i++) {</div>
|
|
<div class="line"><a id="l00544" name="l00544"></a><span class="lineno"> 544</span> <span class="comment">// loop till max(N, num_out)</span></div>
|
|
<div class="line"><a id="l00545" name="l00545"></a><span class="lineno"> 545</span> <span class="keywordflow">if</span> (i < N) { <span class="comment">// only add new arrays if i < N</span></div>
|
|
<div class="line"><a id="l00546" name="l00546"></a><span class="lineno"> 546</span> X[i] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00547" name="l00547"></a><span class="lineno"> 547</span> }</div>
|
|
<div class="line"><a id="l00548" name="l00548"></a><span class="lineno"> 548</span> <span class="keywordflow">if</span> (i < num_out) { <span class="comment">// only add new arrays if i < num_out</span></div>
|
|
<div class="line"><a id="l00549" name="l00549"></a><span class="lineno"> 549</span> W[i] = std::vector<std::valarray<double>>(num_out);</div>
|
|
<div class="line"><a id="l00550" name="l00550"></a><span class="lineno"> 550</span> <span class="keywordflow">for</span> (<span class="keywordtype">int</span> k = 0; k < num_out; k++) {</div>
|
|
<div class="line"><a id="l00551" name="l00551"></a><span class="lineno"> 551</span> W[i][k] = std::valarray<double>(features);</div>
|
|
<div class="line"><a id="l00552" name="l00552"></a><span class="lineno"> 552</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00553" name="l00553"></a><span class="lineno"> 553</span><span class="preprocessor">#pragma omp for</span></div>
|
|
<div class="line"><a id="l00554" name="l00554"></a><span class="lineno"> 554</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00555" name="l00555"></a><span class="lineno"> 555</span> <span class="keywordflow">for</span> (j = 0; j < features; j++) {</div>
|
|
<div class="line"><a id="l00556" name="l00556"></a><span class="lineno"> 556</span> <span class="comment">// preallocate with random initial weights</span></div>
|
|
<div class="line"><a id="l00557" name="l00557"></a><span class="lineno"> 557</span> W[i][k][j] = <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a>(-10, 10);</div>
|
|
<div class="line"><a id="l00558" name="l00558"></a><span class="lineno"> 558</span> }</div>
|
|
<div class="line"><a id="l00559" name="l00559"></a><span class="lineno"> 559</span> }</div>
|
|
<div class="line"><a id="l00560" name="l00560"></a><span class="lineno"> 560</span> }</div>
|
|
<div class="line"><a id="l00561" name="l00561"></a><span class="lineno"> 561</span> }</div>
|
|
<div class="line"><a id="l00562" name="l00562"></a><span class="lineno"> 562</span> </div>
|
|
<div class="line"><a id="l00563" name="l00563"></a><span class="lineno"> 563</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a4b7ab643f6a5002f991837de46f70653">test_3d_classes2</a>(&X); <span class="comment">// create test data around circumference of a circle</span></div>
|
|
<div class="line"><a id="l00564" name="l00564"></a><span class="lineno"> 564</span> <a class="code hl_function" href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c">save_2d_data</a>(<span class="stringliteral">"test3.csv"</span>, X); <span class="comment">// save test data points</span></div>
|
|
<div class="line"><a id="l00565" name="l00565"></a><span class="lineno"> 565</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w31.csv"</span>, W); <span class="comment">// save initial random weights</span></div>
|
|
<div class="line"><a id="l00566" name="l00566"></a><span class="lineno"> 566</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#ac43d294e21a0c4fa33c53757df054576">kohonen_som</a>(X, &W, 1e-4); <span class="comment">// train the SOM</span></div>
|
|
<div class="line"><a id="l00567" name="l00567"></a><span class="lineno"> 567</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a>(<span class="stringliteral">"w32.csv"</span>, W); <span class="comment">// save the resultant weights</span></div>
|
|
<div class="line"><a id="l00568" name="l00568"></a><span class="lineno"> 568</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00569" name="l00569"></a><span class="lineno"> 569</span></div>
|
|
<div class="foldopen" id="foldopen00577" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00577" name="l00577"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908"> 577</a></span><span class="keywordtype">double</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a>(clock_t start_t, clock_t end_t) {</div>
|
|
<div class="line"><a id="l00578" name="l00578"></a><span class="lineno"> 578</span> <span class="keywordflow">return</span> <span class="keyword">static_cast<</span><span class="keywordtype">double</span><span class="keyword">></span>(end_t - start_t) / CLOCKS_PER_SEC;</div>
|
|
<div class="line"><a id="l00579" name="l00579"></a><span class="lineno"> 579</span>}</div>
|
|
</div>
|
|
<div class="line"><a id="l00580" name="l00580"></a><span class="lineno"> 580</span></div>
|
|
<div class="foldopen" id="foldopen00582" data-start="{" data-end="}">
|
|
<div class="line"><a id="l00582" name="l00582"></a><span class="lineno"><a class="line" href="../../d4/def/kohonen__som__topology_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4"> 582</a></span><span class="keywordtype">int</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>() {</div>
|
|
<div class="line"><a id="l00583" name="l00583"></a><span class="lineno"> 583</span><span class="preprocessor">#ifdef _OPENMP</span></div>
|
|
<div class="line"><a id="l00584" name="l00584"></a><span class="lineno"> 584</span> std::cout << <span class="stringliteral">"Using OpenMP based parallelization\n"</span>;</div>
|
|
<div class="line"><a id="l00585" name="l00585"></a><span class="lineno"> 585</span><span class="preprocessor">#else</span></div>
|
|
<div class="line"><a id="l00586" name="l00586"></a><span class="lineno"> 586</span> std::cout << <span class="stringliteral">"NOT using OpenMP based parallelization\n"</span>;</div>
|
|
<div class="line"><a id="l00587" name="l00587"></a><span class="lineno"> 587</span><span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a id="l00588" name="l00588"></a><span class="lineno"> 588</span> </div>
|
|
<div class="line"><a id="l00589" name="l00589"></a><span class="lineno"> 589</span> std::srand(std::time(<span class="keyword">nullptr</span>));</div>
|
|
<div class="line"><a id="l00590" name="l00590"></a><span class="lineno"> 590</span> </div>
|
|
<div class="line"><a id="l00591" name="l00591"></a><span class="lineno"> 591</span> std::clock_t start_clk = std::clock();</div>
|
|
<div class="line"><a id="l00592" name="l00592"></a><span class="lineno"> 592</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a>();</div>
|
|
<div class="line"><a id="l00593" name="l00593"></a><span class="lineno"> 593</span> <span class="keyword">auto</span> end_clk = std::clock();</div>
|
|
<div class="line"><a id="l00594" name="l00594"></a><span class="lineno"> 594</span> std::cout << <span class="stringliteral">"Test 1 completed in "</span> << <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a>(start_clk, end_clk)</div>
|
|
<div class="line"><a id="l00595" name="l00595"></a><span class="lineno"> 595</span> << <span class="stringliteral">" sec\n"</span>;</div>
|
|
<div class="line"><a id="l00596" name="l00596"></a><span class="lineno"> 596</span> </div>
|
|
<div class="line"><a id="l00597" name="l00597"></a><span class="lineno"> 597</span> start_clk = std::clock();</div>
|
|
<div class="line"><a id="l00598" name="l00598"></a><span class="lineno"> 598</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a>();</div>
|
|
<div class="line"><a id="l00599" name="l00599"></a><span class="lineno"> 599</span> end_clk = std::clock();</div>
|
|
<div class="line"><a id="l00600" name="l00600"></a><span class="lineno"> 600</span> std::cout << <span class="stringliteral">"Test 2 completed in "</span> << <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a>(start_clk, end_clk)</div>
|
|
<div class="line"><a id="l00601" name="l00601"></a><span class="lineno"> 601</span> << <span class="stringliteral">" sec\n"</span>;</div>
|
|
<div class="line"><a id="l00602" name="l00602"></a><span class="lineno"> 602</span> </div>
|
|
<div class="line"><a id="l00603" name="l00603"></a><span class="lineno"> 603</span> start_clk = std::clock();</div>
|
|
<div class="line"><a id="l00604" name="l00604"></a><span class="lineno"> 604</span> <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a>();</div>
|
|
<div class="line"><a id="l00605" name="l00605"></a><span class="lineno"> 605</span> end_clk = std::clock();</div>
|
|
<div class="line"><a id="l00606" name="l00606"></a><span class="lineno"> 606</span> std::cout << <span class="stringliteral">"Test 3 completed in "</span> << <a class="code hl_function" href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a>(start_clk, end_clk)</div>
|
|
<div class="line"><a id="l00607" name="l00607"></a><span class="lineno"> 607</span> << <span class="stringliteral">" sec\n"</span>;</div>
|
|
<div class="line"><a id="l00608" name="l00608"></a><span class="lineno"> 608</span> </div>
|
|
<div class="line"><a id="l00609" name="l00609"></a><span class="lineno"> 609</span> std::cout</div>
|
|
<div class="line"><a id="l00610" name="l00610"></a><span class="lineno"> 610</span> << <span class="stringliteral">"(Note: Calculated times include: creating test sets, training "</span></div>
|
|
<div class="line"><a id="l00611" name="l00611"></a><span class="lineno"> 611</span> <span class="stringliteral">"model and writing files to disk.)\n\n"</span>;</div>
|
|
<div class="line"><a id="l00612" name="l00612"></a><span class="lineno"> 612</span> <span class="keywordflow">return</span> 0;</div>
|
|
<div class="line"><a id="l00613" name="l00613"></a><span class="lineno"> 613</span>}</div>
|
|
</div>
|
|
<div class="ttc" id="agroup__machine__learning_html_ga60f9186ccb682724a8792a2bf81e9b9e"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#ga60f9186ccb682724a8792a2bf81e9b9e">get_min_2d</a></div><div class="ttdeci">void get_min_2d(const std::vector< std::valarray< double > > &X, double *val, int *x_idx, int *y_idx)</div><div class="ttdef"><b>Definition</b> <a href="#l00105">kohonen_som_topology.cpp:105</a></div></div>
|
|
<div class="ttc" id="agroup__machine__learning_html_gabc90175770bf0d5853c466e14993a08c"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gabc90175770bf0d5853c466e14993a08c">save_2d_data</a></div><div class="ttdeci">int save_2d_data(const char *fname, const std::vector< std::valarray< double > > &X)</div><div class="ttdef"><b>Definition</b> <a href="#l00065">kohonen_som_topology.cpp:65</a></div></div>
|
|
<div class="ttc" id="agroup__machine__learning_html_gaf5ce14f026d6d231bef29161bac2b485"><div class="ttname"><a href="../../d9/d66/group__machine__learning.html#gaf5ce14f026d6d231bef29161bac2b485">_random</a></div><div class="ttdeci">double _random(double a, double b)</div><div class="ttdef"><b>Definition</b> <a href="#l00053">kohonen_som_topology.cpp:53</a></div></div>
|
|
<div class="ttc" id="ahash__search_8cpp_html_a6e1a77282bc65ad359d753d25df23243"><div class="ttname"><a href="../../d1/df3/hash__search_8cpp.html#a6e1a77282bc65ad359d753d25df23243">data</a></div><div class="ttdeci">int data[MAX]</div><div class="ttdoc">test data</div><div class="ttdef"><b>Definition</b> <a href="../../d1/df3/hash__search_8cpp_source.html#l00024">hash_search.cpp:24</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a0283886819c7c140a023582b7269e2d0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a0283886819c7c140a023582b7269e2d0">test2</a></div><div class="ttdeci">void test2()</div><div class="ttdef"><b>Definition</b> <a href="#l00451">kohonen_som_topology.cpp:451</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a1302662a56ebf67a21249270b017297e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a1302662a56ebf67a21249270b017297e">test_3d_classes1</a></div><div class="ttdeci">void test_3d_classes1(std::vector< std::valarray< double > > *data)</div><div class="ttdef"><b>Definition</b> <a href="#l00411">kohonen_som_topology.cpp:411</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a1440a7779ac56f47a3f355ce4a8c7da0"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a1440a7779ac56f47a3f355ce4a8c7da0">test1</a></div><div class="ttdeci">void test1()</div><div class="ttdef"><b>Definition</b> <a href="#l00369">kohonen_som_topology.cpp:369</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a2256c10b16edba377b64a44b6c656908"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a2256c10b16edba377b64a44b6c656908">get_clock_diff</a></div><div class="ttdeci">double get_clock_diff(clock_t start_t, clock_t end_t)</div><div class="ttdef"><b>Definition</b> <a href="#l00577">kohonen_som_topology.cpp:577</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a48efb079040c7aaa3a4917a0e486cba9"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a48efb079040c7aaa3a4917a0e486cba9">test_2d_classes</a></div><div class="ttdeci">void test_2d_classes(std::vector< std::valarray< double > > *data)</div><div class="ttdef"><b>Definition</b> <a href="#l00330">kohonen_som_topology.cpp:330</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a4b7ab643f6a5002f991837de46f70653"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a4b7ab643f6a5002f991837de46f70653">test_3d_classes2</a></div><div class="ttdeci">void test_3d_classes2(std::vector< std::valarray< double > > *data)</div><div class="ttdef"><b>Definition</b> <a href="#l00493">kohonen_som_topology.cpp:493</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_a6d0455dd5c30adda100e95f0423c786e"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#a6d0455dd5c30adda100e95f0423c786e">test3</a></div><div class="ttdeci">void test3()</div><div class="ttdef"><b>Definition</b> <a href="#l00537">kohonen_som_topology.cpp:537</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_aa72a53c88203fde278f1fe6c3afe5b07"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#aa72a53c88203fde278f1fe6c3afe5b07">save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector< std::vector< std::valarray< double > > > &W)</div><div class="ttdef"><b>Definition</b> <a href="#l00142">kohonen_som_topology.cpp:142</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_ac43d294e21a0c4fa33c53757df054576"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ac43d294e21a0c4fa33c53757df054576">kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector< std::valarray< double > > &X, std::vector< std::vector< std::valarray< double > > > *W, double alpha_min)</div><div class="ttdef"><b>Definition</b> <a href="#l00269">kohonen_som_topology.cpp:269</a></div></div>
|
|
<div class="ttc" id="akohonen__som__topology_8cpp_html_ae66f6b31b5ad750f1fe042a706a4e3d4"><div class="ttname"><a href="../../d4/def/kohonen__som__topology_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a></div><div class="ttdeci">int main()</div><div class="ttdef"><b>Definition</b> <a href="#l00582">kohonen_som_topology.cpp:582</a></div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html">machine_learning</a></div><div class="ttdoc">A* search algorithm</div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html_a6f1c98c016ad34ff3d9f39372161bd35"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a6f1c98c016ad34ff3d9f39372161bd35">machine_learning::sum</a></div><div class="ttdeci">T sum(const std::vector< std::valarray< T > > &A)</div><div class="ttdef"><b>Definition</b> <a href="../../d8/d95/vector__ops_8hpp_source.html#l00232">vector_ops.hpp:232</a></div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html_a7220dbb7fa896d83bfb7a50e4fce1786"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#a7220dbb7fa896d83bfb7a50e4fce1786">machine_learning::MIN_DISTANCE</a></div><div class="ttdeci">constexpr double MIN_DISTANCE</div><div class="ttdef"><b>Definition</b> <a href="#l00129">kohonen_som_topology.cpp:129</a></div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html_aa72a53c88203fde278f1fe6c3afe5b07"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#aa72a53c88203fde278f1fe6c3afe5b07">machine_learning::save_u_matrix</a></div><div class="ttdeci">int save_u_matrix(const char *fname, const std::vector< std::vector< std::valarray< double > > > &W)</div><div class="ttdef"><b>Definition</b> <a href="#l00142">kohonen_som_topology.cpp:142</a></div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html_ac43d294e21a0c4fa33c53757df054576"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ac43d294e21a0c4fa33c53757df054576">machine_learning::kohonen_som</a></div><div class="ttdeci">void kohonen_som(const std::vector< std::valarray< double > > &X, std::vector< std::vector< std::valarray< double > > > *W, double alpha_min)</div><div class="ttdef"><b>Definition</b> <a href="#l00269">kohonen_som_topology.cpp:269</a></div></div>
|
|
<div class="ttc" id="anamespacemachine__learning_html_ae868ad43698a1d69ba46ea3827d7d2c3"><div class="ttname"><a href="../../d8/d77/namespacemachine__learning.html#ae868ad43698a1d69ba46ea3827d7d2c3">machine_learning::update_weights</a></div><div class="ttdeci">double update_weights(const std::valarray< double > &X, std::vector< std::vector< std::valarray< double > > > *W, std::vector< std::valarray< double > > *D, double alpha, int R)</div><div class="ttdef"><b>Definition</b> <a href="#l00200">kohonen_som_topology.cpp:200</a></div></div>
|
|
</div><!-- fragment --></div><!-- contents -->
|
|
</div><!-- doc-content -->
|
|
</div><!-- container -->
|
|
<!-- start footer part -->
|
|
<div id="nav-path" class="navpath"><!-- id is needed for treeview function! -->
|
|
<ul>
|
|
<li class="navelem"><a href="../../dir_3343723ae086de42ee4ca9774da3a13f.html">machine_learning</a></li><li class="navelem"><a href="../../d4/def/kohonen__som__topology_8cpp.html">kohonen_som_topology.cpp</a></li>
|
|
<li class="footer">Generated by <a href="https://www.doxygen.org/index.html"><img class="footer" src="../../doxygen.svg" width="104" height="31" alt="doxygen"/></a> 1.14.0 </li>
|
|
</ul>
|
|
</div>
|
|
</body>
|
|
</html>
|