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<title>EO: TargetInfo.cpp Source File</title>
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<a class="el" href="dir_000007.html">contrib</a> / <a class="el" href="dir_000008.html">mathsym</a> / <a class="el" href="dir_000012.html">regression</a></div>
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<h1>TargetInfo.cpp</h1><div class="fragment"><pre class="fragment">00001 <span class="comment">/* </span>
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00002 <span class="comment"> * Copyright (C) 2005 Maarten Keijzer</span>
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00003 <span class="comment"> *</span>
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00004 <span class="comment"> * This program is free software; you can redistribute it and/or modify</span>
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00005 <span class="comment"> * it under the terms of version 2 of the GNU General Public License as </span>
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00006 <span class="comment"> * published by the Free Software Foundation. </span>
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00007 <span class="comment"> *</span>
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00008 <span class="comment"> * This program is distributed in the hope that it will be useful,</span>
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00009 <span class="comment"> * but WITHOUT ANY WARRANTY; without even the implied warranty of</span>
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00010 <span class="comment"> * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the</span>
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00011 <span class="comment"> * GNU General Public License for more details.</span>
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00012 <span class="comment"> *</span>
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00013 <span class="comment"> * You should have received a copy of the GNU General Public License</span>
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00014 <span class="comment"> * along with this program; if not, write to the Free Software</span>
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00015 <span class="comment"> * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA</span>
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00016 <span class="comment"> */</span>
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00017
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00018 <span class="preprocessor">#include "TargetInfo.h"</span>
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00019
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00020 <span class="keyword">using</span> <span class="keyword">namespace </span>std;
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00021
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00022 TargetInfo::TargetInfo(<span class="keyword">const</span> TargetInfo& org) { operator=(org); }
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00023
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00024 TargetInfo& TargetInfo::operator=(<span class="keyword">const</span> TargetInfo& org) {
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00025 _targets.resize(org._targets.size());
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00026 _weights.resize(org._weights.size());
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00027 _tcov_part.resize(org._tcov_part.size());
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00028
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00029 _targets = org._targets;
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00030 _weights = org._weights;
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00031 _tcov_part = org._tcov_part;
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00032
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00033 _tmean = org._tmean;
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00034 _tvar = org._tvar;
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00035 _tstd = org._tstd;
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00036 _tmed = org._tmed;
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00037 <span class="keywordflow">return</span> *<span class="keyword">this</span>;
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00038 }
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00039
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00040
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00041 TargetInfo::TargetInfo(<span class="keyword">const</span> std::valarray<double>& t) {
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00042 _weights.resize(0);
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00043 _targets.resize(t.size());
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00044 _targets = t;
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00045
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00046 _tmean = _targets.sum()/_targets.size();
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00047
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00048 _tcov_part.resize(_targets.size());
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00049 _tcov_part = _targets;
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00050 _tcov_part -= _tmean;
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00051
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00052 std::valarray<double> tmp = _tcov_part;
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00053 tmp = _tcov_part;
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00054 tmp *= tmp;
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00055
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00056 _tvar = tmp.sum() / (tmp.size()-1);
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00057 _tstd = sqrt(_tvar);
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00058 _tmed = 0;
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00059 }
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00060
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00061 TargetInfo::TargetInfo(<span class="keyword">const</span> std::valarray<double>& t, <span class="keyword">const</span> std::valarray<double>& w) {
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00062
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00063 _targets.resize(t.size());
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00064 _weights.resize(w.size());
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00065
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00066 _targets = t;
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00067 _weights = w;
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00068
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00069 <span class="keywordtype">double</span> sumw = _weights.sum();
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00070 <span class="comment">// scale weights so that they'll add up to 1</span>
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00071 _weights /= sumw;
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00072
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00073 _tmean = (_targets * _weights).sum();
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00074 _tcov_part.resize(_targets.size());
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00075 _tcov_part = _targets;
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00076 _tcov_part -= _tmean;
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00077
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00078 _tvar = (pow(_targets - _tmean, 2.0) * _weights).sum();
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00079 _tstd = sqrt(_tvar);
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00080 _tmed = 0.;
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00081 }
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00082
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00083 <span class="comment">// calculate the members, now in the context of a mask</span>
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00084 <span class="keywordtype">void</span> TargetInfo::set_training_mask(<span class="keyword">const</span> std::valarray<bool>& tmask) {
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00085
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00086 TargetInfo tmp;
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00087
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00088 <span class="keywordflow">if</span> (has_weights() ) {
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00089 tmp = TargetInfo( _targets[tmask], _weights[tmask]);
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00090 } <span class="keywordflow">else</span> {
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00091 tmp = TargetInfo( _targets[tmask] );
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00092 }
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00093
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00094 _tcov_part.resize(tmp._tcov_part.size());
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00095 _tcov_part = tmp._tcov_part;
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00096
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00097 _tmean = tmp._tmean;
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00098 _tvar = tmp._tvar;
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00099 _tstd = tmp._tstd;
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00100 _tmed = tmp._tmed;
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00101
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00102 _training_mask.resize(tmask.size());
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00103 _training_mask = tmask;
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00104 }
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00105
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00106 <span class="keyword">struct </span>SortOnTargets
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00107 {
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00108 <span class="keyword">const</span> valarray<double>& t;
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00109 SortOnTargets(<span class="keyword">const</span> valarray<double>& v) : t(v) {}
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00110
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00111 <span class="keywordtype">bool</span> operator()(<span class="keywordtype">int</span> i, <span class="keywordtype">int</span> j)<span class="keyword"> const </span>{
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00112 <span class="keywordflow">return</span> fabs(t[i]) < fabs(t[j]);
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00113 }
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00114 };
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00115
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00116 vector<int> TargetInfo::sort() {
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00117
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00118 vector<int> ind(_targets.size());
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00119 <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> i = 0; i < ind.size(); ++i) { ind[i] = i; }
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00120
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00121 std::sort(ind.begin(), ind.end(), SortOnTargets(_targets));
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00122
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00123 valarray<double> tmptargets = _targets;
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00124 valarray<double> tmpweights = _weights;
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00125 valarray<double> tmpcov = _tcov_part;
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00126
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00127 <span class="keywordflow">for</span> (<span class="keywordtype">unsigned</span> i = 0; i < ind.size(); ++i)
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00128 {
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00129 _targets[i] = tmptargets[ ind[i] ];
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00130 _tcov_part[i] = tmpcov[ ind[i] ];
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00131 <span class="keywordflow">if</span> (_weights.size()) _weights[i] = tmpweights[ ind[i] ];
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00132 }
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00133
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00134 <span class="keywordflow">return</span> ind;
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00135 }
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00136
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00137
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00138
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</pre></div><hr size="1"><address style="align: right;"><small>Generated on Thu Oct 19 05:06:44 2006 for EO by
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<a href="http://www.doxygen.org/index.html">
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<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.3.9.1 </small></address>
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