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