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| 64 | <h1>particles.h</h1><a href="particles_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 |
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| 65 | <a name="l00013"></a>00013 <span class="preprocessor">#ifndef PARTICLES_H</span> |
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| 66 | <a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define PARTICLES_H</span> |
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| 67 | <a name="l00015"></a>00015 <span class="preprocessor"></span> |
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| 68 | <a name="l00016"></a>00016 |
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| 69 | <a name="l00017"></a>00017 <span class="preprocessor">#include "../stat/exp_family.h"</span> |
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| 70 | <a name="l00018"></a>00018 |
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| 71 | <a name="l00019"></a>00019 <span class="keyword">namespace </span>bdm { |
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| 72 | <a name="l00020"></a>00020 |
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| 73 | <a name="l00027"></a><a class="code" href="classbdm_1_1PF.html">00027</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> { |
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| 74 | <a name="l00028"></a>00028 <span class="keyword">protected</span>: |
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| 75 | <a name="l00030"></a><a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe">00030</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>; |
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| 76 | <a name="l00032"></a><a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af">00032</a> <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>; |
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| 77 | <a name="l00034"></a><a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3">00034</a> vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
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| 78 | <a name="l00036"></a><a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1">00036</a> Array<vec> &<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>; |
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| 79 | <a name="l00038"></a><a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf">00038</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>; |
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| 80 | <a name="l00040"></a><a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec">00040</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a>; |
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| 81 | <a name="l00041"></a>00041 |
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| 82 | <a name="l00043"></a><a class="code" href="classbdm_1_1PF.html#9932c7c5865954ef9a438afcbe944e52">00043</a> RESAMPLING_METHOD <a class="code" href="classbdm_1_1PF.html#9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>; |
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| 83 | <a name="l00044"></a>00044 |
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| 84 | <a name="l00047"></a>00047 |
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| 85 | <a name="l00049"></a><a class="code" href="classbdm_1_1PF.html#98ef9ff80c394fafd28680b7a3f831b1">00049</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a>; |
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| 86 | <a name="l00051"></a><a class="code" href="classbdm_1_1PF.html#5a49463a88ee80771a464861df845ff6">00051</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a>; |
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| 87 | <a name="l00053"></a>00053 |
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| 88 | <a name="l00054"></a>00054 <span class="keyword">public</span>: |
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| 89 | <a name="l00057"></a>00057 <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> ( ) : <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>(), <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>() ), <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>() ), <a class="code" href="classbdm_1_1PF.html#98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> ( false ), <a class="code" href="classbdm_1_1PF.html#5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> ( false ) { |
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| 90 | <a name="l00058"></a>00058 <a class="code" href="classbdm_1_1BM.html#109c1a626a69031658e3a44e9e500cca" title="IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].">LIDs</a>.set_size ( 5 ); |
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| 91 | <a name="l00059"></a>00059 }; |
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| 92 | <a name="l00060"></a>00060 <span class="comment">/* PF ( mpdf *par0, mpdf *obs0, epdf *epdf0, int n0 ) :</span> |
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| 93 | <a name="l00061"></a>00061 <span class="comment"> est ( ),_w ( est._w() ),_samples ( est._samples() ),opt_L_smp(false), opt_L_wei(false)</span> |
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| 94 | <a name="l00062"></a>00062 <span class="comment"> { set_parameters ( par0,obs0,n0 ); set_statistics ( ones ( n0 ),epdf0 ); };*/</span> |
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| 95 | <a name="l00063"></a>00063 <span class="keywordtype">void</span> set_parameters ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *obs0, <span class="keywordtype">int</span> n0, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
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| 96 | <a name="l00064"></a>00064 <a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a> = par0; |
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| 97 | <a name="l00065"></a>00065 <a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a> = obs0; |
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| 98 | <a name="l00066"></a>00066 <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> = n0; |
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| 99 | <a name="l00067"></a>00067 <a class="code" href="classbdm_1_1PF.html#9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a> = rm; |
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| 100 | <a name="l00068"></a>00068 }; |
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| 101 | <a name="l00069"></a>00069 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec w0, <span class="keyword">const</span> epdf &epdf0 ) { |
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| 102 | <a name="l00070"></a>00070 <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_statistics ( w0, epdf0 ); |
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| 103 | <a name="l00071"></a>00071 }; |
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| 104 | <a name="l00074"></a>00074 <span class="comment">// void set_est ( const epdf &epdf0 );</span> |
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| 105 | <a name="l00075"></a><a class="code" href="classbdm_1_1PF.html#bf104b869b5df8dd4a14bbe430d40488">00075</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#bf104b869b5df8dd4a14bbe430d40488">set_options</a> ( <span class="keyword">const</span> <span class="keywordtype">string</span> &opt ) { |
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| 106 | <a name="l00076"></a>00076 <a class="code" href="classbdm_1_1PF.html#bf104b869b5df8dd4a14bbe430d40488">BM::set_options</a> ( opt ); |
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| 107 | <a name="l00077"></a>00077 <a class="code" href="classbdm_1_1PF.html#5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> = ( opt.find ( <span class="stringliteral">"logweights"</span> ) != string::npos ); |
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| 108 | <a name="l00078"></a>00078 <a class="code" href="classbdm_1_1PF.html#98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> = ( opt.find ( <span class="stringliteral">"logsamples"</span> ) != string::npos ); |
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| 109 | <a name="l00079"></a>00079 } |
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| 110 | <a name="l00080"></a>00080 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#638946eea22d4964bf9350286bb4efd8" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
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| 111 | <a name="l00082"></a><a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed">00082</a> vec* <a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed" title="access function">__w</a>() { |
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| 112 | <a name="l00083"></a>00083 <span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
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| 113 | <a name="l00084"></a>00084 } |
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| 114 | <a name="l00085"></a>00085 }; |
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| 115 | <a name="l00086"></a>00086 |
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| 116 | <a name="l00093"></a>00093 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
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| 117 | <a name="l00094"></a><a class="code" href="classbdm_1_1MPF.html">00094</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> { |
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| 118 | <a name="l00095"></a>00095 Array<BM_T*> BMs; |
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| 119 | <a name="l00096"></a>00096 |
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| 120 | <a name="l00098"></a>00098 |
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| 121 | <a name="l00099"></a>00099 <span class="keyword">class </span>mpfepdf : <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> { |
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| 122 | <a name="l00100"></a>00100 <span class="keyword">protected</span>: |
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| 123 | <a name="l00101"></a>00101 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
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| 124 | <a name="l00102"></a>00102 vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
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| 125 | <a name="l00103"></a>00103 Array<const epdf*> Coms; |
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| 126 | <a name="l00104"></a>00104 <span class="keyword">public</span>: |
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| 127 | <a name="l00105"></a>00105 mpfepdf ( <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E0 ) : |
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| 128 | <a name="l00106"></a>00106 <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ), E ( E0 ), <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( E._w() ), |
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| 129 | <a name="l00107"></a>00107 Coms ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ) { |
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| 130 | <a name="l00108"></a>00108 }; |
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| 131 | <a name="l00110"></a>00110 <span class="keywordtype">void</span> read_statistics ( Array<BM_T*> &A ) { |
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| 132 | <a name="l00111"></a>00111 dim = E.dimension() + A ( 0 )->posterior().dimension(); |
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| 133 | <a name="l00112"></a>00112 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ; i++ ) { |
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| 134 | <a name="l00113"></a>00113 Coms ( i ) = &(A ( i )->posterior()); |
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| 135 | <a name="l00114"></a>00114 } |
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| 136 | <a name="l00115"></a>00115 } |
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| 137 | <a name="l00117"></a>00117 <span class="keywordtype">void</span> set_elements ( <span class="keywordtype">int</span> &i, <span class="keywordtype">double</span> wi, <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* ep ) { |
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| 138 | <a name="l00118"></a>00118 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) = wi; |
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| 139 | <a name="l00119"></a>00119 Coms ( i ) = ep; |
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| 140 | <a name="l00120"></a>00120 }; |
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| 141 | <a name="l00121"></a>00121 |
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| 142 | <a name="l00122"></a>00122 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ) { |
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| 143 | <a name="l00123"></a>00123 E.<a class="code" href="classbdm_1_1epdf.html#840de94aa33cf4f2ebd2427f45a165d8">set_parameters</a> ( n, <span class="keyword">false</span> ); |
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| 144 | <a name="l00124"></a>00124 Coms.set_length ( n ); |
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| 145 | <a name="l00125"></a>00125 } |
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| 146 | <a name="l00126"></a>00126 vec mean()<span class="keyword"> const </span>{ |
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| 147 | <a name="l00127"></a>00127 <span class="comment">// ugly</span> |
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| 148 | <a name="l00128"></a>00128 vec pom = zeros ( Coms ( 0 )->dimension() ); |
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| 149 | <a name="l00129"></a>00129 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
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| 150 | <a name="l00130"></a>00130 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
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| 151 | <a name="l00131"></a>00131 } |
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| 152 | <a name="l00132"></a>00132 <span class="keywordflow">return</span> concat ( E.mean(), pom ); |
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| 153 | <a name="l00133"></a>00133 } |
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| 154 | <a name="l00134"></a>00134 vec variance()<span class="keyword"> const </span>{ |
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| 155 | <a name="l00135"></a>00135 <span class="comment">// ugly</span> |
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| 156 | <a name="l00136"></a>00136 vec pom = zeros ( Coms ( 0 )->dimension() ); |
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| 157 | <a name="l00137"></a>00137 vec pom2 = zeros ( Coms ( 0 )->dimension() ); |
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| 158 | <a name="l00138"></a>00138 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
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| 159 | <a name="l00139"></a>00139 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
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| 160 | <a name="l00140"></a>00140 pom2 += ( Coms ( i )->variance() + pow ( Coms ( i )->mean(), 2 ) ) * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
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| 161 | <a name="l00141"></a>00141 } |
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| 162 | <a name="l00142"></a>00142 <span class="keywordflow">return</span> concat ( E.variance(), pom2 - pow ( pom, 2 ) ); |
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| 163 | <a name="l00143"></a>00143 } |
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| 164 | <a name="l00144"></a>00144 <span class="keywordtype">void</span> qbounds ( vec &lb, vec &ub, <span class="keywordtype">double</span> perc = 0.95 )<span class="keyword"> const </span>{ |
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| 165 | <a name="l00145"></a>00145 <span class="comment">//bounds on particles</span> |
|---|
| 166 | <a name="l00146"></a>00146 vec lbp; |
|---|
| 167 | <a name="l00147"></a>00147 vec ubp; |
|---|
| 168 | <a name="l00148"></a>00148 E.qbounds ( lbp, ubp ); |
|---|
| 169 | <a name="l00149"></a>00149 |
|---|
| 170 | <a name="l00150"></a>00150 <span class="comment">//bounds on Components</span> |
|---|
| 171 | <a name="l00151"></a>00151 <span class="keywordtype">int</span> dimC = Coms ( 0 )->dimension(); |
|---|
| 172 | <a name="l00152"></a>00152 <span class="keywordtype">int</span> j; |
|---|
| 173 | <a name="l00153"></a>00153 <span class="comment">// temporary</span> |
|---|
| 174 | <a name="l00154"></a>00154 vec lbc ( dimC ); |
|---|
| 175 | <a name="l00155"></a>00155 vec ubc ( dimC ); |
|---|
| 176 | <a name="l00156"></a>00156 <span class="comment">// minima and maxima</span> |
|---|
| 177 | <a name="l00157"></a>00157 vec Lbc ( dimC ); |
|---|
| 178 | <a name="l00158"></a>00158 vec Ubc ( dimC ); |
|---|
| 179 | <a name="l00159"></a>00159 Lbc = std::numeric_limits<double>::infinity(); |
|---|
| 180 | <a name="l00160"></a>00160 Ubc = -std::numeric_limits<double>::infinity(); |
|---|
| 181 | <a name="l00161"></a>00161 |
|---|
| 182 | <a name="l00162"></a>00162 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
|---|
| 183 | <a name="l00163"></a>00163 <span class="comment">// check Coms</span> |
|---|
| 184 | <a name="l00164"></a>00164 Coms ( i )->qbounds ( lbc, ubc ); |
|---|
| 185 | <a name="l00165"></a>00165 <span class="keywordflow">for</span> ( j = 0; j < dimC; j++ ) { |
|---|
| 186 | <a name="l00166"></a>00166 <span class="keywordflow">if</span> ( lbc ( j ) < Lbc ( j ) ) { |
|---|
| 187 | <a name="l00167"></a>00167 Lbc ( j ) = lbc ( j ); |
|---|
| 188 | <a name="l00168"></a>00168 } |
|---|
| 189 | <a name="l00169"></a>00169 <span class="keywordflow">if</span> ( ubc ( j ) > Ubc ( j ) ) { |
|---|
| 190 | <a name="l00170"></a>00170 Ubc ( j ) = ubc ( j ); |
|---|
| 191 | <a name="l00171"></a>00171 } |
|---|
| 192 | <a name="l00172"></a>00172 } |
|---|
| 193 | <a name="l00173"></a>00173 } |
|---|
| 194 | <a name="l00174"></a>00174 lb = concat ( lbp, Lbc ); |
|---|
| 195 | <a name="l00175"></a>00175 ub = concat ( ubp, Ubc ); |
|---|
| 196 | <a name="l00176"></a>00176 } |
|---|
| 197 | <a name="l00177"></a>00177 |
|---|
| 198 | <a name="l00178"></a>00178 vec sample()<span class="keyword"> const </span>{ |
|---|
| 199 | <a name="l00179"></a>00179 <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"Not implemented"</span> ); |
|---|
| 200 | <a name="l00180"></a>00180 <span class="keywordflow">return</span> vec(); |
|---|
| 201 | <a name="l00181"></a>00181 } |
|---|
| 202 | <a name="l00182"></a>00182 |
|---|
| 203 | <a name="l00183"></a>00183 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{ |
|---|
| 204 | <a name="l00184"></a>00184 <a class="code" href="bdmerror_8h.html#7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"not implemented"</span> ); |
|---|
| 205 | <a name="l00185"></a>00185 <span class="keywordflow">return</span> 0.0; |
|---|
| 206 | <a name="l00186"></a>00186 } |
|---|
| 207 | <a name="l00187"></a>00187 }; |
|---|
| 208 | <a name="l00188"></a>00188 |
|---|
| 209 | <a name="l00190"></a>00190 mpfepdf jest; |
|---|
| 210 | <a name="l00191"></a>00191 |
|---|
| 211 | <a name="l00193"></a>00193 <span class="keywordtype">bool</span> opt_L_mea; |
|---|
| 212 | <a name="l00194"></a>00194 |
|---|
| 213 | <a name="l00195"></a>00195 <span class="keyword">public</span>: |
|---|
| 214 | <a name="l00197"></a><a class="code" href="classbdm_1_1MPF.html#0068e7ca53d90fa5911eb31a0d657f26">00197</a> <a class="code" href="classbdm_1_1MPF.html#0068e7ca53d90fa5911eb31a0d657f26" title="Default constructor.">MPF</a> () : <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> (), jest ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a> ) {}; |
|---|
| 215 | <a name="l00198"></a>00198 <span class="keywordtype">void</span> set_parameters ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *obs0, <span class="keywordtype">int</span> n0, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
|---|
| 216 | <a name="l00199"></a>00199 PF::set_parameters ( par0, obs0, n0, rm ); |
|---|
| 217 | <a name="l00200"></a>00200 jest.set_parameters ( n0 );<span class="comment">//duplication of rm</span> |
|---|
| 218 | <a name="l00201"></a>00201 BMs.set_length ( n0 ); |
|---|
| 219 | <a name="l00202"></a>00202 } |
|---|
| 220 | <a name="l00203"></a>00203 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> epdf &epdf0, <span class="keyword">const</span> BM_T* BMcond0 ) { |
|---|
| 221 | <a name="l00204"></a>00204 |
|---|
| 222 | <a name="l00205"></a>00205 PF::set_statistics ( ones ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ) / <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>, epdf0 ); |
|---|
| 223 | <a name="l00206"></a>00206 <span class="comment">// copy</span> |
|---|
| 224 | <a name="l00207"></a>00207 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>; i++ ) { |
|---|
| 225 | <a name="l00208"></a>00208 BMs ( i ) = <span class="keyword">new</span> BM_T ( *BMcond0 ); |
|---|
| 226 | <a name="l00209"></a>00209 BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
|---|
| 227 | <a name="l00210"></a>00210 } |
|---|
| 228 | <a name="l00211"></a>00211 |
|---|
| 229 | <a name="l00212"></a>00212 jest.read_statistics ( BMs ); |
|---|
| 230 | <a name="l00213"></a>00213 <span class="comment">//options</span> |
|---|
| 231 | <a name="l00214"></a>00214 }; |
|---|
| 232 | <a name="l00215"></a>00215 |
|---|
| 233 | <a name="l00216"></a>00216 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
|---|
| 234 | <a name="l00217"></a>00217 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{ |
|---|
| 235 | <a name="l00218"></a>00218 <span class="keywordflow">return</span> jest; |
|---|
| 236 | <a name="l00219"></a>00219 } |
|---|
| 237 | <a name="l00221"></a>00221 <span class="comment">/* void set_est ( const epdf& epdf0 ) {</span> |
|---|
| 238 | <a name="l00222"></a>00222 <span class="comment"> PF::set_est ( epdf0 ); // sample params in condition</span> |
|---|
| 239 | <a name="l00223"></a>00223 <span class="comment"> // copy conditions to BMs</span> |
|---|
| 240 | <a name="l00224"></a>00224 <span class="comment"></span> |
|---|
| 241 | <a name="l00225"></a>00225 <span class="comment"> for ( int i=0;i<n;i++ ) {BMs(i)->condition ( _samples ( i ) );}</span> |
|---|
| 242 | <a name="l00226"></a>00226 <span class="comment"> }*/</span> |
|---|
| 243 | <a name="l00227"></a><a class="code" href="classbdm_1_1MPF.html#2e95498dec734088ab9f4878ff404144">00227</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#2e95498dec734088ab9f4878ff404144" title="Set postrior of rvc to samples from epdf0. Statistics of BMs are not re-computed!...">set_options</a> ( <span class="keyword">const</span> <span class="keywordtype">string</span> &opt ) { |
|---|
| 244 | <a name="l00228"></a>00228 <a class="code" href="classbdm_1_1MPF.html#2e95498dec734088ab9f4878ff404144" title="Set postrior of rvc to samples from epdf0. Statistics of BMs are not re-computed!...">PF::set_options</a> ( opt ); |
|---|
| 245 | <a name="l00229"></a>00229 opt_L_mea = ( opt.find ( <span class="stringliteral">"logmeans"</span> ) != string::npos ); |
|---|
| 246 | <a name="l00230"></a>00230 } |
|---|
| 247 | <a name="l00231"></a>00231 |
|---|
| 248 | <a name="l00233"></a><a class="code" href="classbdm_1_1MPF.html#b6e7b094cbe32944b8ccde5df73cd839">00233</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1MPF.html#b6e7b094cbe32944b8ccde5df73cd839" title="Access function.">_BM</a> ( <span class="keywordtype">int</span> i ) { |
|---|
| 249 | <a name="l00234"></a>00234 <span class="keywordflow">return</span> BMs ( i ); |
|---|
| 250 | <a name="l00235"></a>00235 } |
|---|
| 251 | <a name="l00236"></a>00236 }; |
|---|
| 252 | <a name="l00237"></a>00237 |
|---|
| 253 | <a name="l00238"></a>00238 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
|---|
| 254 | <a name="l00239"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00239</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14" title="Incremental Bayes rule.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
|---|
| 255 | <a name="l00240"></a>00240 <span class="keywordtype">int</span> i; |
|---|
| 256 | <a name="l00241"></a>00241 vec lls ( n ); |
|---|
| 257 | <a name="l00242"></a>00242 vec llsP ( n ); |
|---|
| 258 | <a name="l00243"></a>00243 ivec ind; |
|---|
| 259 | <a name="l00244"></a>00244 <span class="keywordtype">double</span> mlls = -std::numeric_limits<double>::infinity(); |
|---|
| 260 | <a name="l00245"></a>00245 |
|---|
| 261 | <a name="l00246"></a>00246 <span class="preprocessor">#pragma omp parallel for</span> |
|---|
| 262 | <a name="l00247"></a>00247 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
|---|
| 263 | <a name="l00248"></a>00248 <span class="comment">//generate new samples from paramater evolution model;</span> |
|---|
| 264 | <a name="l00249"></a>00249 vec old_smp=<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ); |
|---|
| 265 | <a name="l00250"></a>00250 <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) = <a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>-><a class="code" href="classbdm_1_1mpdf.html#f0c1db6fcbb3aae2dd6123884457a367" title="Returns a sample from the density conditioned on cond, .">samplecond</a> ( old_smp ); |
|---|
| 266 | <a name="l00251"></a>00251 llsP ( i ) = <a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>-><a class="code" href="classbdm_1_1mpdf.html#6336a8a72462e2a56a3989a220f18b1b" title="Shortcut for conditioning and evaluation of the internal epdf. In some cases, this...">evallogcond</a> ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ), old_smp ); |
|---|
| 267 | <a name="l00252"></a>00252 BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
|---|
| 268 | <a name="l00253"></a>00253 BMs ( i )->bayes ( dt ); |
|---|
| 269 | <a name="l00254"></a>00254 lls ( i ) = BMs ( i )->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
|---|
| 270 | <a name="l00255"></a>00255 <span class="keywordflow">if</span> ( lls ( i ) > mlls ) mlls = lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
|---|
| 271 | <a name="l00256"></a>00256 } |
|---|
| 272 | <a name="l00257"></a>00257 |
|---|
| 273 | <a name="l00258"></a>00258 <span class="keywordtype">double</span> sum_w = 0.0; |
|---|
| 274 | <a name="l00259"></a>00259 <span class="comment">// compute weights</span> |
|---|
| 275 | <a name="l00260"></a>00260 <span class="preprocessor">#pragma omp parallel for</span> |
|---|
| 276 | <a name="l00261"></a>00261 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
|---|
| 277 | <a name="l00262"></a>00262 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) *= exp ( lls ( i ) - mlls ); <span class="comment">// multiply w by likelihood</span> |
|---|
| 278 | <a name="l00263"></a>00263 sum_w += <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
|---|
| 279 | <a name="l00264"></a>00264 } |
|---|
| 280 | <a name="l00265"></a>00265 |
|---|
| 281 | <a name="l00266"></a>00266 <span class="keywordflow">if</span> ( sum_w > 0.0 ) { |
|---|
| 282 | <a name="l00267"></a>00267 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /= sum_w; <span class="comment">//?</span> |
|---|
| 283 | <a name="l00268"></a>00268 } <span class="keywordflow">else</span> { |
|---|
| 284 | <a name="l00269"></a>00269 cout << <span class="stringliteral">"sum(w)==0"</span> << endl; |
|---|
| 285 | <a name="l00270"></a>00270 } |
|---|
| 286 | <a name="l00271"></a>00271 |
|---|
| 287 | <a name="l00272"></a>00272 |
|---|
| 288 | <a name="l00273"></a>00273 <span class="keywordtype">double</span> eff = 1.0 / ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ); |
|---|
| 289 | <a name="l00274"></a>00274 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
|---|
| 290 | <a name="l00275"></a>00275 ind = <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1eEmp.html#f06ce255de5dbb2313f52ee51f82ba3d" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a> ( <a class="code" href="classbdm_1_1PF.html#9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a> ); |
|---|
| 291 | <a name="l00276"></a>00276 <span class="comment">// Resample Bms!</span> |
|---|
| 292 | <a name="l00277"></a>00277 |
|---|
| 293 | <a name="l00278"></a>00278 <span class="preprocessor">#pragma omp parallel for</span> |
|---|
| 294 | <a name="l00279"></a>00279 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
|---|
| 295 | <a name="l00280"></a>00280 <span class="keywordflow">if</span> ( ind ( i ) != i ) {<span class="comment">//replace the current Bm by a new one</span> |
|---|
| 296 | <a name="l00281"></a>00281 <span class="comment">//fixme this would require new assignment operator</span> |
|---|
| 297 | <a name="l00282"></a>00282 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
|---|
| 298 | <a name="l00283"></a>00283 |
|---|
| 299 | <a name="l00284"></a>00284 <span class="comment">// poor-man's solution: replicate constructor here</span> |
|---|
| 300 | <a name="l00285"></a>00285 <span class="comment">// copied from MPF::MPF</span> |
|---|
| 301 | <a name="l00286"></a>00286 <span class="keyword">delete</span> BMs ( i ); |
|---|
| 302 | <a name="l00287"></a>00287 BMs ( i ) = <span class="keyword">new</span> BM_T ( *BMs ( ind ( i ) ) ); <span class="comment">//copy constructor</span> |
|---|
| 303 | <a name="l00288"></a>00288 <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& pom = BMs ( i )->posterior(); |
|---|
| 304 | <a name="l00289"></a>00289 jest.set_elements ( i, 1.0 / n, &pom ); |
|---|
| 305 | <a name="l00290"></a>00290 } |
|---|
| 306 | <a name="l00291"></a>00291 }; |
|---|
| 307 | <a name="l00292"></a>00292 cout << <span class="charliteral">'.'</span>; |
|---|
| 308 | <a name="l00293"></a>00293 } |
|---|
| 309 | <a name="l00294"></a>00294 } |
|---|
| 310 | <a name="l00295"></a>00295 |
|---|
| 311 | <a name="l00296"></a>00296 } |
|---|
| 312 | <a name="l00297"></a>00297 <span class="preprocessor">#endif // KF_H</span> |
|---|
| 313 | <a name="l00298"></a>00298 <span class="preprocessor"></span> |
|---|
| 314 | <a name="l00299"></a>00299 |
|---|
| 315 | </pre></div></div> |
|---|
| 316 | <hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 29 20:49:42 2009 for mixpp by |
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| 317 | <a href="http://www.doxygen.org/index.html"> |
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| 318 | <img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.8 </small></address> |
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| 319 | </body> |
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| 320 | </html> |
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