| 37 | | <a name="l00043"></a><a class="code" href="classbdm_1_1PF.html#db2ed4517083f83de9d61750a87274de">00043</a> <a class="code" href="classbdm_1_1PF.html#db2ed4517083f83de9d61750a87274de" title="Default constructor.">PF</a> ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs0, <span class="keywordtype">int</span> n0 ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> ( ), |
| 38 | | <a name="l00044"></a>00044 <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ( n0 ),<a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a> ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</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>() ), |
| 39 | | <a name="l00045"></a>00045 <a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" title="Parameter evolution model.">par</a> ( par0 ), <a class="code" href="classbdm_1_1PF.html#c58b8fa634272c3f48845a9020ba55aa" title="Observation model.">obs</a> ( obs0 ) {}; |
| 40 | | <a name="l00046"></a>00046 |
| 41 | | <a name="l00048"></a>00048 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e" title="Set posterior density by sampling from epdf0.">set_est</a> ( <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> &epdf0 ); |
| 42 | | <a name="l00049"></a>00049 <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 ); |
| 43 | | <a name="l00051"></a><a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed">00051</a> vec* <a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed" title="access function">__w</a>(){<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>;} |
| 44 | | <a name="l00052"></a>00052 }; |
| 45 | | <a name="l00053"></a>00053 |
| 46 | | <a name="l00060"></a>00060 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 47 | | <a name="l00061"></a>00061 |
| 48 | | <a name="l00062"></a><a class="code" href="classbdm_1_1MPF.html">00062</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> { |
| 49 | | <a name="l00063"></a>00063 BM_T* Bms[10000]; |
| 50 | | <a name="l00064"></a>00064 |
| | 77 | <a name="l00044"></a>00044 <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>() ) {}; |
| | 78 | <a name="l00045"></a>00045 <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_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *obs0, <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> *epdf0, <span class="keywordtype">int</span> n0 ) : |
| | 79 | <a name="l00046"></a>00046 <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>() ) |
| | 80 | <a name="l00047"></a>00047 { <a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a> = par0; <a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a>=obs0; <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1eEmp.html#82320074a9b0ad7e1bb33a6e885b65d7" title="Set samples and weights.">set_parameters</a> ( ones(n0),epdf0 ); }; |
| | 81 | <a name="l00048"></a>00048 <span class="keywordtype">void</span> set_parameters ( mpdf *par0, mpdf *obs0, <span class="keywordtype">int</span> n0 ) |
| | 82 | <a name="l00049"></a>00049 { <a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a> = par0; <a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a>=obs0; <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>=n0; }; |
| | 83 | <a name="l00050"></a>00050 <span class="keywordtype">void</span> set_statistics (<span class="keyword">const</span> vec w0, epdf *epdf0){<a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_parameters ( w0,epdf0 );}; |
| | 84 | <a name="l00053"></a>00053 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e">set_est</a> ( <span class="keyword">const</span> epdf &epdf0 ); |
| | 85 | <a name="l00054"></a>00054 <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 ); |
| | 86 | <a name="l00056"></a><a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed">00056</a> vec* <a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed" title="access function">__w</a>() {<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>;} |
| | 87 | <a name="l00057"></a>00057 }; |
| | 88 | <a name="l00058"></a>00058 |
| | 89 | <a name="l00065"></a>00065 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 68 | | <a name="l00083"></a>00083 vec mean()<span class="keyword"> const </span>{ |
| 69 | | <a name="l00084"></a>00084 <span class="comment">// ugly</span> |
| 70 | | <a name="l00085"></a>00085 vec pom=zeros ( ( Coms ( 0 )->_rv() ).count() ); |
| 71 | | <a name="l00086"></a>00086 <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++ ) {pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i );} |
| 72 | | <a name="l00087"></a>00087 <span class="keywordflow">return</span> <a class="code" href="namespacebdm.html#b9016687c0e874ca5cdcf75ae28811aa" title="Concat two random variables.">concat</a> ( E.mean(),pom ); |
| 73 | | <a name="l00088"></a>00088 } |
| 74 | | <a name="l00089"></a>00089 vec variance()<span class="keyword"> const </span>{ |
| 75 | | <a name="l00090"></a>00090 <span class="comment">// ugly</span> |
| 76 | | <a name="l00091"></a>00091 vec pom=zeros ( ( Coms ( 0 )->_rv() ).count() ); |
| 77 | | <a name="l00092"></a>00092 vec pom2=zeros ( ( Coms ( 0 )->_rv() ).count() ); |
| 78 | | <a name="l00093"></a>00093 <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++ ) { |
| 79 | | <a name="l00094"></a>00094 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 80 | | <a name="l00095"></a>00095 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 );} |
| 81 | | <a name="l00096"></a>00096 <span class="keywordflow">return</span> <a class="code" href="namespacebdm.html#b9016687c0e874ca5cdcf75ae28811aa" title="Concat two random variables.">concat</a> ( E.variance(),pom2-pow(pom,2) ); |
| 82 | | <a name="l00097"></a>00097 } |
| 83 | | <a name="l00098"></a>00098 |
| 84 | | <a name="l00099"></a>00099 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;} |
| 85 | | <a name="l00100"></a>00100 |
| 86 | | <a name="l00101"></a>00101 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"not implemented"</span> ); <span class="keywordflow">return</span> 0.0;} |
| 87 | | <a name="l00102"></a>00102 }; |
| 88 | | <a name="l00103"></a>00103 |
| 89 | | <a name="l00105"></a>00105 mpfepdf jest; |
| 90 | | <a name="l00106"></a>00106 |
| 91 | | <a name="l00107"></a>00107 <span class="keyword">public</span>: |
| 92 | | <a name="l00109"></a><a class="code" href="classbdm_1_1MPF.html#e2a00c2399599c3613ab632fc36a1f79">00109</a> <a class="code" href="classbdm_1_1MPF.html#e2a00c2399599c3613ab632fc36a1f79" title="Default constructor.">MPF</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvlin, <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvpf, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs0, <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>, <span class="keyword">const</span> BM_T &BMcond0 ) : <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> ( rvpf ,par0,obs0,n ),jest ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>,rvlin ) { |
| 93 | | <a name="l00110"></a>00110 <span class="comment">//</span> |
| 94 | | <a name="l00111"></a>00111 <span class="comment">//TODO test if rv and BMcond.rv are compatible.</span> |
| 95 | | <a name="l00112"></a>00112 <span class="comment">// rv.add ( rvlin );</span> |
| 96 | | <a name="l00113"></a>00113 <span class="comment">//</span> |
| 97 | | <a name="l00114"></a>00114 |
| 98 | | <a name="l00115"></a>00115 <span class="keywordflow">if</span> ( n>10000 ) {it_error ( <span class="stringliteral">"increase 10000 here!"</span> );} |
| 99 | | <a name="l00116"></a>00116 |
| 100 | | <a name="l00117"></a>00117 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<n;i++ ) { |
| 101 | | <a name="l00118"></a>00118 Bms[i] = <span class="keyword">new</span> BM_T ( BMcond0 ); <span class="comment">//copy constructor</span> |
| 102 | | <a name="l00119"></a>00119 <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]->_epdf(); |
| 103 | | <a name="l00120"></a>00120 jest.set_elements ( i,1.0/n,&pom ); |
| 104 | | <a name="l00121"></a>00121 } |
| 105 | | <a name="l00122"></a>00122 }; |
| 106 | | <a name="l00123"></a>00123 |
| 107 | | <a name="l00124"></a>00124 ~<a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a>() { |
| 108 | | <a name="l00125"></a>00125 } |
| 109 | | <a name="l00126"></a>00126 |
| 110 | | <a name="l00127"></a>00127 <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 ); |
| 111 | | <a name="l00128"></a>00128 <span class="keyword">const</span> epdf& _epdf()<span class="keyword"> const </span>{<span class="keywordflow">return</span> jest;} |
| 112 | | <a name="l00129"></a>00129 <span class="keyword">const</span> epdf* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &jest;} <span class="comment">//Fixme: is it useful?</span> |
| 113 | | <a name="l00131"></a><a class="code" href="classbdm_1_1MPF.html#dcecdaf2acbbee51acf3018a70989a7e">00131</a> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#dcecdaf2acbbee51acf3018a70989a7e" title="Set postrior of rvc to samples from epdf0. Statistics of Bms are not re-computed!...">set_est</a> ( <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>& epdf0 ) { |
| 114 | | <a name="l00132"></a>00132 <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e" title="Set posterior density by sampling from epdf0.">PF::set_est</a> ( epdf0 ); <span class="comment">// sample params in condition</span> |
| 115 | | <a name="l00133"></a>00133 <span class="comment">// copy conditions to BMs</span> |
| 116 | | <a name="l00134"></a>00134 |
| 117 | | <a name="l00135"></a>00135 <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++ ) {Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) );} |
| 118 | | <a name="l00136"></a>00136 } |
| 119 | | <a name="l00137"></a>00137 |
| 120 | | <a name="l00139"></a><a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c">00139</a> <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#82b5a34d9ed0e78452f98d2ecbf1e93c" title="Access function.">_BM</a>(<span class="keywordtype">int</span> i){<span class="keywordflow">return</span> Bms[i];} |
| 121 | | <a name="l00140"></a>00140 }; |
| 122 | | <a name="l00141"></a>00141 |
| 123 | | <a name="l00142"></a>00142 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 124 | | <a name="l00143"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00143</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
| 125 | | <a name="l00144"></a>00144 <span class="keywordtype">int</span> i; |
| 126 | | <a name="l00145"></a>00145 vec lls ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 127 | | <a name="l00146"></a>00146 vec llsP ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 128 | | <a name="l00147"></a>00147 ivec ind; |
| 129 | | <a name="l00148"></a>00148 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
| 130 | | <a name="l00149"></a>00149 |
| 131 | | <a name="l00150"></a>00150 <span class="preprocessor"> #pragma omp parallel for</span> |
| 132 | | <a name="l00151"></a>00151 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>;i++ ) { |
| 133 | | <a name="l00152"></a>00152 <span class="comment">//generate new samples from paramater evolution model;</span> |
| 134 | | <a name="l00153"></a>00153 <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) = <a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" 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> ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 135 | | <a name="l00154"></a>00154 llsP ( i ) = <a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" title="Parameter evolution model.">par</a>.<a class="code" href="classbdm_1_1mpdf.html#05e843fd11c410a99dad2b88c55aca80">_e</a>()-><a class="code" href="classbdm_1_1epdf.html#a8e39e2ff5e5cf5471bc159530d3b2d3" title="Compute log-probability of argument val.">evallog</a>(<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>(i)); |
| 136 | | <a name="l00155"></a>00155 Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 137 | | <a name="l00156"></a>00156 Bms[i]->bayes ( dt ); |
| 138 | | <a name="l00157"></a>00157 lls ( i ) = Bms[i]->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| 139 | | <a name="l00158"></a>00158 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| 140 | | <a name="l00159"></a>00159 } |
| 141 | | <a name="l00160"></a>00160 |
| 142 | | <a name="l00161"></a>00161 <span class="keywordtype">double</span> sum_w=0.0; |
| 143 | | <a name="l00162"></a>00162 <span class="comment">// compute weights</span> |
| 144 | | <a name="l00163"></a>00163 <span class="preprocessor"> #pragma omp parallel for</span> |
| 145 | | <a name="l00164"></a>00164 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| 146 | | <a name="l00165"></a>00165 <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> |
| 147 | | <a name="l00166"></a>00166 sum_w+=<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>(i); |
| 148 | | <a name="l00167"></a>00167 } |
| 149 | | <a name="l00168"></a>00168 |
| 150 | | <a name="l00169"></a>00169 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
| 151 | | <a name="l00170"></a>00170 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
| 152 | | <a name="l00171"></a>00171 } <span class="keywordflow">else</span> { |
| 153 | | <a name="l00172"></a>00172 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
| 154 | | <a name="l00173"></a>00173 } |
| 155 | | <a name="l00174"></a>00174 |
| 156 | | <a name="l00175"></a>00175 |
| 157 | | <a name="l00176"></a>00176 <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> ); |
| 158 | | <a name="l00177"></a>00177 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
| 159 | | <a name="l00178"></a>00178 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>(); |
| 160 | | <a name="l00179"></a>00179 <span class="comment">// Resample Bms!</span> |
| | 106 | <a name="l00083"></a>00083 <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 ) |
| | 107 | <a name="l00084"></a>00084 {<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;}; |
| | 108 | <a name="l00085"></a>00085 |
| | 109 | <a name="l00086"></a>00086 vec mean()<span class="keyword"> const </span>{ |
| | 110 | <a name="l00087"></a>00087 <span class="comment">// ugly</span> |
| | 111 | <a name="l00088"></a>00088 vec pom=zeros ( Coms(0)->dimension() ); |
| | 112 | <a name="l00089"></a>00089 <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++ ) {pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i );} |
| | 113 | <a name="l00090"></a>00090 <span class="keywordflow">return</span> concat ( E.mean(),pom ); |
| | 114 | <a name="l00091"></a>00091 } |
| | 115 | <a name="l00092"></a>00092 vec variance()<span class="keyword"> const </span>{ |
| | 116 | <a name="l00093"></a>00093 <span class="comment">// ugly</span> |
| | 117 | <a name="l00094"></a>00094 vec pom=zeros ( Coms ( 0 )->dimension() ); |
| | 118 | <a name="l00095"></a>00095 vec pom2=zeros ( Coms ( 0 )->dimension() ); |
| | 119 | <a name="l00096"></a>00096 <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++ ) { |
| | 120 | <a name="l00097"></a>00097 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| | 121 | <a name="l00098"></a>00098 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 ); |
| | 122 | <a name="l00099"></a>00099 } |
| | 123 | <a name="l00100"></a>00100 <span class="keywordflow">return</span> concat ( E.variance(),pom2-pow ( pom,2 ) ); |
| | 124 | <a name="l00101"></a>00101 } |
| | 125 | <a name="l00102"></a>00102 |
| | 126 | <a name="l00103"></a>00103 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;} |
| | 127 | <a name="l00104"></a>00104 |
| | 128 | <a name="l00105"></a>00105 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"not implemented"</span> ); <span class="keywordflow">return</span> 0.0;} |
| | 129 | <a name="l00106"></a>00106 }; |
| | 130 | <a name="l00107"></a>00107 |
| | 131 | <a name="l00109"></a>00109 mpfepdf jest; |
| | 132 | <a name="l00110"></a>00110 |
| | 133 | <a name="l00111"></a>00111 <span class="keyword">public</span>: |
| | 134 | <a name="l00113"></a><a class="code" href="classbdm_1_1MPF.html#ca0e773df05fd70cf8ef3a7f1b3e42ef">00113</a> <a class="code" href="classbdm_1_1MPF.html#ca0e773df05fd70cf8ef3a7f1b3e42ef" title="Default constructor.">MPF</a> ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *obs0, <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>, <span class="keyword">const</span> BM_T &BMcond0 ) : <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> ) { |
| | 135 | <a name="l00114"></a>00114 PF::set_parameters(par0,obs0,n); |
| | 136 | <a name="l00115"></a>00115 <span class="comment">//</span> |
| | 137 | <a name="l00116"></a>00116 <span class="comment">//TODO test if rv and BMcond.rv are compatible.</span> |
| | 138 | <a name="l00117"></a>00117 <span class="comment">// rv.add ( rvlin );</span> |
| | 139 | <a name="l00118"></a>00118 <span class="comment">//</span> |
| | 140 | <a name="l00119"></a>00119 |
| | 141 | <a name="l00120"></a>00120 <span class="keywordflow">if</span> ( n>10000 ) {it_error ( <span class="stringliteral">"increase 10000 here!"</span> );} |
| | 142 | <a name="l00121"></a>00121 |
| | 143 | <a name="l00122"></a>00122 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<n;i++ ) { |
| | 144 | <a name="l00123"></a>00123 Bms[i] = <span class="keyword">new</span> BM_T ( BMcond0 ); <span class="comment">//copy constructor</span> |
| | 145 | <a name="l00124"></a>00124 <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(); |
| | 146 | <a name="l00125"></a>00125 jest.set_elements ( i,1.0/n,&pom ); |
| | 147 | <a name="l00126"></a>00126 } |
| | 148 | <a name="l00127"></a>00127 }; |
| | 149 | <a name="l00128"></a>00128 |
| | 150 | <a name="l00129"></a>00129 ~<a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a>() { |
| | 151 | <a name="l00130"></a>00130 } |
| | 152 | <a name="l00131"></a>00131 |
| | 153 | <a name="l00132"></a>00132 <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 ); |
| | 154 | <a name="l00133"></a>00133 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> jest;} |
| | 155 | <a name="l00134"></a>00134 <span class="keyword">const</span> epdf* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &jest;} <span class="comment">//Fixme: is it useful?</span> |
| | 156 | <a name="l00136"></a><a class="code" href="classbdm_1_1MPF.html#dcecdaf2acbbee51acf3018a70989a7e">00136</a> <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#dcecdaf2acbbee51acf3018a70989a7e" title="Set postrior of rvc to samples from epdf0. Statistics of Bms are not re-computed!...">set_est</a> ( <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>& epdf0 ) { |
| | 157 | <a name="l00137"></a>00137 <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e">PF::set_est</a> ( epdf0 ); <span class="comment">// sample params in condition</span> |
| | 158 | <a name="l00138"></a>00138 <span class="comment">// copy conditions to BMs</span> |
| | 159 | <a name="l00139"></a>00139 |
| | 160 | <a name="l00140"></a>00140 <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++ ) {Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) );} |
| | 161 | <a name="l00141"></a>00141 } |
| | 162 | <a name="l00142"></a>00142 |
| | 163 | <a name="l00144"></a><a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c">00144</a> <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#82b5a34d9ed0e78452f98d2ecbf1e93c" title="Access function.">_BM</a> ( <span class="keywordtype">int</span> i ) {<span class="keywordflow">return</span> Bms[i];} |
| | 164 | <a name="l00145"></a>00145 }; |
| | 165 | <a name="l00146"></a>00146 |
| | 166 | <a name="l00147"></a>00147 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| | 167 | <a name="l00148"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00148</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
| | 168 | <a name="l00149"></a>00149 <span class="keywordtype">int</span> i; |
| | 169 | <a name="l00150"></a>00150 vec lls ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| | 170 | <a name="l00151"></a>00151 vec llsP ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| | 171 | <a name="l00152"></a>00152 ivec ind; |
| | 172 | <a name="l00153"></a>00153 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
| | 173 | <a name="l00154"></a>00154 |
| | 174 | <a name="l00155"></a>00155 <span class="preprocessor">#pragma omp parallel for</span> |
| | 175 | <a name="l00156"></a>00156 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>;i++ ) { |
| | 176 | <a name="l00157"></a>00157 <span class="comment">//generate new samples from paramater evolution model;</span> |
| | 177 | <a name="l00158"></a>00158 <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> ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| | 178 | <a name="l00159"></a>00159 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#05e843fd11c410a99dad2b88c55aca80">_e</a>()-><a class="code" href="classbdm_1_1epdf.html#deab266d63c236c277538867d5c3f249" title="Compute log-probability of argument val.">evallog</a> ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| | 179 | <a name="l00160"></a>00160 Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| | 180 | <a name="l00161"></a>00161 Bms[i]->bayes ( dt ); |
| | 181 | <a name="l00162"></a>00162 lls ( i ) = Bms[i]->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| | 182 | <a name="l00163"></a>00163 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| | 183 | <a name="l00164"></a>00164 } |
| | 184 | <a name="l00165"></a>00165 |
| | 185 | <a name="l00166"></a>00166 <span class="keywordtype">double</span> sum_w=0.0; |
| | 186 | <a name="l00167"></a>00167 <span class="comment">// compute weights</span> |
| | 187 | <a name="l00168"></a>00168 <span class="preprocessor">#pragma omp parallel for</span> |
| | 188 | <a name="l00169"></a>00169 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| | 189 | <a name="l00170"></a>00170 <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> |
| | 190 | <a name="l00171"></a>00171 sum_w+=<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| | 191 | <a name="l00172"></a>00172 } |
| | 192 | <a name="l00173"></a>00173 |
| | 193 | <a name="l00174"></a>00174 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
| | 194 | <a name="l00175"></a>00175 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
| | 195 | <a name="l00176"></a>00176 } |
| | 196 | <a name="l00177"></a>00177 <span class="keywordflow">else</span> { |
| | 197 | <a name="l00178"></a>00178 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
| | 198 | <a name="l00179"></a>00179 } |
