| 76 | | <a name="l00041"></a>00041 <span class="keyword">public</span>: |
| 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; <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_n(<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>);}; |
| 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> |
| 90 | | <a name="l00066"></a>00066 |
| 91 | | <a name="l00067"></a><a class="code" href="classbdm_1_1MPF.html">00067</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> { |
| 92 | | <a name="l00068"></a>00068 BM_T* Bms[10000]; |
| 93 | | <a name="l00069"></a>00069 |
| 94 | | <a name="l00071"></a>00071 |
| 95 | | <a name="l00072"></a>00072 <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> { |
| 96 | | <a name="l00073"></a>00073 <span class="keyword">protected</span>: |
| 97 | | <a name="l00074"></a>00074 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
| 98 | | <a name="l00075"></a>00075 vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| 99 | | <a name="l00076"></a>00076 Array<const epdf*> Coms; |
| 100 | | <a name="l00077"></a>00077 <span class="keyword">public</span>: |
| 101 | | <a name="l00078"></a>00078 mpfepdf ( <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E0) : |
| 102 | | <a name="l00079"></a>00079 <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() ), |
| 103 | | <a name="l00080"></a>00080 Coms ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ) { |
| 104 | | <a name="l00081"></a>00081 }; |
| 105 | | <a name="l00082"></a>00082 <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 ) |
| 106 | | <a name="l00083"></a>00083 {<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;}; |
| 107 | | <a name="l00084"></a>00084 |
| 108 | | <a name="l00085"></a>00085 <span class="keywordtype">void</span> set_n(<span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>){E.set_n(n); Coms.set_length(n);} |
| 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 }; |
| | 76 | <a name="l00041"></a>00041 |
| | 77 | <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>; |
| | 78 | <a name="l00044"></a>00044 |
| | 79 | <a name="l00047"></a>00047 |
| | 80 | <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>; |
| | 81 | <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>; |
| | 82 | <a name="l00053"></a>00053 |
| | 83 | <a name="l00054"></a>00054 <span class="keyword">public</span>: |
| | 84 | <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 ) {<a class="code" href="classbdm_1_1BM.html#109c1a626a69031658e3a44e9e500cca" title="IDs of storages in loggers.">LIDs</a>.set_size ( 5 );}; |
| | 85 | <a name="l00058"></a>00058 <span class="comment">/* PF ( mpdf *par0, mpdf *obs0, epdf *epdf0, int n0 ) :</span> |
| | 86 | <a name="l00059"></a>00059 <span class="comment"> est ( ),_w ( est._w() ),_samples ( est._samples() ),opt_L_smp(false), opt_L_wei(false)</span> |
| | 87 | <a name="l00060"></a>00060 <span class="comment"> { set_parameters ( par0,obs0,n0 ); set_statistics ( ones ( n0 ),epdf0 ); };*/</span> |
| | 88 | <a name="l00061"></a>00061 <span class="keywordtype">void</span> set_parameters ( <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, RESAMPLING_METHOD rm=SYSTEMATIC ) |
| | 89 | <a name="l00062"></a>00062 { <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; <a class="code" href="classbdm_1_1PF.html#9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>= rm;}; |
| | 90 | <a name="l00063"></a>00063 <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_statistics ( w0,epdf0 );}; |
| | 91 | <a name="l00066"></a>00066 <span class="comment">// void set_est ( const epdf &epdf0 );</span> |
| | 92 | <a name="l00067"></a><a class="code" href="classbdm_1_1PF.html#bf104b869b5df8dd4a14bbe430d40488">00067</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 ) { |
| | 93 | <a name="l00068"></a>00068 <a class="code" href="classbdm_1_1BM.html#224dd68a83c1472b43163763fa93c477" title="Set boolean options from a string.">BM::set_options</a>(opt); |
| | 94 | <a name="l00069"></a>00069 <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 ); |
| | 95 | <a name="l00070"></a>00070 <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 ); |
| | 96 | <a name="l00071"></a>00071 } |
| | 97 | <a name="l00072"></a>00072 <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 ); |
| | 98 | <a name="l00074"></a><a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed">00074</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>;} |
| | 99 | <a name="l00075"></a>00075 }; |
| | 100 | <a name="l00076"></a>00076 |
| | 101 | <a name="l00083"></a>00083 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| | 102 | <a name="l00084"></a><a class="code" href="classbdm_1_1MPF.html">00084</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> { |
| | 103 | <a name="l00085"></a>00085 Array<BM_T*> BMs; |
| | 104 | <a name="l00086"></a>00086 |
| | 105 | <a name="l00088"></a>00088 |
| | 106 | <a name="l00089"></a>00089 <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> { |
| | 107 | <a name="l00090"></a>00090 <span class="keyword">protected</span>: |
| | 108 | <a name="l00091"></a>00091 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
| | 109 | <a name="l00092"></a>00092 vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| | 110 | <a name="l00093"></a>00093 Array<const epdf*> Coms; |
| | 111 | <a name="l00094"></a>00094 <span class="keyword">public</span>: |
| | 112 | <a name="l00095"></a>00095 mpfepdf ( <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E0 ) : |
| | 113 | <a name="l00096"></a>00096 <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() ), |
| | 114 | <a name="l00097"></a>00097 Coms ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ) { |
| | 115 | <a name="l00098"></a>00098 }; |
| | 116 | <a name="l00100"></a>00100 <span class="keywordtype">void</span> read_statistics ( Array<BM_T*> &A ) { |
| | 117 | <a name="l00101"></a>00101 dim = E.dimension() +A ( 0 )->posterior().dimension(); |
| | 118 | <a name="l00102"></a>00102 <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++ ) {Coms ( i ) = A ( i )->_e();} |
| | 119 | <a name="l00103"></a>00103 } |
| | 120 | <a name="l00105"></a>00105 <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 ) |
| | 121 | <a name="l00106"></a>00106 {<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;}; |
| 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 jest.set_n(n); |
| 137 | | <a name="l00116"></a>00116 <span class="comment">//</span> |
| 138 | | <a name="l00117"></a>00117 <span class="comment">//TODO test if rv and BMcond.rv are compatible.</span> |
| 139 | | <a name="l00118"></a>00118 <span class="comment">// rv.add ( rvlin );</span> |
| 140 | | <a name="l00119"></a>00119 <span class="comment">//</span> |
| 141 | | <a name="l00120"></a>00120 |
| 142 | | <a name="l00121"></a>00121 <span class="keywordflow">if</span> ( n>10000 ) {it_error ( <span class="stringliteral">"increase 10000 here!"</span> );} |
| 143 | | <a name="l00122"></a>00122 |
| 144 | | <a name="l00123"></a>00123 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<n;i++ ) { |
| 145 | | <a name="l00124"></a>00124 Bms[i] = <span class="keyword">new</span> BM_T ( BMcond0 ); <span class="comment">//copy constructor</span> |
| 146 | | <a name="l00125"></a>00125 <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(); |
| 147 | | <a name="l00126"></a>00126 jest.set_elements ( i,1.0/n,&pom ); |
| | 123 | <a name="l00108"></a>00108 <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> ) { |
| | 124 | <a name="l00109"></a>00109 E.set_parameters ( n, <span class="keyword">false</span> ); |
| | 125 | <a name="l00110"></a>00110 Coms.set_length ( n ); |
| | 126 | <a name="l00111"></a>00111 } |
| | 127 | <a name="l00112"></a>00112 vec mean()<span class="keyword"> const </span>{ |
| | 128 | <a name="l00113"></a>00113 <span class="comment">// ugly</span> |
| | 129 | <a name="l00114"></a>00114 vec pom=zeros ( Coms ( 0 )->dimension() ); |
| | 130 | <a name="l00115"></a>00115 <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 );} |
| | 131 | <a name="l00116"></a>00116 <span class="keywordflow">return</span> concat ( E.mean(),pom ); |
| | 132 | <a name="l00117"></a>00117 } |
| | 133 | <a name="l00118"></a>00118 vec variance()<span class="keyword"> const </span>{ |
| | 134 | <a name="l00119"></a>00119 <span class="comment">// ugly</span> |
| | 135 | <a name="l00120"></a>00120 vec pom=zeros ( Coms ( 0 )->dimension() ); |
| | 136 | <a name="l00121"></a>00121 vec pom2=zeros ( Coms ( 0 )->dimension() ); |
| | 137 | <a name="l00122"></a>00122 <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++ ) { |
| | 138 | <a name="l00123"></a>00123 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| | 139 | <a name="l00124"></a>00124 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 ); |
| | 140 | <a name="l00125"></a>00125 } |
| | 141 | <a name="l00126"></a>00126 <span class="keywordflow">return</span> concat ( E.variance(),pom2-pow ( pom,2 ) ); |
| 149 | | <a name="l00128"></a>00128 }; |
| 150 | | <a name="l00129"></a>00129 |
| 151 | | <a name="l00130"></a>00130 ~<a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a>() { |
| 152 | | <a name="l00131"></a>00131 } |
| 153 | | <a name="l00132"></a>00132 |
| 154 | | <a name="l00133"></a>00133 <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 ); |
| 155 | | <a name="l00134"></a>00134 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> jest;} |
| 156 | | <a name="l00135"></a>00135 <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> |
| 157 | | <a name="l00137"></a><a class="code" href="classbdm_1_1MPF.html#dcecdaf2acbbee51acf3018a70989a7e">00137</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 ) { |
| 158 | | <a name="l00138"></a>00138 <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e">PF::set_est</a> ( epdf0 ); <span class="comment">// sample params in condition</span> |
| 159 | | <a name="l00139"></a>00139 <span class="comment">// copy conditions to BMs</span> |
| 160 | | <a name="l00140"></a>00140 |
| 161 | | <a name="l00141"></a>00141 <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 ) );} |
| 162 | | <a name="l00142"></a>00142 } |
| 163 | | <a name="l00143"></a>00143 |
| 164 | | <a name="l00145"></a><a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c">00145</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];} |
| 165 | | <a name="l00146"></a>00146 }; |
| 166 | | <a name="l00147"></a>00147 |
| 167 | | <a name="l00148"></a>00148 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 168 | | <a name="l00149"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00149</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 ) { |
| 169 | | <a name="l00150"></a>00150 <span class="keywordtype">int</span> i; |
| 170 | | <a name="l00151"></a>00151 vec lls ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 171 | | <a name="l00152"></a>00152 vec llsP ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 172 | | <a name="l00153"></a>00153 ivec ind; |
| 173 | | <a name="l00154"></a>00154 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
| 174 | | <a name="l00155"></a>00155 |
| 175 | | <a name="l00156"></a>00156 <span class="preprocessor">#pragma omp parallel for</span> |
| 176 | | <a name="l00157"></a>00157 <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++ ) { |
| 177 | | <a name="l00158"></a>00158 <span class="comment">//generate new samples from paramater evolution model;</span> |
| 178 | | <a name="l00159"></a>00159 <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 ) ); |
| 179 | | <a name="l00160"></a>00160 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 ) ); |
| 180 | | <a name="l00161"></a>00161 Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 181 | | <a name="l00162"></a>00162 Bms[i]->bayes ( dt ); |
| 182 | | <a name="l00163"></a>00163 lls ( i ) = Bms[i]->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| 183 | | <a name="l00164"></a>00164 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| 184 | | <a name="l00165"></a>00165 } |
| 185 | | <a name="l00166"></a>00166 |
| 186 | | <a name="l00167"></a>00167 <span class="keywordtype">double</span> sum_w=0.0; |
| 187 | | <a name="l00168"></a>00168 <span class="comment">// compute weights</span> |
| 188 | | <a name="l00169"></a>00169 <span class="preprocessor">#pragma omp parallel for</span> |
| 189 | | <a name="l00170"></a>00170 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| 190 | | <a name="l00171"></a>00171 <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> |
| 191 | | <a name="l00172"></a>00172 sum_w+=<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 192 | | <a name="l00173"></a>00173 } |
| 193 | | <a name="l00174"></a>00174 |
| 194 | | <a name="l00175"></a>00175 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
| 195 | | <a name="l00176"></a>00176 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
| 196 | | <a name="l00177"></a>00177 } |
| 197 | | <a name="l00178"></a>00178 <span class="keywordflow">else</span> { |
| 198 | | <a name="l00179"></a>00179 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
| 199 | | <a name="l00180"></a>00180 } |
| 200 | | <a name="l00181"></a>00181 |
| | 143 | <a name="l00128"></a>00128 <span class="keywordtype">void</span> qbounds ( vec &lb, vec &ub, <span class="keywordtype">double</span> perc=0.95 )<span class="keyword"> const </span>{ |
| | 144 | <a name="l00129"></a>00129 <span class="comment">//bounds on particles</span> |
| | 145 | <a name="l00130"></a>00130 vec lbp; |
| | 146 | <a name="l00131"></a>00131 vec ubp; |
| | 147 | <a name="l00132"></a>00132 E.qbounds ( lbp,ubp ); |
| | 148 | <a name="l00133"></a>00133 |
| | 149 | <a name="l00134"></a>00134 <span class="comment">//bounds on Components</span> |
| | 150 | <a name="l00135"></a>00135 <span class="keywordtype">int</span> dimC=Coms ( 0 )->dimension(); |
| | 151 | <a name="l00136"></a>00136 <span class="keywordtype">int</span> j; |
| | 152 | <a name="l00137"></a>00137 <span class="comment">// temporary</span> |
| | 153 | <a name="l00138"></a>00138 vec lbc(dimC); |
| | 154 | <a name="l00139"></a>00139 vec ubc(dimC); |
| | 155 | <a name="l00140"></a>00140 <span class="comment">// minima and maxima</span> |
| | 156 | <a name="l00141"></a>00141 vec Lbc(dimC); |
| | 157 | <a name="l00142"></a>00142 vec Ubc(dimC); |
| | 158 | <a name="l00143"></a>00143 Lbc = std::numeric_limits<double>::infinity(); |
| | 159 | <a name="l00144"></a>00144 Ubc = -std::numeric_limits<double>::infinity(); |
| | 160 | <a name="l00145"></a>00145 |
| | 161 | <a name="l00146"></a>00146 <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++ ) { |
| | 162 | <a name="l00147"></a>00147 <span class="comment">// check Coms</span> |
| | 163 | <a name="l00148"></a>00148 Coms ( i )->qbounds ( lbc,ubc ); |
| | 164 | <a name="l00149"></a>00149 <span class="keywordflow">for</span> ( j=0;j<dimC; j++ ) { |
| | 165 | <a name="l00150"></a>00150 <span class="keywordflow">if</span> ( lbc ( j ) <Lbc ( j ) ) {Lbc ( j ) =lbc ( j );} |
| | 166 | <a name="l00151"></a>00151 <span class="keywordflow">if</span> ( ubc ( j ) >Ubc ( j ) ) {Ubc ( j ) =ubc ( j );} |
| | 167 | <a name="l00152"></a>00152 } |
| | 168 | <a name="l00153"></a>00153 } |
| | 169 | <a name="l00154"></a>00154 lb=concat(lbp,Lbc); |
| | 170 | <a name="l00155"></a>00155 ub=concat(ubp,Ubc); |
| | 171 | <a name="l00156"></a>00156 } |
| | 172 | <a name="l00157"></a>00157 |
| | 173 | <a name="l00158"></a>00158 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;} |
| | 174 | <a name="l00159"></a>00159 |
| | 175 | <a name="l00160"></a>00160 <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;} |
| | 176 | <a name="l00161"></a>00161 }; |
| | 177 | <a name="l00162"></a>00162 |
| | 178 | <a name="l00164"></a>00164 mpfepdf jest; |
| | 179 | <a name="l00165"></a>00165 |
| | 180 | <a name="l00167"></a>00167 <span class="keywordtype">bool</span> opt_L_mea; |
| | 181 | <a name="l00168"></a>00168 |
| | 182 | <a name="l00169"></a>00169 <span class="keyword">public</span>: |
| | 183 | <a name="l00171"></a><a class="code" href="classbdm_1_1MPF.html#0068e7ca53d90fa5911eb31a0d657f26">00171</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> ) {}; |
| | 184 | <a name="l00172"></a>00172 <span class="keywordtype">void</span> set_parameters ( <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, RESAMPLING_METHOD rm=SYSTEMATIC ) { |
| | 185 | <a name="l00173"></a>00173 PF::set_parameters ( par0, obs0, n0, rm ); |
| | 186 | <a name="l00174"></a>00174 jest.set_parameters ( n0 );<span class="comment">//duplication of rm</span> |
| | 187 | <a name="l00175"></a>00175 BMs.set_length ( n0 ); |
| | 188 | <a name="l00176"></a>00176 } |
| | 189 | <a name="l00177"></a>00177 <span class="keywordtype">void</span> set_statistics ( epdf *epdf0, <span class="keyword">const</span> BM_T* BMcond0 ) { |
| | 190 | <a name="l00178"></a>00178 |
| | 191 | <a name="l00179"></a>00179 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 ); |
| | 192 | <a name="l00180"></a>00180 <span class="comment">// copy</span> |
| | 193 | <a name="l00181"></a>00181 <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 ) = <span class="keyword">new</span> BM_T ( *BMcond0 ); BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) );} |
| 202 | | <a name="l00183"></a>00183 <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> ); |
| 203 | | <a name="l00184"></a>00184 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
| 204 | | <a name="l00185"></a>00185 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>(); |
| 205 | | <a name="l00186"></a>00186 <span class="comment">// Resample Bms!</span> |
| 206 | | <a name="l00187"></a>00187 |
| 207 | | <a name="l00188"></a>00188 <span class="preprocessor">#pragma omp parallel for</span> |
| 208 | | <a name="l00189"></a>00189 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| 209 | | <a name="l00190"></a>00190 <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span> |
| 210 | | <a name="l00191"></a>00191 <span class="comment">//fixme this would require new assignment operator</span> |
| 211 | | <a name="l00192"></a>00192 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
| 212 | | <a name="l00193"></a>00193 |
| 213 | | <a name="l00194"></a>00194 <span class="comment">// poor-man's solution: replicate constructor here</span> |
| 214 | | <a name="l00195"></a>00195 <span class="comment">// copied from MPF::MPF</span> |
| 215 | | <a name="l00196"></a>00196 <span class="keyword">delete</span> Bms[i]; |
| 216 | | <a name="l00197"></a>00197 Bms[i] = <span class="keyword">new</span> BM_T ( *Bms[ind ( i ) ] ); <span class="comment">//copy constructor</span> |
| 217 | | <a name="l00198"></a>00198 <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(); |
| 218 | | <a name="l00199"></a>00199 jest.set_elements ( i,1.0/n,&pom ); |
| 219 | | <a name="l00200"></a>00200 } |
| 220 | | <a name="l00201"></a>00201 }; |
| 221 | | <a name="l00202"></a>00202 cout << <span class="charliteral">'.'</span>; |
| 222 | | <a name="l00203"></a>00203 } |
| 223 | | <a name="l00204"></a>00204 } |
| | 195 | <a name="l00183"></a>00183 jest.read_statistics ( BMs ); |
| | 196 | <a name="l00184"></a>00184 <span class="comment">//options</span> |
| | 197 | <a name="l00185"></a>00185 }; |
| | 198 | <a name="l00186"></a>00186 |
| | 199 | <a name="l00187"></a>00187 <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 ); |
| | 200 | <a name="l00188"></a>00188 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> jest;} |
| | 201 | <a name="l00189"></a>00189 <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> |
| | 202 | <a name="l00191"></a>00191 <span class="comment"></span> <span class="comment">/* void set_est ( const epdf& epdf0 ) {</span> |
| | 203 | <a name="l00192"></a>00192 <span class="comment"> PF::set_est ( epdf0 ); // sample params in condition</span> |
| | 204 | <a name="l00193"></a>00193 <span class="comment"> // copy conditions to BMs</span> |
| | 205 | <a name="l00194"></a>00194 <span class="comment"></span> |
| | 206 | <a name="l00195"></a>00195 <span class="comment"> for ( int i=0;i<n;i++ ) {BMs(i)->condition ( _samples ( i ) );}</span> |
| | 207 | <a name="l00196"></a>00196 <span class="comment"> }*/</span> |
| | 208 | <a name="l00197"></a><a class="code" href="classbdm_1_1MPF.html#2e95498dec734088ab9f4878ff404144">00197</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 ) { |
| | 209 | <a name="l00198"></a>00198 <a class="code" href="classbdm_1_1PF.html#bf104b869b5df8dd4a14bbe430d40488">PF::set_options</a> ( opt ); |
| | 210 | <a name="l00199"></a>00199 opt_L_mea = ( opt.find ( <span class="stringliteral">"logmeans"</span> ) !=string::npos ); |
| | 211 | <a name="l00200"></a>00200 } |
| | 212 | <a name="l00201"></a>00201 |
| | 213 | <a name="l00203"></a><a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c">00203</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 );} |
| | 214 | <a name="l00204"></a>00204 }; |
| 225 | | <a name="l00206"></a>00206 } |
| 226 | | <a name="l00207"></a>00207 <span class="preprocessor">#endif // KF_H</span> |
| 227 | | <a name="l00208"></a>00208 <span class="preprocessor"></span> |
| 228 | | <a name="l00209"></a>00209 |
| | 216 | <a name="l00206"></a>00206 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| | 217 | <a name="l00207"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00207</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 ) { |
| | 218 | <a name="l00208"></a>00208 <span class="keywordtype">int</span> i; |
| | 219 | <a name="l00209"></a>00209 vec lls ( n ); |
| | 220 | <a name="l00210"></a>00210 vec llsP ( n ); |
| | 221 | <a name="l00211"></a>00211 ivec ind; |
| | 222 | <a name="l00212"></a>00212 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
| | 223 | <a name="l00213"></a>00213 |
| | 224 | <a name="l00214"></a>00214 <span class="preprocessor">#pragma omp parallel for</span> |
| | 225 | <a name="l00215"></a>00215 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| | 226 | <a name="l00216"></a>00216 <span class="comment">//generate new samples from paramater evolution model;</span> |
| | 227 | <a name="l00217"></a>00217 <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 ) ); |
| | 228 | <a name="l00218"></a>00218 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 ) ); |
| | 229 | <a name="l00219"></a>00219 BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| | 230 | <a name="l00220"></a>00220 BMs ( i )->bayes ( dt ); |
| | 231 | <a name="l00221"></a>00221 lls ( i ) = BMs ( i )->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| | 232 | <a name="l00222"></a>00222 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| | 233 | <a name="l00223"></a>00223 } |
| | 234 | <a name="l00224"></a>00224 |
| | 235 | <a name="l00225"></a>00225 <span class="keywordtype">double</span> sum_w=0.0; |
| | 236 | <a name="l00226"></a>00226 <span class="comment">// compute weights</span> |
| | 237 | <a name="l00227"></a>00227 <span class="preprocessor">#pragma omp parallel for</span> |
| | 238 | <a name="l00228"></a>00228 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| | 239 | <a name="l00229"></a>00229 <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> |
| | 240 | <a name="l00230"></a>00230 sum_w+=<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| | 241 | <a name="l00231"></a>00231 } |
| | 242 | <a name="l00232"></a>00232 |
| | 243 | <a name="l00233"></a>00233 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
| | 244 | <a name="l00234"></a>00234 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
| | 245 | <a name="l00235"></a>00235 } |
| | 246 | <a name="l00236"></a>00236 <span class="keywordflow">else</span> { |
| | 247 | <a name="l00237"></a>00237 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
| | 248 | <a name="l00238"></a>00238 } |
| | 249 | <a name="l00239"></a>00239 |
| | 250 | <a name="l00240"></a>00240 |
| | 251 | <a name="l00241"></a>00241 <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> ); |
| | 252 | <a name="l00242"></a>00242 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
| | 253 | <a name="l00243"></a>00243 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> ); |
| | 254 | <a name="l00244"></a>00244 <span class="comment">// Resample Bms!</span> |
| | 255 | <a name="l00245"></a>00245 |
| | 256 | <a name="l00246"></a>00246 <span class="preprocessor">#pragma omp parallel for</span> |
| | 257 | <a name="l00247"></a>00247 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| | 258 | <a name="l00248"></a>00248 <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span> |
| | 259 | <a name="l00249"></a>00249 <span class="comment">//fixme this would require new assignment operator</span> |
| | 260 | <a name="l00250"></a>00250 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
| | 261 | <a name="l00251"></a>00251 |
| | 262 | <a name="l00252"></a>00252 <span class="comment">// poor-man's solution: replicate constructor here</span> |
| | 263 | <a name="l00253"></a>00253 <span class="comment">// copied from MPF::MPF</span> |
| | 264 | <a name="l00254"></a>00254 <span class="keyword">delete</span> BMs ( i ); |
| | 265 | <a name="l00255"></a>00255 BMs ( i ) = <span class="keyword">new</span> BM_T ( *BMs ( ind ( i ) ) ); <span class="comment">//copy constructor</span> |
| | 266 | <a name="l00256"></a>00256 <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(); |
| | 267 | <a name="l00257"></a>00257 jest.set_elements ( i,1.0/n,&pom ); |
| | 268 | <a name="l00258"></a>00258 } |
| | 269 | <a name="l00259"></a>00259 }; |
| | 270 | <a name="l00260"></a>00260 cout << <span class="charliteral">'.'</span>; |
| | 271 | <a name="l00261"></a>00261 } |
| | 272 | <a name="l00262"></a>00262 } |
| | 273 | <a name="l00263"></a>00263 |
| | 274 | <a name="l00264"></a>00264 } |
| | 275 | <a name="l00265"></a>00265 <span class="preprocessor">#endif // KF_H</span> |
| | 276 | <a name="l00266"></a>00266 <span class="preprocessor"></span> |
| | 277 | <a name="l00267"></a>00267 |
