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[261]59<h1>libPF.h</h1><a href="libPF_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001
[8]60<a name="l00013"></a>00013 <span class="preprocessor">#ifndef PF_H</span>
61<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define PF_H</span>
62<a name="l00015"></a>00015 <span class="preprocessor"></span>
[261]63<a name="l00016"></a>00016
[32]64<a name="l00017"></a>00017 <span class="preprocessor">#include "../stat/libEF.h"</span>
[261]65<a name="l00018"></a>00018
[271]66<a name="l00019"></a>00019 <span class="keyword">namespace </span>bdm {
[261]67<a name="l00020"></a>00020
[269]68<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> {
[261]69<a name="l00028"></a>00028 <span class="keyword">protected</span>:
70<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>;
71<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>;
72<a name="l00034"></a><a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3">00034</a>         vec &amp;<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>;
73<a name="l00036"></a><a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1">00036</a>         Array&lt;vec&gt; &amp;<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>;
[271]74<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 some dependencies.">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>;
75<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 some dependencies.">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#d6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a>;
[261]76<a name="l00041"></a>00041 <span class="keyword">public</span>:
[271]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 &amp;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 &amp;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> &amp;<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>&lt;<span class="keyword">class</span> BM_T&gt;
[261]90<a name="l00066"></a>00066
[271]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> &amp;E;
98<a name="l00075"></a>00075                 vec &amp;<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>;
99<a name="l00076"></a>00076                 Array&lt;const epdf*&gt; 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> &amp;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                 };
[261]105<a name="l00082"></a>00082
[271]106<a name="l00083"></a>00083                 <span class="keywordtype">void</span> set_elements ( <span class="keywordtype">int</span> &amp;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)-&gt;dimension() );
112<a name="l00089"></a>00089                         <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i&lt;<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) {pom += Coms ( i )-&gt;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 )-&gt;dimension() );
118<a name="l00095"></a>00095                         vec pom2=zeros (  Coms ( 0 )-&gt;dimension() );
119<a name="l00096"></a>00096                         <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i&lt;<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 )-&gt;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 )-&gt;variance() + pow ( Coms ( i )-&gt;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 &amp;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 &amp;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&gt;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&lt;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>&amp; pom=Bms[i]-&gt;posterior();
146<a name="l00125"></a>00125                         jest.set_elements ( i,1.0/n,&amp;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 &amp;dt );
154<a name="l00133"></a>00133         <span class="keyword">const</span> epdf&amp; 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> &amp;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>&amp; 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&lt;<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>;i++ ) {Bms[i]-&gt;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>&lt;<span class="keyword">class</span> BM_T&gt;
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&lt;BM_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;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&lt;double&gt;::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&lt;<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>-&gt;<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>-&gt;<a class="code" href="classbdm_1_1mpdf.html#05e843fd11c410a99dad2b88c55aca80">_e</a>()-&gt;<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]-&gt;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]-&gt;bayes ( dt );
181<a name="l00162"></a>00162                 lls ( i ) = Bms[i]-&gt;_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 ) &gt;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&lt;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  &gt;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&lt;&lt;<span class="stringliteral">"sum(w)==0"</span>&lt;&lt;endl;
198<a name="l00179"></a>00179         }
[269]199<a name="l00180"></a>00180
[271]200<a name="l00181"></a>00181
201<a name="l00182"></a>00182         <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> );
202<a name="l00183"></a>00183         <span class="keywordflow">if</span> ( eff &lt; ( 0.3*n ) ) {
203<a name="l00184"></a>00184                 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>();
204<a name="l00185"></a>00185                 <span class="comment">// Resample Bms!</span>
[269]205<a name="l00186"></a>00186
[271]206<a name="l00187"></a>00187 <span class="preprocessor">#pragma omp parallel for</span>
207<a name="l00188"></a>00188 <span class="preprocessor"></span>                <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) {
208<a name="l00189"></a>00189                         <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span>
209<a name="l00190"></a>00190                                 <span class="comment">//fixme this would require new assignment operator</span>
210<a name="l00191"></a>00191                                 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span>
211<a name="l00192"></a>00192
212<a name="l00193"></a>00193                                 <span class="comment">// poor-man's solution: replicate constructor here</span>
213<a name="l00194"></a>00194                                 <span class="comment">// copied from MPF::MPF</span>
214<a name="l00195"></a>00195                                 <span class="keyword">delete</span> Bms[i];
215<a name="l00196"></a>00196                                 Bms[i] = <span class="keyword">new</span> BM_T ( *Bms[ind ( i ) ] ); <span class="comment">//copy constructor</span>
216<a name="l00197"></a>00197                                 <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>&amp; pom=Bms[i]-&gt;posterior();
217<a name="l00198"></a>00198                                 jest.set_elements ( i,1.0/n,&amp;pom );
218<a name="l00199"></a>00199                         }
219<a name="l00200"></a>00200                 };
220<a name="l00201"></a>00201                 cout &lt;&lt; <span class="charliteral">'.'</span>;
221<a name="l00202"></a>00202         }
222<a name="l00203"></a>00203 }
223<a name="l00204"></a>00204
224<a name="l00205"></a>00205 }
225<a name="l00206"></a>00206 <span class="preprocessor">#endif // KF_H</span>
226<a name="l00207"></a>00207 <span class="preprocessor"></span>
227<a name="l00208"></a>00208
[91]228</pre></div></div>
[275]229<hr size="1"><address style="text-align: right;"><small>Generated on Mon Feb 16 10:06:24 2009 for mixpp by&nbsp;
[8]230<a href="http://www.doxygen.org/index.html">
[139]231<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
[8]232</body>
233</html>
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