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17<h1>work/mixpp/bdm/estim/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
18<a name="l00013"></a>00013 <span class="preprocessor">#ifndef PF_H</span>
19<a name="l00014"></a>00014 <span class="preprocessor"></span><span class="preprocessor">#define PF_H</span>
20<a name="l00015"></a>00015 <span class="preprocessor"></span>
21<a name="l00016"></a>00016 <span class="preprocessor">#include &lt;itpp/itbase.h&gt;</span>
22<a name="l00017"></a>00017 <span class="preprocessor">#include "../stat/libEF.h"</span>
23<a name="l00018"></a>00018 <span class="preprocessor">#include "../math/libDC.h"</span>
24<a name="l00019"></a>00019
25<a name="l00020"></a>00020 <span class="keyword">using namespace </span>itpp;
26<a name="l00021"></a>00021
27<a name="l00022"></a>00022 <span class="comment">//UGLY HACK</span>
28<a name="l00023"></a>00023 <span class="keyword">extern</span> <span class="keywordtype">double</span> PF_SSAT;<span class="comment">//used for StrSim:06 test... if length&gt;0 the value is written.</span>
29<a name="l00024"></a>00024
30<a name="l00031"></a><a class="code" href="classPF.html">00031</a> <span class="keyword">class </span><a class="code" href="classPF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> : <span class="keyword">public</span> <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> {
31<a name="l00032"></a>00032 <span class="keyword">protected</span>:
32<a name="l00034"></a><a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280">00034</a>         <span class="keywordtype">int</span> <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;
33<a name="l00036"></a><a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b">00036</a>         <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> <a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a>;
34<a name="l00038"></a><a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a">00038</a>         vec &amp;<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>;
35<a name="l00040"></a><a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5">00040</a>         Array&lt;vec&gt; &amp;<a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a>;
36<a name="l00042"></a><a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09">00042</a>         <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;<a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09" title="Parameter evolution model.">par</a>;
37<a name="l00044"></a><a class="code" href="classPF.html#dd0a687a4515333d6809147335854e77">00044</a>         <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;<a class="code" href="classPF.html#dd0a687a4515333d6809147335854e77" title="Observation model.">obs</a>;
38<a name="l00045"></a>00045 <span class="keyword">public</span>:
39<a name="l00047"></a><a class="code" href="classPF.html#e99f0d866721405dd281e315ecb690aa">00047</a>         <a class="code" href="classPF.html#e99f0d866721405dd281e315ecb690aa" title="Default constructor.">PF</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rv0, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;par0,  <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;obs0, <span class="keywordtype">int</span> n0 ) :<a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( rv0 ),
40<a name="l00048"></a>00048                         <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> ( n0 ),<a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a> ( rv0,<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> ),<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( <a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a>.<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>() ),<a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( <a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a>.<a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a>() ),
41<a name="l00049"></a>00049                         <a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09" title="Parameter evolution model.">par</a> ( par0 ), <a class="code" href="classPF.html#dd0a687a4515333d6809147335854e77" title="Observation model.">obs</a> ( obs0 ) {};
42<a name="l00050"></a>00050
43<a name="l00052"></a>00052         <span class="keywordtype">void</span> <a class="code" href="classPF.html#04d38fbcc0348b558212f530d9ec183e" title="Set posterior density by sampling from epdf0.">set_est</a> ( <span class="keyword">const</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> &amp;epdf0 );
44<a name="l00053"></a>00053         <span class="keywordtype">void</span> <a class="code" href="classPF.html#64f636bbd63bea9efd778214e6b631d3" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt );
45<a name="l00054"></a>00054 };
46<a name="l00055"></a>00055
47<a name="l00062"></a>00062 <span class="keyword">template</span>&lt;<span class="keyword">class</span> BM_T&gt;
48<a name="l00063"></a>00063
49<a name="l00064"></a><a class="code" href="classMPF.html">00064</a> <span class="keyword">class </span><a class="code" href="classMPF.html" title="Marginalized Particle filter.">MPF</a> : <span class="keyword">public</span> <a class="code" href="classPF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> {
50<a name="l00065"></a>00065         BM_T* Bms[10000];
51<a name="l00066"></a>00066
52<a name="l00068"></a>00068
53<a name="l00069"></a>00069 <span class="keyword">class </span>mpfepdf : <span class="keyword">public</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>  {
54<a name="l00070"></a>00070         <span class="keyword">protected</span>:
55<a name="l00071"></a>00071                 <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> &amp;E;
56<a name="l00072"></a>00072                 vec &amp;<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>;
57<a name="l00073"></a>00073                 Array&lt;epdf*&gt; Coms;
58<a name="l00074"></a>00074         <span class="keyword">public</span>:
59<a name="l00075"></a>00075                 mpfepdf ( <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> &amp;E0, <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rvc ) :
60<a name="l00076"></a>00076                                 <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a>( ) ), E ( E0 ),  <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( E._w() ),
61<a name="l00077"></a>00077                                 Coms ( <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>.length() ) {
62<a name="l00078"></a>00078                         <a class="code" href="classBM.html#af00f0612fabe66241dd507188cdbf88" title="Random variable of the posterior.">rv</a>.<a class="code" href="classRV.html#4fc941a5ebc9f82aa372f54f2e02dab2" title="Add (concat) another variable to the current one.">add</a> ( E._rv() );
63<a name="l00079"></a>00079                         <a class="code" href="classBM.html#af00f0612fabe66241dd507188cdbf88" title="Random variable of the posterior.">rv</a>.<a class="code" href="classRV.html#4fc941a5ebc9f82aa372f54f2e02dab2" title="Add (concat) another variable to the current one.">add</a> ( rvc );
64<a name="l00080"></a>00080                 };
65<a name="l00081"></a>00081
66<a name="l00082"></a>00082                 <span class="keywordtype">void</span> set_elements ( <span class="keywordtype">int</span> &amp;i, <span class="keywordtype">double</span> wi, <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* ep )
67<a name="l00083"></a>00083                 {<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;};
68<a name="l00084"></a>00084
69<a name="l00085"></a>00085                 vec mean()<span class="keyword"> const </span>{
70<a name="l00086"></a>00086                         <span class="comment">// ugly</span>
71<a name="l00087"></a>00087                         vec pom=zeros ( ( Coms ( 0 )-&gt;<a class="code" href="classBM.html#126bd2595c48e311fc2a7ab72876092a" title="access function">_rv</a>() ).count() );
72<a name="l00088"></a>00088
73<a name="l00089"></a>00089                         <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i&lt;<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>.length(); i++ ) {pom += Coms ( i )-&gt;mean() * <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i );}
74<a name="l00090"></a>00090
75<a name="l00091"></a>00091                         <span class="keywordflow">return</span> concat ( E.mean(),pom );
76<a name="l00092"></a>00092                 }
77<a name="l00093"></a>00093
78<a name="l00094"></a>00094                 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;}
79<a name="l00095"></a>00095
80<a name="l00096"></a>00096                 <span class="keywordtype">double</span> evalpdflog ( <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;}
81<a name="l00097"></a>00097         };
82<a name="l00098"></a>00098
83<a name="l00100"></a>00100         mpfepdf jest;
84<a name="l00101"></a>00101
85<a name="l00102"></a>00102 <span class="keyword">public</span>:
86<a name="l00104"></a><a class="code" href="classMPF.html#fc5e11e11eec3195e3c6503937bf02bd">00104</a>         <a class="code" href="classMPF.html#fc5e11e11eec3195e3c6503937bf02bd" title="Default constructor.">MPF</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rvlin, <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &amp;rvpf, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;par0, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &amp;obs0, <span class="keywordtype">int</span> <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>, <span class="keyword">const</span> BM_T &amp;BMcond0 ) : <a class="code" href="classPF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> ( rvpf ,par0,obs0,n ),jest ( <a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a>,rvlin ) {
87<a name="l00105"></a>00105                 <span class="comment">//</span>
88<a name="l00106"></a>00106                 <span class="comment">//TODO test if rv and BMcond.rv are compatible.</span>
89<a name="l00107"></a>00107                 <a class="code" href="classBM.html#af00f0612fabe66241dd507188cdbf88" title="Random variable of the posterior.">rv</a>.<a class="code" href="classRV.html#4fc941a5ebc9f82aa372f54f2e02dab2" title="Add (concat) another variable to the current one.">add</a> ( rvlin );
90<a name="l00108"></a>00108                 <span class="comment">//</span>
91<a name="l00109"></a>00109
92<a name="l00110"></a>00110                 <span class="keywordflow">if</span> ( n&gt;10000 ) it_error ( <span class="stringliteral">"increase 10000 here!"</span> );
93<a name="l00111"></a>00111
94<a name="l00112"></a>00112                 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i&lt;n;i++ ) {
95<a name="l00113"></a>00113                         Bms[i] = <span class="keyword">new</span> BM_T ( BMcond0 ); <span class="comment">//copy constructor</span>
96<a name="l00114"></a>00114                         <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; pom=Bms[i]-&gt;_epdf();
97<a name="l00115"></a>00115                         jest.set_elements ( i,1.0/n,&amp;pom );
98<a name="l00116"></a>00116                 }
99<a name="l00117"></a>00117         };
100<a name="l00118"></a>00118
101<a name="l00119"></a>00119         ~<a class="code" href="classMPF.html" title="Marginalized Particle filter.">MPF</a>() {
102<a name="l00120"></a>00120         }
103<a name="l00121"></a>00121
104<a name="l00122"></a>00122         <span class="keywordtype">void</span> <a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt );
105<a name="l00123"></a><a class="code" href="classMPF.html#549e08268a46a250f21a33d06f19276a">00123</a>         <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; <a class="code" href="classMPF.html#549e08268a46a250f21a33d06f19276a" title="Returns a pointer to the epdf representing posterior density on parameters. Use with...">_epdf</a>() {<span class="keywordflow">return</span> jest;}
106<a name="l00125"></a><a class="code" href="classMPF.html#7c66e1c1c0e45fc4ae765133cb3a1553">00125</a>         <span class="keywordtype">void</span> <a class="code" href="classMPF.html#7c66e1c1c0e45fc4ae765133cb3a1553" 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="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; epdf0 ) {
107<a name="l00126"></a>00126                 <a class="code" href="classPF.html#04d38fbcc0348b558212f530d9ec183e" title="Set posterior density by sampling from epdf0.">PF::set_est</a> ( epdf0 );  <span class="comment">// sample params in condition</span>
108<a name="l00127"></a>00127                 <span class="comment">// copy conditions to BMs</span>
109<a name="l00128"></a>00128
110<a name="l00129"></a>00129                 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i&lt;<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;i++ ) {Bms[i]-&gt;condition ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ) );}
111<a name="l00130"></a>00130         }
112<a name="l00131"></a>00131
113<a name="l00132"></a>00132 <span class="comment">//SimStr:</span>
114<a name="l00133"></a>00133         <span class="keywordtype">double</span> SSAT;
115<a name="l00134"></a>00134 };
116<a name="l00135"></a>00135
117<a name="l00136"></a>00136 <span class="keyword">template</span>&lt;<span class="keyword">class</span> BM_T&gt;
118<a name="l00137"></a><a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623">00137</a> <span class="keywordtype">void</span> <a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623" title="Incremental Bayes rule.">MPF&lt;BM_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) {
119<a name="l00138"></a>00138         <span class="keywordtype">int</span> i;
120<a name="l00139"></a>00139         vec lls ( <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> );
121<a name="l00140"></a>00140         vec llsP ( <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> );
122<a name="l00141"></a>00141         ivec ind;
123<a name="l00142"></a>00142         <span class="keywordtype">double</span> mlls=-std::numeric_limits&lt;double&gt;::infinity();
124<a name="l00143"></a>00143
125<a name="l00144"></a>00144         <span class="comment">// StrSim:06</span>
126<a name="l00145"></a>00145         <span class="keywordtype">double</span> sumLWL=0.0;
127<a name="l00146"></a>00146         <span class="keywordtype">double</span> sumL2WL=0.0;
128<a name="l00147"></a>00147         <span class="keywordtype">double</span> WL = 0.0;
129<a name="l00148"></a>00148
130<a name="l00149"></a>00149 <span class="preprocessor">        #pragma omp parallel for</span>
131<a name="l00150"></a>00150 <span class="preprocessor"></span>        <span class="keywordflow">for</span> ( i=0;i&lt;<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;i++ ) {   
132<a name="l00151"></a>00151                 <span class="comment">//generate new samples from paramater evolution model;</span>
133<a name="l00152"></a>00152                 <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ) = <a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09" title="Parameter evolution model.">par</a>.<a class="code" href="classmpdf.html#b0193a350c97933ddf15b15a130da352" title="Returns the required moment of the epdf.">samplecond</a> ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ), llsP ( i ) );
134<a name="l00153"></a>00153                 Bms[i]-&gt;condition ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ) );
135<a name="l00154"></a>00154                 Bms[i]-&gt;bayes ( dt );
136<a name="l00155"></a>00155                 lls ( i ) = Bms[i]-&gt;_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span>
137<a name="l00156"></a>00156                 <span class="keywordflow">if</span> ( lls ( i ) &gt;mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span>
138<a name="l00157"></a>00157         }
139<a name="l00158"></a>00158
140<a name="l00159"></a>00159         <span class="keywordflow">if</span> ( <span class="keyword">false</span>) {
141<a name="l00160"></a>00160 <span class="preprocessor">                #pragma omp parallel for reduction(+:sumLWL,sumL2WL) private(WL)</span>
142<a name="l00161"></a>00161 <span class="preprocessor"></span>                <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) {
143<a name="l00162"></a>00162                         WL = <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i ) *exp ( llsP ( i ) ); <span class="comment">//using old weights!</span>
144<a name="l00163"></a>00163                         sumLWL += exp ( lls ( i ) ) *WL;
145<a name="l00164"></a>00164                         sumL2WL += exp ( 2*lls ( i ) ) *WL;
146<a name="l00165"></a>00165                 }
147<a name="l00166"></a>00166                 SSAT  = sumL2WL/ ( sumLWL*sumLWL );
148<a name="l00167"></a>00167         }
149<a name="l00168"></a>00168
150<a name="l00169"></a>00169         <span class="keywordtype">double</span> sum_w=0.0;
151<a name="l00170"></a>00170         <span class="comment">// compute weights</span>
152<a name="l00171"></a>00171 <span class="preprocessor">        #pragma omp parallel for</span>
153<a name="l00172"></a>00172 <span class="preprocessor"></span>        <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) {
154<a name="l00173"></a>00173                 <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i ) *= exp ( lls ( i ) - mlls ); <span class="comment">// multiply w by likelihood</span>
155<a name="l00174"></a>00174                 sum_w+=<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>(i);
156<a name="l00175"></a>00175         }
157<a name="l00176"></a>00176
158<a name="l00177"></a>00177         <span class="keywordflow">if</span> ( sum_w  &gt;0.0 ) {
159<a name="l00178"></a>00178                 <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span>
160<a name="l00179"></a>00179         } <span class="keywordflow">else</span> {
161<a name="l00180"></a>00180                 cout&lt;&lt;<span class="stringliteral">"sum(w)==0"</span>&lt;&lt;endl;
162<a name="l00181"></a>00181         }
163<a name="l00182"></a>00182
164<a name="l00183"></a>00183
165<a name="l00184"></a>00184         <span class="keywordtype">double</span> eff = 1.0/ ( <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>*<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> );
166<a name="l00185"></a>00185         <span class="keywordflow">if</span> ( eff &lt; ( 0.3*n ) ) {
167<a name="l00186"></a>00186                 ind = <a class="code" href="classPF.html#1a0a09e309da997f63ae8e30d1e9806b" title="posterior density">est</a>.<a class="code" href="classeEmp.html#77268292fc4465cb73ddbfb1f2932a59" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a>();
168<a name="l00187"></a>00187                 <span class="comment">// Resample Bms!</span>
169<a name="l00188"></a>00188
170<a name="l00189"></a>00189 <span class="preprocessor">                #pragma omp parallel for</span>
171<a name="l00190"></a>00190 <span class="preprocessor"></span>                <span class="keywordflow">for</span> ( i=0;i&lt;n;i++ ) {
172<a name="l00191"></a>00191                         <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span>
173<a name="l00192"></a>00192                                 <span class="comment">//fixme this would require new assignment operator</span>
174<a name="l00193"></a>00193                                 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span>
175<a name="l00194"></a>00194
176<a name="l00195"></a>00195                                 <span class="comment">// poor-man's solution: replicate constructor here</span>
177<a name="l00196"></a>00196                                 <span class="comment">// copied from MPF::MPF</span>
178<a name="l00197"></a>00197                                 <span class="keyword">delete</span> Bms[i];
179<a name="l00198"></a>00198                                 Bms[i] = <span class="keyword">new</span> BM_T ( *Bms[ind ( i ) ] ); <span class="comment">//copy constructor</span>
180<a name="l00199"></a>00199                                 <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>&amp; pom=Bms[i]-&gt;_epdf();
181<a name="l00200"></a>00200                                 jest.set_elements ( i,1.0/n,&amp;pom );
182<a name="l00201"></a>00201                         }
183<a name="l00202"></a>00202                 };
184<a name="l00203"></a>00203                 cout &lt;&lt; <span class="charliteral">'.'</span>;
185<a name="l00204"></a>00204         }
186<a name="l00205"></a>00205 }
187<a name="l00206"></a>00206
188<a name="l00207"></a>00207 <span class="preprocessor">#endif // KF_H</span>
189<a name="l00208"></a>00208 <span class="preprocessor"></span>
190<a name="l00209"></a>00209
191</pre></div></div>
192<hr size="1"><address style="text-align: right;"><small>Generated on Sat Aug 16 11:58:41 2008 for mixpp by&nbsp;
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194<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>
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