| 82 | | <a name="l00038"></a><a class="code" href="classbdm_1_1PF.html#a521e9621d3b5e1274275f323691afdaf">00038</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#a521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>; |
| 83 | | <a name="l00040"></a><a class="code" href="classbdm_1_1PF.html#ad6e7a62fba1e0a0d73c9b87f4fb683ec">00040</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *<a class="code" href="classbdm_1_1PF.html#ad6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a>; |
| 84 | | <a name="l00041"></a>00041 |
| 85 | | <a name="l00043"></a><a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52">00043</a> RESAMPLING_METHOD <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>; |
| 86 | | <a name="l00044"></a>00044 |
| 87 | | <a name="l00047"></a>00047 |
| 88 | | <a name="l00049"></a><a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1">00049</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a>; |
| 89 | | <a name="l00051"></a><a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6">00051</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a>; |
| 90 | | <a name="l00053"></a>00053 |
| 91 | | <a name="l00054"></a>00054 <span class="keyword">public</span>: |
| 92 | | <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#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>(), <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>() ), <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>() ), <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> ( false ), <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> ( false ) { |
| 93 | | <a name="l00058"></a>00058 <a class="code" href="classbdm_1_1BM.html#a109c1a626a69031658e3a44e9e500cca" title="IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].">LIDs</a>.set_size ( 5 ); |
| 94 | | <a name="l00059"></a>00059 }; |
| 95 | | <a name="l00060"></a>00060 <span class="comment">/* PF ( mpdf *par0, mpdf *obs0, epdf *epdf0, int n0 ) :</span> |
| 96 | | <a name="l00061"></a>00061 <span class="comment"> est ( ),_w ( est._w() ),_samples ( est._samples() ),opt_L_smp(false), opt_L_wei(false)</span> |
| 97 | | <a name="l00062"></a>00062 <span class="comment"> { set_parameters ( par0,obs0,n0 ); set_statistics ( ones ( n0 ),epdf0 ); };*/</span> |
| 98 | | <a name="l00063"></a>00063 <span class="keywordtype">void</span> set_parameters ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *obs0, <span class="keywordtype">int</span> n0, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
| 99 | | <a name="l00064"></a>00064 <a class="code" href="classbdm_1_1PF.html#a521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a> = par0; |
| 100 | | <a name="l00065"></a>00065 <a class="code" href="classbdm_1_1PF.html#ad6e7a62fba1e0a0d73c9b87f4fb683ec" title="Observation model.">obs</a> = obs0; |
| 101 | | <a name="l00066"></a>00066 <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> = n0; |
| 102 | | <a name="l00067"></a>00067 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a> = rm; |
| 103 | | <a name="l00068"></a>00068 }; |
| 104 | | <a name="l00069"></a>00069 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec w0, <span class="keyword">const</span> epdf &epdf0 ) { |
| 105 | | <a name="l00070"></a>00070 <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_statistics ( w0, epdf0 ); |
| 106 | | <a name="l00071"></a>00071 }; |
| 107 | | <a name="l00074"></a>00074 <span class="comment">// void set_est ( const epdf &epdf0 );</span> |
| 108 | | <a name="l00075"></a><a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">00075</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">set_options</a> ( <span class="keyword">const</span> <span class="keywordtype">string</span> &opt ) { |
| 109 | | <a name="l00076"></a>00076 <a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">BM::set_options</a> ( opt ); |
| 110 | | <a name="l00077"></a>00077 <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> = ( opt.find ( <span class="stringliteral">"logweights"</span> ) != string::npos ); |
| 111 | | <a name="l00078"></a>00078 <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> = ( opt.find ( <span class="stringliteral">"logsamples"</span> ) != string::npos ); |
| 112 | | <a name="l00079"></a>00079 } |
| 113 | | <a name="l00080"></a>00080 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a638946eea22d4964bf9350286bb4efd8" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
| 114 | | <a name="l00082"></a><a class="code" href="classbdm_1_1PF.html#a78a9f6809827be1d9bfe215d03b1c6ed">00082</a> vec* <a class="code" href="classbdm_1_1PF.html#a78a9f6809827be1d9bfe215d03b1c6ed" title="access function">__w</a>() { |
| 115 | | <a name="l00083"></a>00083 <span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| 116 | | <a name="l00084"></a>00084 } |
| 117 | | <a name="l00085"></a>00085 }; |
| 118 | | <a name="l00086"></a>00086 |
| 119 | | <a name="l00093"></a>00093 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 120 | | <a name="l00094"></a><a class="code" href="classbdm_1_1MPF.html">00094</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> { |
| 121 | | <a name="l00095"></a>00095 Array<BM_T*> BMs; |
| 122 | | <a name="l00096"></a>00096 |
| 123 | | <a name="l00098"></a>00098 |
| 124 | | <a name="l00099"></a>00099 <span class="keyword">class </span>mpfepdf : <span class="keyword">public</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> { |
| 125 | | <a name="l00100"></a>00100 <span class="keyword">protected</span>: |
| 126 | | <a name="l00101"></a>00101 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
| 127 | | <a name="l00102"></a>00102 vec &<a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| 128 | | <a name="l00103"></a>00103 Array<const epdf*> Coms; |
| 129 | | <a name="l00104"></a>00104 <span class="keyword">public</span>: |
| 130 | | <a name="l00105"></a>00105 mpfepdf ( <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E0 ) : |
| 131 | | <a name="l00106"></a>00106 <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( ), E ( E0 ), <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( E._w() ), |
| 132 | | <a name="l00107"></a>00107 Coms ( <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ) { |
| 133 | | <a name="l00108"></a>00108 }; |
| 134 | | <a name="l00110"></a>00110 <span class="keywordtype">void</span> read_statistics ( Array<BM_T*> &A ) { |
| 135 | | <a name="l00111"></a>00111 dim = E.dimension() + A ( 0 )->posterior().dimension(); |
| 136 | | <a name="l00112"></a>00112 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ; i++ ) { |
| 137 | | <a name="l00113"></a>00113 Coms ( i ) = &(A ( i )->posterior()); |
| 138 | | <a name="l00114"></a>00114 } |
| 139 | | <a name="l00115"></a>00115 } |
| 140 | | <a name="l00117"></a>00117 <span class="keywordtype">void</span> set_elements ( <span class="keywordtype">int</span> &i, <span class="keywordtype">double</span> wi, <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* ep ) { |
| 141 | | <a name="l00118"></a>00118 <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) = wi; |
| 142 | | <a name="l00119"></a>00119 Coms ( i ) = ep; |
| 143 | | <a name="l00120"></a>00120 }; |
| 144 | | <a name="l00121"></a>00121 |
| 145 | | <a name="l00122"></a>00122 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ) { |
| 146 | | <a name="l00123"></a>00123 E.set_parameters ( n, <span class="keyword">false</span> ); |
| 147 | | <a name="l00124"></a>00124 Coms.set_length ( n ); |
| 148 | | <a name="l00125"></a>00125 } |
| 149 | | <a name="l00126"></a>00126 vec mean()<span class="keyword"> const </span>{ |
| 150 | | <a name="l00127"></a>00127 <span class="comment">// ugly</span> |
| 151 | | <a name="l00128"></a>00128 vec pom = zeros ( Coms ( 0 )->dimension() ); |
| 152 | | <a name="l00129"></a>00129 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
| 153 | | <a name="l00130"></a>00130 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 154 | | <a name="l00131"></a>00131 } |
| 155 | | <a name="l00132"></a>00132 <span class="keywordflow">return</span> concat ( E.mean(), pom ); |
| 156 | | <a name="l00133"></a>00133 } |
| 157 | | <a name="l00134"></a>00134 vec variance()<span class="keyword"> const </span>{ |
| 158 | | <a name="l00135"></a>00135 <span class="comment">// ugly</span> |
| 159 | | <a name="l00136"></a>00136 vec pom = zeros ( Coms ( 0 )->dimension() ); |
| 160 | | <a name="l00137"></a>00137 vec pom2 = zeros ( Coms ( 0 )->dimension() ); |
| 161 | | <a name="l00138"></a>00138 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
| 162 | | <a name="l00139"></a>00139 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 163 | | <a name="l00140"></a>00140 pom2 += ( Coms ( i )->variance() + pow ( Coms ( i )->mean(), 2 ) ) * <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 164 | | <a name="l00141"></a>00141 } |
| 165 | | <a name="l00142"></a>00142 <span class="keywordflow">return</span> concat ( E.variance(), pom2 - pow ( pom, 2 ) ); |
| 166 | | <a name="l00143"></a>00143 } |
| 167 | | <a name="l00144"></a>00144 <span class="keywordtype">void</span> qbounds ( vec &lb, vec &ub, <span class="keywordtype">double</span> perc = 0.95 )<span class="keyword"> const </span>{ |
| 168 | | <a name="l00145"></a>00145 <span class="comment">//bounds on particles</span> |
| 169 | | <a name="l00146"></a>00146 vec lbp; |
| 170 | | <a name="l00147"></a>00147 vec ubp; |
| 171 | | <a name="l00148"></a>00148 E.qbounds ( lbp, ubp ); |
| 172 | | <a name="l00149"></a>00149 |
| 173 | | <a name="l00150"></a>00150 <span class="comment">//bounds on Components</span> |
| 174 | | <a name="l00151"></a>00151 <span class="keywordtype">int</span> dimC = Coms ( 0 )->dimension(); |
| 175 | | <a name="l00152"></a>00152 <span class="keywordtype">int</span> j; |
| 176 | | <a name="l00153"></a>00153 <span class="comment">// temporary</span> |
| 177 | | <a name="l00154"></a>00154 vec lbc ( dimC ); |
| 178 | | <a name="l00155"></a>00155 vec ubc ( dimC ); |
| 179 | | <a name="l00156"></a>00156 <span class="comment">// minima and maxima</span> |
| 180 | | <a name="l00157"></a>00157 vec Lbc ( dimC ); |
| 181 | | <a name="l00158"></a>00158 vec Ubc ( dimC ); |
| 182 | | <a name="l00159"></a>00159 Lbc = std::numeric_limits<double>::infinity(); |
| 183 | | <a name="l00160"></a>00160 Ubc = -std::numeric_limits<double>::infinity(); |
| 184 | | <a name="l00161"></a>00161 |
| 185 | | <a name="l00162"></a>00162 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
| 186 | | <a name="l00163"></a>00163 <span class="comment">// check Coms</span> |
| 187 | | <a name="l00164"></a>00164 Coms ( i )->qbounds ( lbc, ubc ); |
| 188 | | <a name="l00165"></a>00165 <span class="keywordflow">for</span> ( j = 0; j < dimC; j++ ) { |
| 189 | | <a name="l00166"></a>00166 <span class="keywordflow">if</span> ( lbc ( j ) < Lbc ( j ) ) { |
| 190 | | <a name="l00167"></a>00167 Lbc ( j ) = lbc ( j ); |
| 191 | | <a name="l00168"></a>00168 } |
| 192 | | <a name="l00169"></a>00169 <span class="keywordflow">if</span> ( ubc ( j ) > Ubc ( j ) ) { |
| 193 | | <a name="l00170"></a>00170 Ubc ( j ) = ubc ( j ); |
| 194 | | <a name="l00171"></a>00171 } |
| 195 | | <a name="l00172"></a>00172 } |
| 196 | | <a name="l00173"></a>00173 } |
| 197 | | <a name="l00174"></a>00174 lb = concat ( lbp, Lbc ); |
| 198 | | <a name="l00175"></a>00175 ub = concat ( ubp, Ubc ); |
| 199 | | <a name="l00176"></a>00176 } |
| 200 | | <a name="l00177"></a>00177 |
| 201 | | <a name="l00178"></a>00178 vec sample()<span class="keyword"> const </span>{ |
| 202 | | <a name="l00179"></a>00179 <a class="code" href="bdmerror_8h.html#a7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"Not implemented"</span> ); |
| 203 | | <a name="l00180"></a>00180 <span class="keywordflow">return</span> vec(); |
| 204 | | <a name="l00181"></a>00181 } |
| 205 | | <a name="l00182"></a>00182 |
| 206 | | <a name="l00183"></a>00183 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{ |
| 207 | | <a name="l00184"></a>00184 <a class="code" href="bdmerror_8h.html#a7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"not implemented"</span> ); |
| 208 | | <a name="l00185"></a>00185 <span class="keywordflow">return</span> 0.0; |
| | 82 | <a name="l00038"></a><a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff">00038</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>; |
| | 83 | <a name="l00040"></a><a class="code" href="classbdm_1_1PF.html#a77ed889e1b993df253e93059933d227d">00040</a> <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> <a class="code" href="classbdm_1_1PF.html#a77ed889e1b993df253e93059933d227d" title="Observation model.">obs</a>; |
| | 84 | <a name="l00042"></a><a class="code" href="classbdm_1_1PF.html#a08cffd22d6e9501f283972245aeff8cd">00042</a> vec <a class="code" href="classbdm_1_1PF.html#a08cffd22d6e9501f283972245aeff8cd" title="internal structure storing loglikelihood of predictions">lls</a>; |
| | 85 | <a name="l00043"></a>00043 |
| | 86 | <a name="l00045"></a><a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52">00045</a> RESAMPLING_METHOD <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>; |
| | 87 | <a name="l00048"></a><a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">00048</a> <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">res_threshold</a>; |
| | 88 | <a name="l00049"></a>00049 |
| | 89 | <a name="l00052"></a>00052 |
| | 90 | <a name="l00054"></a><a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1">00054</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a>; |
| | 91 | <a name="l00056"></a><a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6">00056</a> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a>; |
| | 92 | <a name="l00058"></a>00058 |
| | 93 | <a name="l00059"></a>00059 <span class="keyword">public</span>: |
| | 94 | <a name="l00062"></a>00062 <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#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>(), <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>() ), <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>() ), <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> ( false ), <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> ( false ) { |
| | 95 | <a name="l00063"></a>00063 <a class="code" href="classbdm_1_1BM.html#a109c1a626a69031658e3a44e9e500cca" title="IDs of storages in loggers 4:[1=mean,2=lb,3=ub,4=ll].">LIDs</a>.set_size ( 5 ); |
| | 96 | <a name="l00064"></a>00064 }; |
| | 97 | <a name="l00065"></a>00065 |
| | 98 | <a name="l00066"></a>00066 <span class="keywordtype">void</span> set_parameters (<span class="keywordtype">int</span> n0, <span class="keywordtype">double</span> res_th0=0.5, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
| | 99 | <a name="l00067"></a>00067 <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> = n0; |
| | 100 | <a name="l00068"></a>00068 <a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">res_threshold</a> = res_th0; |
| | 101 | <a name="l00069"></a>00069 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a> = rm; |
| | 102 | <a name="l00070"></a>00070 }; |
| | 103 | <a name="l00071"></a>00071 <span class="keywordtype">void</span> set_model ( shared_ptr<mpdf> par0, shared_ptr<mpdf> obs0) { |
| | 104 | <a name="l00072"></a>00072 <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a> = par0; |
| | 105 | <a name="l00073"></a>00073 <a class="code" href="classbdm_1_1PF.html#a77ed889e1b993df253e93059933d227d" title="Observation model.">obs</a> = obs0; |
| | 106 | <a name="l00074"></a>00074 <span class="comment">// set values for posterior</span> |
| | 107 | <a name="l00075"></a>00075 <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_rv(<a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv()); |
| | 108 | <a name="l00076"></a>00076 }; |
| | 109 | <a name="l00077"></a>00077 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> vec w0, <span class="keyword">const</span> epdf &epdf0 ) { |
| | 110 | <a name="l00078"></a>00078 <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.set_statistics ( w0, epdf0 ); |
| | 111 | <a name="l00079"></a>00079 }; |
| | 112 | <a name="l00080"></a>00080 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> eEmp &epdf0 ) { |
| | 113 | <a name="l00081"></a>00081 <a class="code" href="bdmerror_8h.html#a89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a>(epdf0._rv().equal(<a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv()),<span class="stringliteral">"Incompatibel input"</span>); |
| | 114 | <a name="l00082"></a>00082 <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>=epdf0; |
| | 115 | <a name="l00083"></a>00083 }; |
| | 116 | <a name="l00089"></a><a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">00089</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">set_options</a> ( <span class="keyword">const</span> <span class="keywordtype">string</span> &opt ) { |
| | 117 | <a name="l00090"></a>00090 <a class="code" href="classbdm_1_1PF.html#abf104b869b5df8dd4a14bbe430d40488">BM::set_options</a> ( opt ); |
| | 118 | <a name="l00091"></a>00091 <a class="code" href="classbdm_1_1PF.html#a5a49463a88ee80771a464861df845ff6" title="Log all samples.">opt_L_wei</a> = ( opt.find ( <span class="stringliteral">"logweights"</span> ) != string::npos ); |
| | 119 | <a name="l00092"></a>00092 <a class="code" href="classbdm_1_1PF.html#a98ef9ff80c394fafd28680b7a3f831b1" title="Log all samples.">opt_L_smp</a> = ( opt.find ( <span class="stringliteral">"logsamples"</span> ) != string::npos ); |
| | 120 | <a name="l00093"></a>00093 } |
| | 121 | <a name="l00095"></a>00095 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a63282dc111d1afb32c194c955d966a15" title="bayes I - generate samples and add their weights to lls">bayes_gensmp</a>(); |
| | 122 | <a name="l00097"></a>00097 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#aec76b4d647ac7dc683d8c9a7b7611026" title="bayes II - compute weights of the">bayes_weights</a>(); |
| | 123 | <a name="l00099"></a><a class="code" href="classbdm_1_1PF.html#ac3443faad7159e742ef3cb0674a92634">00099</a> <span class="keyword">virtual</span> <span class="keywordtype">bool</span> <a class="code" href="classbdm_1_1PF.html#ac3443faad7159e742ef3cb0674a92634" title="important part of particle filtering - decide if it is time to perform resampling...">do_resampling</a>(){ |
| | 124 | <a name="l00100"></a>00100 <span class="keywordtype">double</span> eff = 1.0 / ( <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> * <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ); |
| | 125 | <a name="l00101"></a>00101 <span class="keywordflow">return</span> eff < ( <a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">res_threshold</a>*<a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| | 126 | <a name="l00102"></a>00102 } |
| | 127 | <a name="l00103"></a>00103 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a638946eea22d4964bf9350286bb4efd8" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
| | 128 | <a name="l00105"></a><a class="code" href="classbdm_1_1PF.html#a37cb95af19c7bd13eb3ec61f25923463">00105</a> vec& <a class="code" href="classbdm_1_1PF.html#a37cb95af19c7bd13eb3ec61f25923463" title="access function">__w</a>() { <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; } |
| | 129 | <a name="l00107"></a><a class="code" href="classbdm_1_1PF.html#a82d221d771cbc3c15a37cb358d759734">00107</a> vec& <a class="code" href="classbdm_1_1PF.html#a82d221d771cbc3c15a37cb358d759734" title="access function">_lls</a>() { <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1PF.html#a08cffd22d6e9501f283972245aeff8cd" title="internal structure storing loglikelihood of predictions">lls</a>; } |
| | 130 | <a name="l00108"></a>00108 RESAMPLING_METHOD _resmethod()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>; } |
| | 131 | <a name="l00110"></a><a class="code" href="classbdm_1_1PF.html#aee9553da1a05671f94f30e0e94ff42cd">00110</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a>& <a class="code" href="classbdm_1_1PF.html#aee9553da1a05671f94f30e0e94ff42cd" title="access function">posterior</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>;} |
| | 132 | <a name="l00111"></a>00111 |
| | 133 | <a name="l00124"></a><a class="code" href="classbdm_1_1PF.html#a40d74160df73d152a9bcf044eac25663">00124</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a40d74160df73d152a9bcf044eac25663">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){ |
| | 134 | <a name="l00125"></a>00125 <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a> = UI::build<mpdf>(<span class="keyword">set</span>,<span class="stringliteral">"parameter_pdf"</span>,UI::compulsory); |
| | 135 | <a name="l00126"></a>00126 <a class="code" href="classbdm_1_1PF.html#a77ed889e1b993df253e93059933d227d" title="Observation model.">obs</a> = UI::build<mpdf>(<span class="keyword">set</span>,<span class="stringliteral">"observation_pdf"</span>,UI::compulsory); |
| | 136 | <a name="l00127"></a>00127 |
| | 137 | <a name="l00128"></a>00128 <a class="code" href="classbdm_1_1PF.html#a8ac867d4b88c2c6c73ae29d47f37d0bb" title="load prior information from set and set internal structures accordingly">prior_from_set</a>(<span class="keyword">set</span>); |
| | 138 | <a name="l00129"></a>00129 <a class="code" href="classbdm_1_1PF.html#a30f6a71f3e56ce25e4e0ecafa0ffbd8d" title="auxiliary function reading parameter &#39;resmethod&#39; from configuration file">resmethod_from_set</a>(<span class="keyword">set</span>); |
| | 139 | <a name="l00130"></a>00130 <span class="comment">// set resampling method</span> |
| | 140 | <a name="l00131"></a>00131 <span class="comment">//set drv</span> |
| | 141 | <a name="l00132"></a>00132 <span class="comment">//find potential input - what remains in rvc when we subtract rv</span> |
| | 142 | <a name="l00133"></a>00133 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> u = <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rvc().remove_time().subt( <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv() ); |
| | 143 | <a name="l00134"></a>00134 <span class="comment">//find potential input - what remains in rvc when we subtract x_t</span> |
| | 144 | <a name="l00135"></a>00135 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> obs_u = obs->_rvc().remove_time().subt( <a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv() ); |
| | 145 | <a name="l00136"></a>00136 |
| | 146 | <a name="l00137"></a>00137 u.<a class="code" href="classbdm_1_1RV.html#a87841b5ee43997b79789c0c22047e224" title="Add (concat) another variable to the current one,.">add</a>(obs_u); <span class="comment">// join both u, and check if they do not overlap</span> |
| | 147 | <a name="l00138"></a>00138 |
| | 148 | <a name="l00139"></a>00139 set_drv(concat(obs->_rv(),u) ); |
| | 149 | <a name="l00140"></a>00140 } |
| | 150 | <a name="l00142"></a><a class="code" href="classbdm_1_1PF.html#a30f6a71f3e56ce25e4e0ecafa0ffbd8d">00142</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a30f6a71f3e56ce25e4e0ecafa0ffbd8d" title="auxiliary function reading parameter &#39;resmethod&#39; from configuration file">resmethod_from_set</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){ |
| | 151 | <a name="l00143"></a>00143 <span class="keywordtype">string</span> resmeth; |
| | 152 | <a name="l00144"></a>00144 <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1UI.html#acd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(resmeth,<span class="keyword">set</span>,<span class="stringliteral">"resmethod"</span>,UI::optional)){ |
| | 153 | <a name="l00145"></a>00145 <span class="keywordflow">if</span> (resmeth==<span class="stringliteral">"systematic"</span>) { |
| | 154 | <a name="l00146"></a>00146 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>= SYSTEMATIC; |
| | 155 | <a name="l00147"></a>00147 } <span class="keywordflow">else</span> { |
| | 156 | <a name="l00148"></a>00148 <span class="keywordflow">if</span> (resmeth==<span class="stringliteral">"multinomial"</span>){ |
| | 157 | <a name="l00149"></a>00149 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>=MULTINOMIAL; |
| | 158 | <a name="l00150"></a>00150 } <span class="keywordflow">else</span> { |
| | 159 | <a name="l00151"></a>00151 <span class="keywordflow">if</span> (resmeth==<span class="stringliteral">"stratified"</span>){ |
| | 160 | <a name="l00152"></a>00152 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>= STRATIFIED; |
| | 161 | <a name="l00153"></a>00153 } <span class="keywordflow">else</span> { |
| | 162 | <a name="l00154"></a>00154 <a class="code" href="bdmerror_8h.html#a7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a>(<span class="stringliteral">"Unknown resampling method"</span>); |
| | 163 | <a name="l00155"></a>00155 } |
| | 164 | <a name="l00156"></a>00156 } |
| | 165 | <a name="l00157"></a>00157 } |
| | 166 | <a name="l00158"></a>00158 } <span class="keywordflow">else</span> { |
| | 167 | <a name="l00159"></a>00159 <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a>=SYSTEMATIC; |
| | 168 | <a name="l00160"></a>00160 }; |
| | 169 | <a name="l00161"></a>00161 <span class="keywordflow">if</span>(!<a class="code" href="classbdm_1_1UI.html#acd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(<a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">res_threshold</a>, <span class="keyword">set</span>, <span class="stringliteral">"res_threshold"</span>, UI::optional)){ |
| | 170 | <a name="l00162"></a>00162 <a class="code" href="classbdm_1_1PF.html#ab16816e20f97f9bec993d1f25fc3d711">res_threshold</a>=0.5; |
| | 171 | <a name="l00163"></a>00163 } |
| | 172 | <a name="l00164"></a>00164 } |
| | 173 | <a name="l00166"></a><a class="code" href="classbdm_1_1PF.html#a8ac867d4b88c2c6c73ae29d47f37d0bb">00166</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a8ac867d4b88c2c6c73ae29d47f37d0bb" title="load prior information from set and set internal structures accordingly">prior_from_set</a>(<span class="keyword">const</span> Setting & <span class="keyword">set</span>){ |
| | 174 | <a name="l00167"></a>00167 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<epdf></a> pri = UI::build<epdf>(<span class="keyword">set</span>,<span class="stringliteral">"prior"</span>,UI::compulsory); |
| | 175 | <a name="l00168"></a>00168 |
| | 176 | <a name="l00169"></a>00169 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> *test_emp=<span class="keyword">dynamic_cast<</span><a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a>*<span class="keyword">></span>(&(*pri)); |
| | 177 | <a name="l00170"></a>00170 <span class="keywordflow">if</span> (test_emp) { <span class="comment">// given pdf is sampled</span> |
| | 178 | <a name="l00171"></a>00171 <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>=*test_emp; |
| | 179 | <a name="l00172"></a>00172 } <span class="keywordflow">else</span> { |
| | 180 | <a name="l00173"></a>00173 <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>; |
| | 181 | <a name="l00174"></a>00174 <span class="keywordflow">if</span> (!<a class="code" href="classbdm_1_1UI.html#acd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(n,<span class="keyword">set</span>,<span class="stringliteral">"n"</span>,UI::optional)){n=10;} |
| | 182 | <a name="l00175"></a>00175 <span class="comment">// sample from prior</span> |
| | 183 | <a name="l00176"></a>00176 set_statistics(ones(n)/n, *pri); |
| | 184 | <a name="l00177"></a>00177 } |
| | 185 | <a name="l00178"></a>00178 <span class="comment">//validate();</span> |
| | 186 | <a name="l00179"></a>00179 } |
| | 187 | <a name="l00180"></a>00180 |
| | 188 | <a name="l00181"></a><a class="code" href="classbdm_1_1PF.html#a7ebbb12b5b01e8ac6985af0e04e0f0c2">00181</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#a7ebbb12b5b01e8ac6985af0e04e0f0c2" title="This method TODO.">validate</a>(){ |
| | 189 | <a name="l00182"></a>00182 <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>=<a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); |
| | 190 | <a name="l00183"></a>00183 <a class="code" href="classbdm_1_1PF.html#a08cffd22d6e9501f283972245aeff8cd" title="internal structure storing loglikelihood of predictions">lls</a>=zeros(<a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>); |
| | 191 | <a name="l00184"></a>00184 <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv()._dsize()>0) { |
| | 192 | <a name="l00185"></a>00185 <a class="code" href="bdmerror_8h.html#a7a3399d182b8e3065532596e76f84849" title="Throw std::runtime_exception if t is not true.">bdm_assert</a>(<a class="code" href="classbdm_1_1PF.html#a0b7ffedb2051161df6c102881afe41ff" title="Parameter evolution model.">par</a>->_rv()._dsize()==<a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1epdf.html#a7083a65f7b7a0d0d13b2c516bd2ec29c" title="Size of the random variable.">dimension</a>(),<span class="stringliteral">"Mismatch of RV and dimension of posterior"</span> ); |
| 216 | | <a name="l00195"></a>00195 <span class="keyword">public</span>: |
| 217 | | <a name="l00197"></a><a class="code" href="classbdm_1_1MPF.html#a0068e7ca53d90fa5911eb31a0d657f26">00197</a> <a class="code" href="classbdm_1_1MPF.html#a0068e7ca53d90fa5911eb31a0d657f26" 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#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a> ) {}; |
| 218 | | <a name="l00198"></a>00198 <span class="keywordtype">void</span> set_parameters ( <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a> *obs0, <span class="keywordtype">int</span> n0, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
| 219 | | <a name="l00199"></a>00199 PF::set_parameters ( par0, obs0, n0, rm ); |
| 220 | | <a name="l00200"></a>00200 jest.set_parameters ( n0 );<span class="comment">//duplication of rm</span> |
| 221 | | <a name="l00201"></a>00201 BMs.set_length ( n0 ); |
| 222 | | <a name="l00202"></a>00202 } |
| 223 | | <a name="l00203"></a>00203 <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> epdf &epdf0, <span class="keyword">const</span> BM_T* BMcond0 ) { |
| 224 | | <a name="l00204"></a>00204 |
| 225 | | <a name="l00205"></a>00205 PF::set_statistics ( ones ( <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ) / <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>, epdf0 ); |
| 226 | | <a name="l00206"></a>00206 <span class="comment">// copy</span> |
| 227 | | <a name="l00207"></a>00207 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < <a class="code" href="classbdm_1_1PF.html#aeeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>; i++ ) { |
| 228 | | <a name="l00208"></a>00208 BMs ( i ) = <span class="keyword">new</span> BM_T ( *BMcond0 ); |
| 229 | | <a name="l00209"></a>00209 BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 230 | | <a name="l00210"></a>00210 } |
| 231 | | <a name="l00211"></a>00211 |
| 232 | | <a name="l00212"></a>00212 jest.read_statistics ( BMs ); |
| 233 | | <a name="l00213"></a>00213 <span class="comment">//options</span> |
| 234 | | <a name="l00214"></a>00214 }; |
| 235 | | <a name="l00215"></a>00215 |
| 236 | | <a name="l00216"></a>00216 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#a286d040770d08bd7ff416cea617b1b14" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
| 237 | | <a name="l00217"></a>00217 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{ |
| 238 | | <a name="l00218"></a>00218 <span class="keywordflow">return</span> jest; |
| 239 | | <a name="l00219"></a>00219 } |
| 240 | | <a name="l00221"></a>00221 <span class="comment">/* void set_est ( const epdf& epdf0 ) {</span> |
| 241 | | <a name="l00222"></a>00222 <span class="comment"> PF::set_est ( epdf0 ); // sample params in condition</span> |
| 242 | | <a name="l00223"></a>00223 <span class="comment"> // copy conditions to BMs</span> |
| 243 | | <a name="l00224"></a>00224 <span class="comment"></span> |
| 244 | | <a name="l00225"></a>00225 <span class="comment"> for ( int i=0;i<n;i++ ) {BMs(i)->condition ( _samples ( i ) );}</span> |
| 245 | | <a name="l00226"></a>00226 <span class="comment"> }*/</span> |
| 246 | | <a name="l00227"></a><a class="code" href="classbdm_1_1MPF.html#a2e95498dec734088ab9f4878ff404144">00227</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#a2e95498dec734088ab9f4878ff404144" 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 ) { |
| 247 | | <a name="l00228"></a>00228 <a class="code" href="classbdm_1_1MPF.html#a2e95498dec734088ab9f4878ff404144" title="Set postrior of rvc to samples from epdf0. Statistics of BMs are not re-computed!...">PF::set_options</a> ( opt ); |
| 248 | | <a name="l00229"></a>00229 opt_L_mea = ( opt.find ( <span class="stringliteral">"logmeans"</span> ) != string::npos ); |
| 249 | | <a name="l00230"></a>00230 } |
| 250 | | <a name="l00231"></a>00231 |
| 251 | | <a name="l00233"></a><a class="code" href="classbdm_1_1MPF.html#ab6e7b094cbe32944b8ccde5df73cd839">00233</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1MPF.html#ab6e7b094cbe32944b8ccde5df73cd839" title="Access function.">_BM</a> ( <span class="keywordtype">int</span> i ) { |
| 252 | | <a name="l00234"></a>00234 <span class="keywordflow">return</span> BMs ( i ); |
| 253 | | <a name="l00235"></a>00235 } |
| 254 | | <a name="l00236"></a>00236 }; |
| 255 | | <a name="l00237"></a>00237 |
| 256 | | <a name="l00238"></a>00238 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 257 | | <a name="l00239"></a><a class="code" href="classbdm_1_1MPF.html#a286d040770d08bd7ff416cea617b1b14">00239</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#a286d040770d08bd7ff416cea617b1b14" title="Incremental Bayes rule.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
| 258 | | <a name="l00240"></a>00240 <span class="keywordtype">int</span> i; |
| 259 | | <a name="l00241"></a>00241 vec lls ( n ); |
| 260 | | <a name="l00242"></a>00242 vec llsP ( n ); |
| 261 | | <a name="l00243"></a>00243 ivec ind; |
| 262 | | <a name="l00244"></a>00244 <span class="keywordtype">double</span> mlls = -std::numeric_limits<double>::infinity(); |
| 263 | | <a name="l00245"></a>00245 |
| 264 | | <a name="l00246"></a>00246 <span class="preprocessor">#pragma omp parallel for</span> |
| 265 | | <a name="l00247"></a>00247 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
| 266 | | <a name="l00248"></a>00248 <span class="comment">//generate new samples from paramater evolution model;</span> |
| 267 | | <a name="l00249"></a>00249 vec old_smp=<a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ); |
| 268 | | <a name="l00250"></a>00250 <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) = <a class="code" href="classbdm_1_1PF.html#a521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>-><a class="code" href="classbdm_1_1mpdf.html#af0c1db6fcbb3aae2dd6123884457a367" title="Returns a sample from the density conditioned on cond, .">samplecond</a> ( old_smp ); |
| 269 | | <a name="l00251"></a>00251 llsP ( i ) = <a class="code" href="classbdm_1_1PF.html#a521e9621d3b5e1274275f323691afdaf" title="Parameter evolution model.">par</a>-><a class="code" href="classbdm_1_1mpdf.html#a6336a8a72462e2a56a3989a220f18b1b" title="Shortcut for conditioning and evaluation of the internal epdf. In some cases, this...">evallogcond</a> ( <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ), old_smp ); |
| 270 | | <a name="l00252"></a>00252 BMs ( i )->condition ( <a class="code" href="classbdm_1_1PF.html#a914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 271 | | <a name="l00253"></a>00253 BMs ( i )->bayes ( dt ); |
| 272 | | <a name="l00254"></a>00254 lls ( i ) = BMs ( i )->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| 273 | | <a name="l00255"></a>00255 <span class="keywordflow">if</span> ( lls ( i ) > mlls ) mlls = lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| 274 | | <a name="l00256"></a>00256 } |
| 275 | | <a name="l00257"></a>00257 |
| 276 | | <a name="l00258"></a>00258 <span class="keywordtype">double</span> sum_w = 0.0; |
| 277 | | <a name="l00259"></a>00259 <span class="comment">// compute weights</span> |
| 278 | | <a name="l00260"></a>00260 <span class="preprocessor">#pragma omp parallel for</span> |
| 279 | | <a name="l00261"></a>00261 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
| 280 | | <a name="l00262"></a>00262 <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) *= exp ( lls ( i ) - mlls ); <span class="comment">// multiply w by likelihood</span> |
| 281 | | <a name="l00263"></a>00263 sum_w += <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 282 | | <a name="l00264"></a>00264 } |
| 283 | | <a name="l00265"></a>00265 |
| 284 | | <a name="l00266"></a>00266 <span class="keywordflow">if</span> ( sum_w > 0.0 ) { |
| 285 | | <a name="l00267"></a>00267 <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /= sum_w; <span class="comment">//?</span> |
| 286 | | <a name="l00268"></a>00268 } <span class="keywordflow">else</span> { |
| 287 | | <a name="l00269"></a>00269 cout << <span class="stringliteral">"sum(w)==0"</span> << endl; |
| 288 | | <a name="l00270"></a>00270 } |
| 289 | | <a name="l00271"></a>00271 |
| 290 | | <a name="l00272"></a>00272 |
| 291 | | <a name="l00273"></a>00273 <span class="keywordtype">double</span> eff = 1.0 / ( <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> * <a class="code" href="classbdm_1_1PF.html#af5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ); |
| 292 | | <a name="l00274"></a>00274 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
| 293 | | <a name="l00275"></a>00275 ind = <a class="code" href="classbdm_1_1PF.html#adc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1eEmp.html#af06ce255de5dbb2313f52ee51f82ba3d" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a> ( <a class="code" href="classbdm_1_1PF.html#a9932c7c5865954ef9a438afcbe944e52" title="which resampling method will be used">resmethod</a> ); |
| 294 | | <a name="l00276"></a>00276 <span class="comment">// Resample Bms!</span> |
| 295 | | <a name="l00277"></a>00277 |
| 296 | | <a name="l00278"></a>00278 <span class="preprocessor">#pragma omp parallel for</span> |
| 297 | | <a name="l00279"></a>00279 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i = 0; i < n; i++ ) { |
| 298 | | <a name="l00280"></a>00280 <span class="keywordflow">if</span> ( ind ( i ) != i ) {<span class="comment">//replace the current Bm by a new one</span> |
| 299 | | <a name="l00281"></a>00281 <span class="comment">//fixme this would require new assignment operator</span> |
| 300 | | <a name="l00282"></a>00282 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
| 301 | | <a name="l00283"></a>00283 |
| 302 | | <a name="l00284"></a>00284 <span class="comment">// poor-man's solution: replicate constructor here</span> |
| 303 | | <a name="l00285"></a>00285 <span class="comment">// copied from MPF::MPF</span> |
| 304 | | <a name="l00286"></a>00286 <span class="keyword">delete</span> BMs ( i ); |
| 305 | | <a name="l00287"></a>00287 BMs ( i ) = <span class="keyword">new</span> BM_T ( *BMs ( ind ( i ) ) ); <span class="comment">//copy constructor</span> |
| 306 | | <a name="l00288"></a>00288 <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& pom = BMs ( i )->posterior(); |
| 307 | | <a name="l00289"></a>00289 jest.set_elements ( i, 1.0 / n, &pom ); |
| 308 | | <a name="l00290"></a>00290 } |
| 309 | | <a name="l00291"></a>00291 }; |
| 310 | | <a name="l00292"></a>00292 cout << <span class="charliteral">'.'</span>; |
| 311 | | <a name="l00293"></a>00293 } |
| 312 | | <a name="l00294"></a>00294 } |
| 313 | | <a name="l00295"></a>00295 |
| 314 | | <a name="l00296"></a>00296 } |
| 315 | | <a name="l00297"></a>00297 <span class="preprocessor">#endif // KF_H</span> |
| 316 | | <a name="l00298"></a>00298 <span class="preprocessor"></span> |
| 317 | | <a name="l00299"></a>00299 |
| | 201 | <a name="l00202"></a><a class="code" href="classbdm_1_1MPF.html">00202</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_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a> { |
| | 202 | <a name="l00203"></a>00203 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<PF></a> pf; |
| | 203 | <a name="l00204"></a>00204 Array<BM*> BMs; |
| | 204 | <a name="l00205"></a>00205 |
| | 205 | <a name="l00207"></a>00207 |
| | 206 | <a name="l00208"></a>00208 <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> { |
| | 207 | <a name="l00209"></a>00209 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<PF></a> &pf; |
| | 208 | <a name="l00210"></a>00210 Array<BM*> &BMs; |
| | 209 | <a name="l00211"></a>00211 <span class="keyword">public</span>: |
| | 210 | <a name="l00212"></a>00212 mpfepdf (<a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<PF></a> &pf0, Array<BM*> &BMs0): <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>(), pf(pf0), BMs(BMs0) { }; |
| | 211 | <a name="l00214"></a>00214 <span class="keywordtype">void</span> read_parameters(){ |
| | 212 | <a name="l00215"></a>00215 rv = concat(pf->posterior()._rv(), BMs(0)->posterior()._rv()); |
| | 213 | <a name="l00216"></a>00216 dim = pf->posterior().dimension() + BMs(0)->posterior().dimension(); |
| | 214 | <a name="l00217"></a>00217 <a class="code" href="bdmerror_8h.html#a89a0f906b242b79c5d3d342291b2cab4" title="Throw std::runtime_exception if t is not true and NDEBUG is not defined.">bdm_assert_debug</a>(dim == rv.<a class="code" href="classbdm_1_1RV.html#ade30156104f61d86c94f758861418089" title="total size of a random variable">_dsize</a>(), <span class="stringliteral">"Wrong name "</span>); |
| | 215 | <a name="l00218"></a>00218 } |
| | 216 | <a name="l00219"></a>00219 vec mean()<span class="keyword"> const </span>{ |
| | 217 | <a name="l00220"></a>00220 <span class="keyword">const</span> vec &w = pf->posterior()._w(); |
| | 218 | <a name="l00221"></a>00221 vec pom = zeros ( BMs(0)->posterior ().dimension() ); |
| | 219 | <a name="l00222"></a>00222 <span class="comment">//compute mean of BMs</span> |
| | 220 | <a name="l00223"></a>00223 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < w.length(); i++ ) { |
| | 221 | <a name="l00224"></a>00224 pom += BMs ( i )->posterior().mean() * w ( i ); |
| | 222 | <a name="l00225"></a>00225 } |
| | 223 | <a name="l00226"></a>00226 <span class="keywordflow">return</span> concat ( pf->posterior().mean(), pom ); |
| | 224 | <a name="l00227"></a>00227 } |
| | 225 | <a name="l00228"></a>00228 vec variance()<span class="keyword"> const </span>{ |
| | 226 | <a name="l00229"></a>00229 <span class="keyword">const</span> vec &w = pf->posterior()._w(); |
| | 227 | <a name="l00230"></a>00230 |
| | 228 | <a name="l00231"></a>00231 vec pom = zeros ( BMs(0)->posterior ().dimension() ); |
| | 229 | <a name="l00232"></a>00232 vec pom2 = zeros ( BMs(0)->posterior ().dimension() ); |
| | 230 | <a name="l00233"></a>00233 vec mea; |
| | 231 | <a name="l00234"></a>00234 |
| | 232 | <a name="l00235"></a>00235 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < w.length(); i++ ) { |
| | 233 | <a name="l00236"></a>00236 <span class="comment">// save current mean </span> |
| | 234 | <a name="l00237"></a>00237 mea = BMs ( i )->posterior().mean(); |
| | 235 | <a name="l00238"></a>00238 pom += mea * w ( i ); |
| | 236 | <a name="l00239"></a>00239 <span class="comment">//compute variance</span> |
| | 237 | <a name="l00240"></a>00240 pom2 += ( BMs ( i )->posterior().variance() + pow ( mea, 2 ) ) * w ( i ); |
| | 238 | <a name="l00241"></a>00241 } |
| | 239 | <a name="l00242"></a>00242 <span class="keywordflow">return</span> concat ( pf->posterior().variance(), pom2 - pow ( pom, 2 ) ); |
| | 240 | <a name="l00243"></a>00243 } |
| | 241 | <a name="l00244"></a>00244 |
| | 242 | <a name="l00245"></a>00245 <span class="keywordtype">void</span> qbounds ( vec &lb, vec &ub, <span class="keywordtype">double</span> perc = 0.95 )<span class="keyword"> const </span>{ |
| | 243 | <a name="l00246"></a>00246 <span class="comment">//bounds on particles</span> |
| | 244 | <a name="l00247"></a>00247 vec lbp; |
| | 245 | <a name="l00248"></a>00248 vec ubp; |
| | 246 | <a name="l00249"></a>00249 pf->posterior().qbounds ( lbp, ubp ); |
| | 247 | <a name="l00250"></a>00250 |
| | 248 | <a name="l00251"></a>00251 <span class="comment">//bounds on Components</span> |
| | 249 | <a name="l00252"></a>00252 <span class="keywordtype">int</span> dimC = BMs ( 0 )->posterior().dimension(); |
| | 250 | <a name="l00253"></a>00253 <span class="keywordtype">int</span> j; |
| | 251 | <a name="l00254"></a>00254 <span class="comment">// temporary</span> |
| | 252 | <a name="l00255"></a>00255 vec lbc ( dimC ); |
| | 253 | <a name="l00256"></a>00256 vec ubc ( dimC ); |
| | 254 | <a name="l00257"></a>00257 <span class="comment">// minima and maxima</span> |
| | 255 | <a name="l00258"></a>00258 vec Lbc ( dimC ); |
| | 256 | <a name="l00259"></a>00259 vec Ubc ( dimC ); |
| | 257 | <a name="l00260"></a>00260 Lbc = std::numeric_limits<double>::infinity(); |
| | 258 | <a name="l00261"></a>00261 Ubc = -std::numeric_limits<double>::infinity(); |
| | 259 | <a name="l00262"></a>00262 |
| | 260 | <a name="l00263"></a>00263 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < BMs.length(); i++ ) { |
| | 261 | <a name="l00264"></a>00264 <span class="comment">// check Coms</span> |
| | 262 | <a name="l00265"></a>00265 BMs ( i )->posterior().qbounds ( lbc, ubc ); |
| | 263 | <a name="l00266"></a>00266 <span class="comment">//save either minima or maxima</span> |
| | 264 | <a name="l00267"></a>00267 <span class="keywordflow">for</span> ( j = 0; j < dimC; j++ ) { |
| | 265 | <a name="l00268"></a>00268 <span class="keywordflow">if</span> ( lbc ( j ) < Lbc ( j ) ) { |
| | 266 | <a name="l00269"></a>00269 Lbc ( j ) = lbc ( j ); |
| | 267 | <a name="l00270"></a>00270 } |
| | 268 | <a name="l00271"></a>00271 <span class="keywordflow">if</span> ( ubc ( j ) > Ubc ( j ) ) { |
| | 269 | <a name="l00272"></a>00272 Ubc ( j ) = ubc ( j ); |
| | 270 | <a name="l00273"></a>00273 } |
| | 271 | <a name="l00274"></a>00274 } |
| | 272 | <a name="l00275"></a>00275 } |
| | 273 | <a name="l00276"></a>00276 lb = concat ( lbp, Lbc ); |
| | 274 | <a name="l00277"></a>00277 ub = concat ( ubp, Ubc ); |
| | 275 | <a name="l00278"></a>00278 } |
| | 276 | <a name="l00279"></a>00279 |
| | 277 | <a name="l00280"></a>00280 vec sample()<span class="keyword"> const </span>{ |
| | 278 | <a name="l00281"></a>00281 <a class="code" href="bdmerror_8h.html#a7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"Not implemented"</span> ); |
| | 279 | <a name="l00282"></a>00282 <span class="keywordflow">return</span> vec(); |
| | 280 | <a name="l00283"></a>00283 } |
| | 281 | <a name="l00284"></a>00284 |
| | 282 | <a name="l00285"></a>00285 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{ |
| | 283 | <a name="l00286"></a>00286 <a class="code" href="bdmerror_8h.html#a7c43f3a72afe68ab0c85663a1bb3521a" title="Unconditionally throw std::runtime_error.">bdm_error</a> ( <span class="stringliteral">"not implemented"</span> ); |
| | 284 | <a name="l00287"></a>00287 <span class="keywordflow">return</span> 0.0; |
| | 285 | <a name="l00288"></a>00288 } |
| | 286 | <a name="l00289"></a>00289 }; |
| | 287 | <a name="l00290"></a>00290 |
| | 288 | <a name="l00292"></a>00292 mpfepdf jest; |
| | 289 | <a name="l00293"></a>00293 |
| | 290 | <a name="l00295"></a>00295 <span class="keywordtype">bool</span> opt_L_mea; |
| | 291 | <a name="l00296"></a>00296 |
| | 292 | <a name="l00297"></a>00297 <span class="keyword">public</span>: |
| | 293 | <a name="l00299"></a><a class="code" href="classbdm_1_1MPF.html#af45da512c659b40b21a74492a0c06853">00299</a> <a class="code" href="classbdm_1_1MPF.html#af45da512c659b40b21a74492a0c06853" title="Default constructor.">MPF</a> () : jest (pf,BMs) {}; |
| | 294 | <a name="l00300"></a>00300 <span class="keywordtype">void</span> set_parameters ( <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> par0, <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> obs0, <span class="keywordtype">int</span> n0, RESAMPLING_METHOD rm = SYSTEMATIC ) { |
| | 295 | <a name="l00301"></a>00301 pf->set_model ( par0, obs0); |
| | 296 | <a name="l00302"></a>00302 pf->set_parameters(n0, rm ); |
| | 297 | <a name="l00303"></a>00303 BMs.set_length ( n0 ); |
| | 298 | <a name="l00304"></a>00304 } |
| | 299 | <a name="l00305"></a>00305 <span class="keywordtype">void</span> set_BM ( <span class="keyword">const</span> BM &BMcond0 ) { |
| | 300 | <a name="l00306"></a>00306 |
| | 301 | <a name="l00307"></a>00307 <span class="keywordtype">int</span> n=pf->__w().length(); |
| | 302 | <a name="l00308"></a>00308 BMs.set_length(n); |
| | 303 | <a name="l00309"></a>00309 <span class="comment">// copy</span> |
| | 304 | <a name="l00310"></a>00310 <span class="comment">//BMcond0 .condition ( pf->posterior()._sample ( 0 ) );</span> |
| | 305 | <a name="l00311"></a>00311 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i = 0; i < n; i++ ) { |
| | 306 | <a name="l00312"></a>00312 BMs ( i ) = BMcond0._copy_(); |
| | 307 | <a name="l00313"></a>00313 BMs ( i )->condition ( pf->posterior()._sample ( i ) ); |
| | 308 | <a name="l00314"></a>00314 } |
| | 309 | <a name="l00315"></a>00315 }; |
| | 310 | <a name="l00316"></a>00316 |
| | 311 | <a name="l00317"></a>00317 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#a0fbe47b20c491f25030ef2875c148892" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
| | 312 | <a name="l00318"></a>00318 <span class="keyword">const</span> epdf& posterior()<span class="keyword"> const </span>{ |
| | 313 | <a name="l00319"></a>00319 <span class="keywordflow">return</span> jest; |
| | 314 | <a name="l00320"></a>00320 } |
| | 315 | <a name="l00323"></a><a class="code" href="classbdm_1_1MPF.html#aada1bdb117bc78035fbb49765fa7ef10">00323</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#aada1bdb117bc78035fbb49765fa7ef10">set_options</a> ( <span class="keyword">const</span> <span class="keywordtype">string</span> &opt ) { |
| | 316 | <a name="l00324"></a>00324 <a class="code" href="classbdm_1_1MPF.html#aada1bdb117bc78035fbb49765fa7ef10">BM::set_options</a>(opt); |
| | 317 | <a name="l00325"></a>00325 opt_L_mea = ( opt.find ( <span class="stringliteral">"logmeans"</span> ) != string::npos ); |
| | 318 | <a name="l00326"></a>00326 } |
| | 319 | <a name="l00327"></a>00327 |
| | 320 | <a name="l00329"></a><a class="code" href="classbdm_1_1MPF.html#a71608a6986f57dcfb935e016b97c0637">00329</a> <span class="keyword">const</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of a system, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1MPF.html#a71608a6986f57dcfb935e016b97c0637" title="Access function.">_BM</a> ( <span class="keywordtype">int</span> i ) { |
| | 321 | <a name="l00330"></a>00330 <span class="keywordflow">return</span> BMs ( i ); |
| | 322 | <a name="l00331"></a>00331 } |
| | 323 | <a name="l00332"></a>00332 |
| | 324 | <a name="l00344"></a><a class="code" href="classbdm_1_1MPF.html#a9f74326b9ca3c888cb8eff1355ba3670">00344</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#a9f74326b9ca3c888cb8eff1355ba3670">from_setting</a>(<span class="keyword">const</span> Setting &<span class="keyword">set</span>){ |
| | 325 | <a name="l00345"></a>00345 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> par = UI::build<mpdf>(<span class="keyword">set</span>,<span class="stringliteral">"parameter_pdf"</span>,UI::compulsory); |
| | 326 | <a name="l00346"></a>00346 <a class="code" href="classbdm_1_1shared__ptr.html">shared_ptr<mpdf></a> obs= <span class="keyword">new</span> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling , where is random variable, rv, and...">mpdf</a>(); <span class="comment">// not used!!</span> |
| | 327 | <a name="l00347"></a>00347 |
| | 328 | <a name="l00348"></a>00348 pf = <span class="keyword">new</span> <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a>; |
| | 329 | <a name="l00349"></a>00349 <span class="comment">// rpior must be set before BM</span> |
| | 330 | <a name="l00350"></a>00350 pf->prior_from_set(<span class="keyword">set</span>); |
| | 331 | <a name="l00351"></a>00351 pf->resmethod_from_set(<span class="keyword">set</span>); |
| | 332 | <a name="l00352"></a>00352 pf->set_model(par,obs); |
| | 333 | <a name="l00353"></a>00353 |
| | 334 | <a name="l00354"></a>00354 <a class="code" href="classbdm_1_1shared__ptr.html" title="A naive implementation of roughly a subset of the std::tr1::shared_ptr spec.">shared_ptr<BM></a> BM0 =UI::build<BM>(<span class="keyword">set</span>,<span class="stringliteral">"BM"</span>,UI::compulsory); |
| | 335 | <a name="l00355"></a>00355 set_BM(*BM0); |
| | 336 | <a name="l00356"></a>00356 |
| | 337 | <a name="l00357"></a>00357 <span class="keywordtype">string</span> opt; |
| | 338 | <a name="l00358"></a>00358 <span class="keywordflow">if</span> (<a class="code" href="classbdm_1_1UI.html#acd1667e6fec99ec64dabcb3ca2ff922d">UI::get</a>(opt,<span class="keyword">set</span>,<span class="stringliteral">"options"</span>,UI::optional)){ |
| | 339 | <a name="l00359"></a>00359 <a class="code" href="classbdm_1_1MPF.html#aada1bdb117bc78035fbb49765fa7ef10">set_options</a>(opt); |
| | 340 | <a name="l00360"></a>00360 } |
| | 341 | <a name="l00361"></a>00361 <span class="comment">//set drv</span> |
| | 342 | <a name="l00362"></a>00362 <span class="comment">//find potential input - what remains in rvc when we subtract rv</span> |
| | 343 | <a name="l00363"></a>00363 <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> u = par->_rvc().remove_time().subt( par->_rv() ); |
| | 344 | <a name="l00364"></a>00364 set_drv(concat(BM0->_drv(),u) ); |
| | 345 | <a name="l00365"></a>00365 <a class="code" href="classbdm_1_1MPF.html#aa91b588de1b9690ca475c945d0f10f08" title="This method TODO.">validate</a>(); |
| | 346 | <a name="l00366"></a>00366 } |
| | 347 | <a name="l00367"></a><a class="code" href="classbdm_1_1MPF.html#aa91b588de1b9690ca475c945d0f10f08">00367</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html#aa91b588de1b9690ca475c945d0f10f08" title="This method TODO.">validate</a>(){ |
| | 348 | <a name="l00368"></a>00368 <span class="keywordflow">try</span>{ |
| | 349 | <a name="l00369"></a>00369 pf->validate(); |
| | 350 | <a name="l00370"></a>00370 } <span class="keywordflow">catch</span> (std::exception &e){ |
| | 351 | <a name="l00371"></a>00371 <span class="keywordflow">throw</span> <a class="code" href="classbdm_1_1UIException.html">UIException</a>(<span class="stringliteral">"Error in PF part of MPF:"</span>); |
| | 352 | <a name="l00372"></a>00372 } |
| | 353 | <a name="l00373"></a>00373 jest.read_parameters(); |
| | 354 | <a name="l00374"></a>00374 } |
| | 355 | <a name="l00375"></a>00375 |
| | 356 | <a name="l00376"></a>00376 }; |
| | 357 | <a name="l00377"></a>00377 <a class="code" href="user__info_8h.html#a4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(MPF); |
| | 358 | <a name="l00378"></a>00378 |
| | 359 | <a name="l00379"></a>00379 } |
| | 360 | <a name="l00380"></a>00380 <span class="preprocessor">#endif // KF_H</span> |
| | 361 | <a name="l00381"></a>00381 <span class="preprocessor"></span> |
| | 362 | <a name="l00382"></a>00382 |
