28 | | <a name="l00022"></a>00022 <span class="comment">//UGLY HACK</span> |
29 | | <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>0 the value is written.</span> |
30 | | <a name="l00024"></a>00024 |
31 | | <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> { |
32 | | <a name="l00032"></a>00032 <span class="keyword">protected</span>: |
33 | | <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>; |
34 | | <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>; |
35 | | <a name="l00038"></a><a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a">00038</a> vec &<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>; |
36 | | <a name="l00040"></a><a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5">00040</a> Array<vec> &<a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a>; |
37 | | <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> &<a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09" title="Parameter evolution model.">par</a>; |
38 | | <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> &<a class="code" href="classPF.html#dd0a687a4515333d6809147335854e77" title="Observation model.">obs</a>; |
39 | | <a name="l00045"></a>00045 <span class="keyword">public</span>: |
40 | | <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> &rv0, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par0, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &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 ), |
41 | | <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>() ), |
42 | | <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 ) {}; |
43 | | <a name="l00050"></a>00050 |
44 | | <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> &epdf0 ); |
45 | | <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 &dt ); |
46 | | <a name="l00055"></a><a class="code" href="classPF.html#140a073d5236684078b09021892d3b20">00055</a> vec* <a class="code" href="classPF.html#140a073d5236684078b09021892d3b20" title="access function">__w</a>(){<span class="keywordflow">return</span> &<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>;} |
47 | | <a name="l00056"></a>00056 }; |
48 | | <a name="l00057"></a>00057 |
49 | | <a name="l00064"></a>00064 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 28 | <a name="l00028"></a><a class="code" href="classbdm_1_1PF.html">00028</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> { |
| 29 | <a name="l00029"></a>00029 <span class="keyword">protected</span>: |
| 30 | <a name="l00031"></a><a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe">00031</a> <span class="keywordtype">int</span> <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>; |
| 31 | <a name="l00033"></a><a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af">00033</a> <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>; |
| 32 | <a name="l00035"></a><a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3">00035</a> vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| 33 | <a name="l00037"></a><a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1">00037</a> Array<vec> &<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>; |
| 34 | <a name="l00039"></a><a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34">00039</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &<a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" title="Parameter evolution model.">par</a>; |
| 35 | <a name="l00041"></a><a class="code" href="classbdm_1_1PF.html#c58b8fa634272c3f48845a9020ba55aa">00041</a> <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &<a class="code" href="classbdm_1_1PF.html#c58b8fa634272c3f48845a9020ba55aa" title="Observation model.">obs</a>; |
| 36 | <a name="l00042"></a>00042 <span class="keyword">public</span>: |
| 37 | <a name="l00044"></a><a class="code" href="classbdm_1_1PF.html#df9e7dc54dbe1c78a4aa503c42f7f8c4">00044</a> <a class="code" href="classbdm_1_1PF.html#df9e7dc54dbe1c78a4aa503c42f7f8c4" title="Default constructor.">PF</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rv0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par0, <a class="code" href="classbdm_1_1mpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs0, <span class="keywordtype">int</span> n0 ) :<a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( rv0 ), |
| 38 | <a name="l00045"></a>00045 <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ( n0 ),<a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a> ( rv0,<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ),<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>() ),<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a>() ), |
| 39 | <a name="l00046"></a>00046 <a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" title="Parameter evolution model.">par</a> ( par0 ), <a class="code" href="classbdm_1_1PF.html#c58b8fa634272c3f48845a9020ba55aa" title="Observation model.">obs</a> ( obs0 ) {}; |
| 40 | <a name="l00047"></a>00047 |
| 41 | <a name="l00049"></a>00049 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#6f1988db4c3f602d187a6c15ec89cb1e" title="Set posterior density by sampling from epdf0.">set_est</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> &epdf0 ); |
| 42 | <a name="l00050"></a>00050 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1PF.html#638946eea22d4964bf9350286bb4efd8" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ); |
| 43 | <a name="l00052"></a><a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed">00052</a> vec* <a class="code" href="classbdm_1_1PF.html#78a9f6809827be1d9bfe215d03b1c6ed" title="access function">__w</a>(){<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>;} |
| 44 | <a name="l00053"></a>00053 }; |
| 45 | <a name="l00054"></a>00054 |
| 46 | <a name="l00061"></a>00061 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 47 | <a name="l00062"></a>00062 |
| 48 | <a name="l00063"></a><a class="code" href="classbdm_1_1MPF.html">00063</a> <span class="keyword">class </span><a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF</a> : <span class="keyword">public</span> <a class="code" href="classbdm_1_1PF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> { |
| 49 | <a name="l00064"></a>00064 BM_T* Bms[10000]; |
51 | | <a name="l00066"></a><a class="code" href="classMPF.html">00066</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> { |
52 | | <a name="l00067"></a>00067 BM_T* Bms[10000]; |
53 | | <a name="l00068"></a>00068 |
54 | | <a name="l00070"></a>00070 |
55 | | <a name="l00071"></a>00071 <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> { |
56 | | <a name="l00072"></a>00072 <span class="keyword">protected</span>: |
57 | | <a name="l00073"></a>00073 <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
58 | | <a name="l00074"></a>00074 vec &<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>; |
59 | | <a name="l00075"></a>00075 Array<const epdf*> Coms; |
60 | | <a name="l00076"></a>00076 <span class="keyword">public</span>: |
61 | | <a name="l00077"></a>00077 mpfepdf ( <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> &E0, <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &rvc ) : |
62 | | <a name="l00078"></a>00078 <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() ), |
63 | | <a name="l00079"></a>00079 Coms ( <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>.length() ) { |
64 | | <a name="l00080"></a>00080 <a class="code" href="classBM.html#af00f0612fabe66241dd507188cdbf88" title="Random variable of the posterior.">rv</a>.<a class="code" href="classRV.html#935790526b630dec4ffefa9ec0c2b6fb" title="Add (concat) another variable to the current one,.">add</a> ( E._rv() ); |
65 | | <a name="l00081"></a>00081 <a class="code" href="classBM.html#af00f0612fabe66241dd507188cdbf88" title="Random variable of the posterior.">rv</a>.<a class="code" href="classRV.html#935790526b630dec4ffefa9ec0c2b6fb" title="Add (concat) another variable to the current one,.">add</a> ( rvc ); |
66 | | <a name="l00082"></a>00082 }; |
| 51 | <a name="l00067"></a>00067 |
| 52 | <a name="l00068"></a>00068 <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> { |
| 53 | <a name="l00069"></a>00069 <span class="keyword">protected</span>: |
| 54 | <a name="l00070"></a>00070 <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E; |
| 55 | <a name="l00071"></a>00071 vec &<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>; |
| 56 | <a name="l00072"></a>00072 Array<const epdf*> Coms; |
| 57 | <a name="l00073"></a>00073 <span class="keyword">public</span>: |
| 58 | <a name="l00074"></a>00074 mpfepdf ( <a class="code" href="classbdm_1_1eEmp.html" title="Weighted empirical density.">eEmp</a> &E0, <span class="keyword">const</span> <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a> &rvc ) : |
| 59 | <a name="l00075"></a>00075 <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a> ( <a class="code" href="classbdm_1_1RV.html" title="Class representing variables, most often random variables.">RV</a>( ) ), E ( E0 ), <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( E._w() ), |
| 60 | <a name="l00076"></a>00076 Coms ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length() ) { |
| 61 | <a name="l00077"></a>00077 <a class="code" href="classbdm_1_1BM.html#18d6db4af8ee42077741d9e3618153ca" title="Random variable of the posterior.">rv</a>.<a class="code" href="classbdm_1_1RV.html#87841b5ee43997b79789c0c22047e224" title="Add (concat) another variable to the current one,.">add</a> ( E._rv() ); |
| 62 | <a name="l00078"></a>00078 <a class="code" href="classbdm_1_1BM.html#18d6db4af8ee42077741d9e3618153ca" title="Random variable of the posterior.">rv</a>.<a class="code" href="classbdm_1_1RV.html#87841b5ee43997b79789c0c22047e224" title="Add (concat) another variable to the current one,.">add</a> ( rvc ); |
| 63 | <a name="l00079"></a>00079 }; |
| 64 | <a name="l00080"></a>00080 |
| 65 | <a name="l00081"></a>00081 <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 ) |
| 66 | <a name="l00082"></a>00082 {<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;}; |
68 | | <a name="l00084"></a>00084 <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="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>* ep ) |
69 | | <a name="l00085"></a>00085 {<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i ) =wi; Coms ( i ) =ep;}; |
70 | | <a name="l00086"></a>00086 |
71 | | <a name="l00087"></a>00087 vec mean()<span class="keyword"> const </span>{ |
72 | | <a name="l00088"></a>00088 <span class="comment">// ugly</span> |
73 | | <a name="l00089"></a>00089 vec pom=zeros ( ( Coms ( 0 )-><a class="code" href="classBM.html#126bd2595c48e311fc2a7ab72876092a" title="access function">_rv</a>() ).count() ); |
74 | | <a name="l00090"></a>00090 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i<<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>.length(); i++ ) {pom += Coms ( i )->mean() * <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i );} |
75 | | <a name="l00091"></a>00091 <span class="keywordflow">return</span> <a class="code" href="group__core.html#g33c114e83980d883c5b211c47d5322a4" title="Concat two random variables.">concat</a> ( E.mean(),pom ); |
76 | | <a name="l00092"></a>00092 } |
77 | | <a name="l00093"></a>00093 vec variance()<span class="keyword"> const </span>{ |
78 | | <a name="l00094"></a>00094 <span class="comment">// ugly</span> |
79 | | <a name="l00095"></a>00095 vec pom=zeros ( ( Coms ( 0 )-><a class="code" href="classBM.html#126bd2595c48e311fc2a7ab72876092a" title="access function">_rv</a>() ).count() ); |
80 | | <a name="l00096"></a>00096 vec pom2=zeros ( ( Coms ( 0 )-><a class="code" href="classBM.html#126bd2595c48e311fc2a7ab72876092a" title="access function">_rv</a>() ).count() ); |
81 | | <a name="l00097"></a>00097 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i<<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
82 | | <a name="l00098"></a>00098 pom += Coms ( i )->mean() * <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i ); |
83 | | <a name="l00099"></a>00099 pom2 += (Coms ( i )->variance() + pow(Coms(i)->mean(),2)) * <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> ( i );} |
84 | | <a name="l00100"></a>00100 <span class="keywordflow">return</span> <a class="code" href="group__core.html#g33c114e83980d883c5b211c47d5322a4" title="Concat two random variables.">concat</a> ( E.variance(),pom2-pow(pom,2) ); |
85 | | <a name="l00101"></a>00101 } |
86 | | <a name="l00102"></a>00102 |
87 | | <a name="l00103"></a>00103 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;} |
| 68 | <a name="l00084"></a>00084 vec mean()<span class="keyword"> const </span>{ |
| 69 | <a name="l00085"></a>00085 <span class="comment">// ugly</span> |
| 70 | <a name="l00086"></a>00086 vec pom=zeros ( ( Coms ( 0 )-><a class="code" href="classbdm_1_1BM.html#40a3c891996391e3135518053a917793" title="access function">_rv</a>() ).count() ); |
| 71 | <a name="l00087"></a>00087 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i<<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) {pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i );} |
| 72 | <a name="l00088"></a>00088 <span class="keywordflow">return</span> concat ( E.mean(),pom ); |
| 73 | <a name="l00089"></a>00089 } |
| 74 | <a name="l00090"></a>00090 vec variance()<span class="keyword"> const </span>{ |
| 75 | <a name="l00091"></a>00091 <span class="comment">// ugly</span> |
| 76 | <a name="l00092"></a>00092 vec pom=zeros ( ( Coms ( 0 )-><a class="code" href="classbdm_1_1BM.html#40a3c891996391e3135518053a917793" title="access function">_rv</a>() ).count() ); |
| 77 | <a name="l00093"></a>00093 vec pom2=zeros ( ( Coms ( 0 )-><a class="code" href="classbdm_1_1BM.html#40a3c891996391e3135518053a917793" title="access function">_rv</a>() ).count() ); |
| 78 | <a name="l00094"></a>00094 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0; i<<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>.length(); i++ ) { |
| 79 | <a name="l00095"></a>00095 pom += Coms ( i )->mean() * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ); |
| 80 | <a name="l00096"></a>00096 pom2 += (Coms ( i )->variance() + pow(Coms(i)->mean(),2)) * <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i );} |
| 81 | <a name="l00097"></a>00097 <span class="keywordflow">return</span> concat ( E.variance(),pom2-pow(pom,2) ); |
| 82 | <a name="l00098"></a>00098 } |
| 83 | <a name="l00099"></a>00099 |
| 84 | <a name="l00100"></a>00100 vec sample()<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"Not implemented"</span> );<span class="keywordflow">return</span> 0;} |
| 85 | <a name="l00101"></a>00101 |
| 86 | <a name="l00102"></a>00102 <span class="keywordtype">double</span> evallog ( <span class="keyword">const</span> vec &val )<span class="keyword"> const </span>{it_error ( <span class="stringliteral">"not implemented"</span> ); <span class="keywordflow">return</span> 0.0;} |
| 87 | <a name="l00103"></a>00103 }; |
120 | | <a name="l00139"></a>00139 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;i++ ) {Bms[i]->condition ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ) );} |
121 | | <a name="l00140"></a>00140 } |
122 | | <a name="l00141"></a>00141 |
123 | | <a name="l00143"></a><a class="code" href="classMPF.html#82e7d8fd6bce040a78327d5038ab668f">00143</a> <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classMPF.html#82e7d8fd6bce040a78327d5038ab668f" title="Access function.">_BM</a>(<span class="keywordtype">int</span> i){<span class="keywordflow">return</span> Bms[i];} |
124 | | <a name="l00144"></a>00144 }; |
125 | | <a name="l00145"></a>00145 |
126 | | <a name="l00146"></a>00146 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
127 | | <a name="l00147"></a><a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623">00147</a> <span class="keywordtype">void</span> <a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623" title="Incremental Bayes rule.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
128 | | <a name="l00148"></a>00148 <span class="keywordtype">int</span> i; |
129 | | <a name="l00149"></a>00149 vec lls ( <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> ); |
130 | | <a name="l00150"></a>00150 vec llsP ( <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> ); |
131 | | <a name="l00151"></a>00151 ivec ind; |
132 | | <a name="l00152"></a>00152 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
133 | | <a name="l00153"></a>00153 |
134 | | <a name="l00154"></a>00154 <span class="preprocessor"> #pragma omp parallel for</span> |
135 | | <a name="l00155"></a>00155 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;i++ ) { |
136 | | <a name="l00156"></a>00156 <span class="comment">//generate new samples from paramater evolution model;</span> |
137 | | <a name="l00157"></a>00157 <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#3f172b79ec4a5ebc87898a5381141f1b" title="Returns a sample from the density conditioned on cond, .">samplecond</a> ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ), llsP ( i ) ); |
138 | | <a name="l00158"></a>00158 Bms[i]->condition ( <a class="code" href="classPF.html#cf7dad75e31215780a746c30e71ad9c5" title="pointer into eEmp ">_samples</a> ( i ) ); |
139 | | <a name="l00159"></a>00159 Bms[i]->bayes ( dt ); |
140 | | <a name="l00160"></a>00160 lls ( i ) = Bms[i]->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
141 | | <a name="l00161"></a>00161 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
142 | | <a name="l00162"></a>00162 } |
143 | | <a name="l00163"></a>00163 |
144 | | <a name="l00164"></a>00164 <span class="keywordtype">double</span> sum_w=0.0; |
145 | | <a name="l00165"></a>00165 <span class="comment">// compute weights</span> |
146 | | <a name="l00166"></a>00166 <span class="preprocessor"> #pragma omp parallel for</span> |
147 | | <a name="l00167"></a>00167 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
148 | | <a name="l00168"></a>00168 <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> |
149 | | <a name="l00169"></a>00169 sum_w+=<a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a>(i); |
150 | | <a name="l00170"></a>00170 } |
151 | | <a name="l00171"></a>00171 |
152 | | <a name="l00172"></a>00172 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
153 | | <a name="l00173"></a>00173 <a class="code" href="classPF.html#5c87aba508df321ff26536ced64dbb3a" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
154 | | <a name="l00174"></a>00174 } <span class="keywordflow">else</span> { |
155 | | <a name="l00175"></a>00175 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
156 | | <a name="l00176"></a>00176 } |
157 | | <a name="l00177"></a>00177 |
158 | | <a name="l00178"></a>00178 |
159 | | <a name="l00179"></a>00179 <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> ); |
160 | | <a name="l00180"></a>00180 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
161 | | <a name="l00181"></a>00181 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>(); |
162 | | <a name="l00182"></a>00182 <span class="comment">// Resample Bms!</span> |
163 | | <a name="l00183"></a>00183 |
164 | | <a name="l00184"></a>00184 <span class="preprocessor"> #pragma omp parallel for</span> |
165 | | <a name="l00185"></a>00185 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
166 | | <a name="l00186"></a>00186 <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span> |
167 | | <a name="l00187"></a>00187 <span class="comment">//fixme this would require new assignment operator</span> |
168 | | <a name="l00188"></a>00188 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
169 | | <a name="l00189"></a>00189 |
170 | | <a name="l00190"></a>00190 <span class="comment">// poor-man's solution: replicate constructor here</span> |
171 | | <a name="l00191"></a>00191 <span class="comment">// copied from MPF::MPF</span> |
172 | | <a name="l00192"></a>00192 <span class="keyword">delete</span> Bms[i]; |
173 | | <a name="l00193"></a>00193 Bms[i] = <span class="keyword">new</span> BM_T ( *Bms[ind ( i ) ] ); <span class="comment">//copy constructor</span> |
174 | | <a name="l00194"></a>00194 <span class="keyword">const</span> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& pom=Bms[i]->_epdf(); |
175 | | <a name="l00195"></a>00195 jest.set_elements ( i,1.0/n,&pom ); |
176 | | <a name="l00196"></a>00196 } |
177 | | <a name="l00197"></a>00197 }; |
178 | | <a name="l00198"></a>00198 cout << <span class="charliteral">'.'</span>; |
179 | | <a name="l00199"></a>00199 } |
180 | | <a name="l00200"></a>00200 } |
181 | | <a name="l00201"></a>00201 |
182 | | <a name="l00202"></a>00202 <span class="preprocessor">#endif // KF_H</span> |
183 | | <a name="l00203"></a>00203 <span class="preprocessor"></span> |
184 | | <a name="l00204"></a>00204 |
| 120 | <a name="l00140"></a><a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c">00140</a> <a class="code" href="classbdm_1_1BM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>* <a class="code" href="classbdm_1_1MPF.html#82b5a34d9ed0e78452f98d2ecbf1e93c" title="Access function.">_BM</a>(<span class="keywordtype">int</span> i){<span class="keywordflow">return</span> Bms[i];} |
| 121 | <a name="l00141"></a>00141 }; |
| 122 | <a name="l00142"></a>00142 |
| 123 | <a name="l00143"></a>00143 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| 124 | <a name="l00144"></a><a class="code" href="classbdm_1_1MPF.html#286d040770d08bd7ff416cea617b1b14">00144</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1MPF.html" title="Marginalized Particle filter.">MPF<BM_T>::bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
| 125 | <a name="l00145"></a>00145 <span class="keywordtype">int</span> i; |
| 126 | <a name="l00146"></a>00146 vec lls ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 127 | <a name="l00147"></a>00147 vec llsP ( <a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a> ); |
| 128 | <a name="l00148"></a>00148 ivec ind; |
| 129 | <a name="l00149"></a>00149 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(); |
| 130 | <a name="l00150"></a>00150 |
| 131 | <a name="l00151"></a>00151 <span class="preprocessor"> #pragma omp parallel for</span> |
| 132 | <a name="l00152"></a>00152 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<<a class="code" href="classbdm_1_1PF.html#eeafaf9b8ad75fe62ee9fd6369e3f7fe" title="number of particles;">n</a>;i++ ) { |
| 133 | <a name="l00153"></a>00153 <span class="comment">//generate new samples from paramater evolution model;</span> |
| 134 | <a name="l00154"></a>00154 <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) = <a class="code" href="classbdm_1_1PF.html#cf3a1b2a407012e47ac878e3aa2fbf34" title="Parameter evolution model.">par</a>.<a class="code" href="classbdm_1_1mpdf.html#e4848a428d8ef0549c6e4a9ed386d9f2" title="Returns a sample from the density conditioned on cond, .">samplecond</a> ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ), llsP ( i ) ); |
| 135 | <a name="l00155"></a>00155 Bms[i]->condition ( <a class="code" href="classbdm_1_1PF.html#914bd66025692c4018dbd482cb3c47c1" title="pointer into eEmp ">_samples</a> ( i ) ); |
| 136 | <a name="l00156"></a>00156 Bms[i]->bayes ( dt ); |
| 137 | <a name="l00157"></a>00157 lls ( i ) = Bms[i]->_ll(); <span class="comment">// lls above is also in proposal her must be lls(i) =, not +=!!</span> |
| 138 | <a name="l00158"></a>00158 <span class="keywordflow">if</span> ( lls ( i ) >mlls ) mlls=lls ( i ); <span class="comment">//find maximum likelihood (for numerical stability)</span> |
| 139 | <a name="l00159"></a>00159 } |
| 140 | <a name="l00160"></a>00160 |
| 141 | <a name="l00161"></a>00161 <span class="keywordtype">double</span> sum_w=0.0; |
| 142 | <a name="l00162"></a>00162 <span class="comment">// compute weights</span> |
| 143 | <a name="l00163"></a>00163 <span class="preprocessor"> #pragma omp parallel for</span> |
| 144 | <a name="l00164"></a>00164 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| 145 | <a name="l00165"></a>00165 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ( i ) *= exp ( lls ( i ) - mlls ); <span class="comment">// multiply w by likelihood</span> |
| 146 | <a name="l00166"></a>00166 sum_w+=<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>(i); |
| 147 | <a name="l00167"></a>00167 } |
| 148 | <a name="l00168"></a>00168 |
| 149 | <a name="l00169"></a>00169 <span class="keywordflow">if</span> ( sum_w >0.0 ) { |
| 150 | <a name="l00170"></a>00170 <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> /=sum_w; <span class="comment">//?</span> |
| 151 | <a name="l00171"></a>00171 } <span class="keywordflow">else</span> { |
| 152 | <a name="l00172"></a>00172 cout<<<span class="stringliteral">"sum(w)==0"</span><<endl; |
| 153 | <a name="l00173"></a>00173 } |
| 154 | <a name="l00174"></a>00174 |
| 155 | <a name="l00175"></a>00175 |
| 156 | <a name="l00176"></a>00176 <span class="keywordtype">double</span> eff = 1.0/ ( <a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a>*<a class="code" href="classbdm_1_1PF.html#f5149d5522d1095d39240c4c607f61a3" title="pointer into eEmp ">_w</a> ); |
| 157 | <a name="l00177"></a>00177 <span class="keywordflow">if</span> ( eff < ( 0.3*n ) ) { |
| 158 | <a name="l00178"></a>00178 ind = <a class="code" href="classbdm_1_1PF.html#dc049265b9086cad7071f98d00a2b9af" title="posterior density">est</a>.<a class="code" href="classbdm_1_1eEmp.html#f06ce255de5dbb2313f52ee51f82ba3d" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a>(); |
| 159 | <a name="l00179"></a>00179 <span class="comment">// Resample Bms!</span> |
| 160 | <a name="l00180"></a>00180 |
| 161 | <a name="l00181"></a>00181 <span class="preprocessor"> #pragma omp parallel for</span> |
| 162 | <a name="l00182"></a>00182 <span class="preprocessor"></span> <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| 163 | <a name="l00183"></a>00183 <span class="keywordflow">if</span> ( ind ( i ) !=i ) {<span class="comment">//replace the current Bm by a new one</span> |
| 164 | <a name="l00184"></a>00184 <span class="comment">//fixme this would require new assignment operator</span> |
| 165 | <a name="l00185"></a>00185 <span class="comment">// *Bms[i] = *Bms[ind ( i ) ];</span> |
| 166 | <a name="l00186"></a>00186 |
| 167 | <a name="l00187"></a>00187 <span class="comment">// poor-man's solution: replicate constructor here</span> |
| 168 | <a name="l00188"></a>00188 <span class="comment">// copied from MPF::MPF</span> |
| 169 | <a name="l00189"></a>00189 <span class="keyword">delete</span> Bms[i]; |
| 170 | <a name="l00190"></a>00190 Bms[i] = <span class="keyword">new</span> BM_T ( *Bms[ind ( i ) ] ); <span class="comment">//copy constructor</span> |
| 171 | <a name="l00191"></a>00191 <span class="keyword">const</span> <a class="code" href="classbdm_1_1epdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& pom=Bms[i]->_epdf(); |
| 172 | <a name="l00192"></a>00192 jest.set_elements ( i,1.0/n,&pom ); |
| 173 | <a name="l00193"></a>00193 } |
| 174 | <a name="l00194"></a>00194 }; |
| 175 | <a name="l00195"></a>00195 cout << <span class="charliteral">'.'</span>; |
| 176 | <a name="l00196"></a>00196 } |
| 177 | <a name="l00197"></a>00197 } |
| 178 | <a name="l00198"></a>00198 |
| 179 | <a name="l00199"></a>00199 } |
| 180 | <a name="l00200"></a>00200 <span class="preprocessor">#endif // KF_H</span> |
| 181 | <a name="l00201"></a>00201 <span class="preprocessor"></span> |
| 182 | <a name="l00202"></a>00202 |