| 26 | | <a name="l00022"></a>00022 <span class="keyword">enum</span> RESAMPLING_METHOD { MULTINOMIAL = 0, STRATIFIED = 1, SYSTEMATIC = 3 }; |
| 27 | | <a name="l00023"></a>00023 |
| 28 | | <a name="l00029"></a><a class="code" href="classPF.html">00029</a> <span class="keyword">class </span><a class="code" href="classPF.html" title="A Particle Filter prototype.">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> { |
| 29 | | <a name="l00030"></a>00030 <span class="keyword">protected</span>: |
| 30 | | <a name="l00031"></a>00031 <span class="keywordtype">int</span> n; <span class="comment">//number of particles</span> |
| 31 | | <a name="l00032"></a>00032 vec w; <span class="comment">//particle weights</span> |
| 32 | | <a name="l00033"></a>00033 Uniform_RNG URNG; <span class="comment">//used for resampling</span> |
| 33 | | <a name="l00034"></a>00034 |
| 34 | | <a name="l00035"></a>00035 <span class="keyword">public</span>: |
| 35 | | <a name="l00037"></a>00037 ivec <a class="code" href="classPF.html#a0e26b2f6a5884aca49122f3e4f0cf19" title="Returns indexes of particles that should be resampled. The ordering MUST guarantee...">resample</a>(RESAMPLING_METHOD method = SYSTEMATIC); |
| 36 | | <a name="l00038"></a>00038 <a class="code" href="classPF.html" title="A Particle Filter prototype.">PF</a> (vec w); |
| 37 | | <a name="l00039"></a>00039 <span class="comment">//TODO remove or implement bayes()!</span> |
| 38 | | <a name="l00040"></a>00040 <span class="keywordtype">void</span> bayes(<span class="keyword">const</span> vec &dt, <span class="keywordtype">bool</span> evell){}; |
| 39 | | <a name="l00041"></a>00041 }; |
| 40 | | <a name="l00042"></a>00042 |
| 41 | | <a name="l00049"></a><a class="code" href="classTrivialPF.html">00049</a> <span class="keyword">class </span><a class="code" href="classTrivialPF.html" title="Trivial particle filter with proposal density that is not conditioned on the data...">TrivialPF</a> : <span class="keyword">public</span> <a class="code" href="classPF.html" title="A Particle Filter prototype.">PF</a> { |
| 42 | | <a name="l00050"></a>00050 Array<vec> ptcls; |
| 43 | | <a name="l00051"></a>00051 |
| 44 | | <a name="l00052"></a>00052 <span class="keywordtype">bool</span> is_proposal; |
| 45 | | <a name="l00053"></a>00053 <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> *prop; |
| 46 | | <a name="l00054"></a>00054 <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *par; |
| 47 | | <a name="l00055"></a>00055 <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> *obs; |
| 48 | | <a name="l00056"></a>00056 |
| 49 | | <a name="l00057"></a>00057 <span class="keyword">public</span>: |
| 50 | | <a name="l00058"></a>00058 <a class="code" href="classTrivialPF.html" title="Trivial particle filter with proposal density that is not conditioned on the data...">TrivialPF</a>(<a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs, <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> &prop, <span class="keywordtype">int</span> n0); |
| 51 | | <a name="l00059"></a>00059 <a class="code" href="classTrivialPF.html" title="Trivial particle filter with proposal density that is not conditioned on the data...">TrivialPF</a>(<a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs, <span class="keywordtype">int</span> n0); |
| 52 | | <a name="l00060"></a>00060 <span class="keywordtype">void</span> bayes(<span class="keyword">const</span> vec &dt, <span class="keywordtype">bool</span> <a class="code" href="classBM.html#bf6fb59b30141074f8ee1e2f43d03129" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a>); |
| 53 | | <a name="l00061"></a>00061 }; |
| 54 | | <a name="l00062"></a>00062 |
| 55 | | <a name="l00063"></a>00063 <span class="keyword">class </span>MPF : <span class="keyword">public</span> <a class="code" href="classTrivialPF.html" title="Trivial particle filter with proposal density that is not conditioned on the data...">TrivialPF</a> { |
| 56 | | <a name="l00064"></a>00064 Array<BM> Bms; |
| 57 | | <a name="l00065"></a>00065 <span class="keyword">public</span>: |
| 58 | | <a name="l00066"></a>00066 MPF(<a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> &B, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &prop, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &obs, <a class="code" href="classmpdf.html" title="Conditional probability density, e.g. modeling some dependencies.">mpdf</a> &par); |
| 59 | | <a name="l00067"></a>00067 <span class="keywordtype">void</span> bayes(vec &dt); |
| 60 | | <a name="l00068"></a>00068 }; |
| 61 | | <a name="l00069"></a>00069 |
| 62 | | <a name="l00070"></a>00070 <span class="preprocessor">#endif // KF_H</span> |
| 63 | | <a name="l00071"></a>00071 <span class="preprocessor"></span> |
| 64 | | <a name="l00072"></a>00072 |
| 65 | | </pre></div><hr size="1"><address style="text-align: right;"><small>Generated on Mon Feb 18 21:48:39 2008 for mixpp by |
| | 26 | <a name="l00027"></a><a class="code" href="classPF.html">00027</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> { |
| | 27 | <a name="l00028"></a>00028 <span class="keyword">protected</span>: |
| | 28 | <a name="l00030"></a><a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280">00030</a> <span class="keywordtype">int</span> <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>; |
| | 29 | <a name="l00032"></a><a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0">00032</a> <a class="code" href="classeEmp.html" title="Weighted empirical density.">eEmp</a> <a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0" title="posterior density">ePdf</a>; |
| | 30 | <a name="l00034"></a><a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0">00034</a> vec &<a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a>; |
| | 31 | <a name="l00036"></a><a class="code" href="classPF.html#361743a0b5b89de1a29e91d1343b2565">00036</a> Array<vec> &<a class="code" href="classPF.html#361743a0b5b89de1a29e91d1343b2565" title="pointer into eEmp ">samples</a>; |
| | 32 | <a name="l00038"></a><a class="code" href="classPF.html#d92ac103f88f8c21e197e90af5695a09">00038</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>; |
| | 33 | <a name="l00040"></a><a class="code" href="classPF.html#dd0a687a4515333d6809147335854e77">00040</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>; |
| | 34 | <a name="l00041"></a>00041 <span class="keyword">public</span>: |
| | 35 | <a name="l00042"></a>00042 <a class="code" href="classPF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">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> <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a> ) :<a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a>(rv0), |
| | 36 | <a name="l00043"></a>00043 n ( 1 ),<a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0" title="posterior density">ePdf</a> ( rv0 ),<a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a> ( <a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0" title="posterior density">ePdf</a>._w() ),<a class="code" href="classPF.html#361743a0b5b89de1a29e91d1343b2565" title="pointer into eEmp ">samples</a> ( <a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0" title="posterior density">ePdf</a>._samples() ), |
| | 37 | <a name="l00044"></a>00044 <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 ) {}; |
| | 38 | <a name="l00045"></a>00045 <span class="comment">// void set_parametres(mpdf &par0, mpdf &obs0) {par=&par0;obs=&obs0;};</span> |
| | 39 | <a name="l00046"></a>00046 <span class="keywordtype">void</span> set_est ( <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 ); |
| | 40 | <a name="l00047"></a>00047 <span class="comment">//TODO remove or implement bayes()!</span> |
| | 41 | <a name="l00048"></a>00048 <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 ); |
| | 42 | <a name="l00049"></a>00049 }; |
| | 43 | <a name="l00050"></a>00050 |
| | 44 | <a name="l00057"></a>00057 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| | 45 | <a name="l00058"></a><a class="code" href="classMPF.html">00058</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> { |
| | 46 | <a name="l00059"></a>00059 BM_T* Bms[1000]; |
| | 47 | <a name="l00060"></a>00060 <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvc; |
| | 48 | <a name="l00061"></a>00061 <a class="code" href="classemix.html" title="Weighted mixture of epdfs with external owned components.">emix</a> est; |
| | 49 | <a name="l00062"></a>00062 <span class="keyword">public</span>: |
| | 50 | <a name="l00064"></a><a class="code" href="classMPF.html#827a66609cf69a832535d52233f76fa0">00064</a> <a class="code" href="classMPF.html#827a66609cf69a832535d52233f76fa0" title="Default constructor.">MPF</a> ( <span class="keyword">const</span> <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> &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> <a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>, <span class="keyword">const</span> BM_T &BMcond0 ) : |
| | 51 | <a name="l00065"></a>00065 <a class="code" href="classPF.html" title="Trivial particle filter with proposal density equal to parameter evolution model...">PF</a> ( rv0,par0,obs0,n ), est(rv0,<a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a>) { |
| | 52 | <a name="l00066"></a>00066 <span class="comment">//</span> |
| | 53 | <a name="l00067"></a>00067 <span class="keywordflow">if</span> (n>1000) it_error(<span class="stringliteral">"increase 1000 here!"</span>); |
| | 54 | <a name="l00068"></a>00068 <span class="keywordflow">for</span> ( <span class="keywordtype">int</span> i=0;i<n;i++ ) { |
| | 55 | <a name="l00069"></a>00069 Bms[i] = <span class="keyword">new</span> BM_T(BMcond0); <span class="comment">//copy constructor</span> |
| | 56 | <a name="l00070"></a>00070 <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& pom=Bms[i]->_epdf(); |
| | 57 | <a name="l00071"></a>00071 est.<a class="code" href="classemix.html#599366d678152cfb0703da697b6b1de1">set_parameters</a>(i,&pom); |
| | 58 | <a name="l00072"></a>00072 } |
| | 59 | <a name="l00073"></a>00073 }; |
| | 60 | <a name="l00074"></a>00074 ~<a class="code" href="classMPF.html" title="Marginalized Particle filter.">MPF</a>() { |
| | 61 | <a name="l00075"></a>00075 } |
| | 62 | <a name="l00076"></a>00076 <span class="keywordtype">void</span> <a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623" title="Incremental Bayes rule.">bayes</a> (<span class="keyword">const</span> vec &dt ); |
| | 63 | <a name="l00077"></a><a class="code" href="classMPF.html#549e08268a46a250f21a33d06f19276a">00077</a> <a class="code" href="classepdf.html" title="Probability density function with numerical statistics, e.g. posterior density.">epdf</a>& <a class="code" href="classMPF.html#549e08268a46a250f21a33d06f19276a" title="Returns a pointer to the epdf representing posterior density on parameters. Use with...">_epdf</a>(){<span class="keywordflow">return</span> est;} |
| | 64 | <a name="l00078"></a>00078 }; |
| | 65 | <a name="l00079"></a>00079 |
| | 66 | <a name="l00080"></a>00080 <span class="keyword">template</span><<span class="keyword">class</span> BM_T> |
| | 67 | <a name="l00081"></a><a class="code" href="classMPF.html#55daf8e4b6553dd9f47c692de7931623">00081</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) { |
| | 68 | <a name="l00082"></a>00082 <span class="keywordtype">int</span> i; |
| | 69 | <a name="l00083"></a>00083 vec lls(<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>); |
| | 70 | <a name="l00084"></a>00084 ivec ind; |
| | 71 | <a name="l00085"></a>00085 <span class="keywordtype">double</span> mlls=-std::numeric_limits<double>::infinity(), sum=0.0; |
| | 72 | <a name="l00086"></a>00086 |
| | 73 | <a name="l00087"></a>00087 <span class="keywordflow">for</span> ( i=0;i<<a class="code" href="classPF.html#2c2f44ed7a4eaa42e07bdb58d503f280" title="number of particles;">n</a>;i++ ) { |
| | 74 | <a name="l00088"></a>00088 <span class="comment">//generate new samples from paramater evolution model;</span> |
| | 75 | <a name="l00089"></a>00089 <a class="code" href="classPF.html#361743a0b5b89de1a29e91d1343b2565" 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#c20c796f8d0a201f0897299150e45a41" title="Returns the required moment of the epdf.">samplecond</a>( <a class="code" href="classPF.html#361743a0b5b89de1a29e91d1343b2565" title="pointer into eEmp ">samples</a>( i ), lls(i) ); |
| | 76 | <a name="l00090"></a>00090 <span class="keywordflow">if</span> (lls(i)>mlls) mlls=lls(i); <span class="comment">//find maximum</span> |
| | 77 | <a name="l00091"></a>00091 } |
| | 78 | <a name="l00092"></a>00092 <span class="comment">// compute weights </span> |
| | 79 | <a name="l00093"></a>00093 <span class="keywordflow">for</span> ( i=0;i<n;i++ ) { |
| | 80 | <a name="l00094"></a>00094 <a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a>(i) *= exp( lls(i) - mlls); <span class="comment">// multiply w by likelihood</span> |
| | 81 | <a name="l00095"></a>00095 } |
| | 82 | <a name="l00096"></a>00096 <span class="comment">//renormalize</span> |
| | 83 | <a name="l00097"></a>00097 <span class="keywordflow">for</span> ( i=0;i<n;i++ ){sum+=<a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a>( i );}; |
| | 84 | <a name="l00098"></a>00098 <a class="code" href="classPF.html#a97d12da4d1832c0b0c6ec5877f921f0" title="pointer into eEmp ">w</a>( i ) /=sum; <span class="comment">//?</span> |
| | 85 | <a name="l00099"></a>00099 |
| | 86 | <a name="l00100"></a>00100 ind = <a class="code" href="classPF.html#a2ac56d1e3ffbb4ff0b3f02e6399deb0" title="posterior density">ePdf</a>.<a class="code" href="classeEmp.html#77268292fc4465cb73ddbfb1f2932a59" title="Function performs resampling, i.e. removal of low-weight samples and duplication...">resample</a>(); |
| | 87 | <a name="l00101"></a>00101 |
| | 88 | <a name="l00102"></a>00102 } |
| | 89 | <a name="l00103"></a>00103 |
| | 90 | <a name="l00104"></a>00104 <span class="preprocessor">#endif // KF_H</span> |
| | 91 | <a name="l00105"></a>00105 <span class="preprocessor"></span> |
| | 92 | <a name="l00106"></a>00106 |
| | 93 | </pre></div><hr size="1"><address style="text-align: right;"><small>Generated on Thu Feb 28 16:54:40 2008 for mixpp by |
