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<div class="title">CRejectionSamplingCapable.h</div> </div>
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<a href="_c_rejection_sampling_capable_8h.html">Go to the documentation of this file.</a><div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/* +---------------------------------------------------------------------------+</span>
<a name="l00002"></a>00002 <span class="comment"> | The Mobile Robot Programming Toolkit (MRPT) C++ library |</span>
<a name="l00003"></a>00003 <span class="comment"> | |</span>
<a name="l00004"></a>00004 <span class="comment"> | http://www.mrpt.org/ |</span>
<a name="l00005"></a>00005 <span class="comment"> | |</span>
<a name="l00006"></a>00006 <span class="comment"> | Copyright (C) 2005-2011 University of Malaga |</span>
<a name="l00007"></a>00007 <span class="comment"> | |</span>
<a name="l00008"></a>00008 <span class="comment"> | This software was written by the Machine Perception and Intelligent |</span>
<a name="l00009"></a>00009 <span class="comment"> | Robotics Lab, University of Malaga (Spain). |</span>
<a name="l00010"></a>00010 <span class="comment"> | Contact: Jose-Luis Blanco <jlblanco@ctima.uma.es> |</span>
<a name="l00011"></a>00011 <span class="comment"> | |</span>
<a name="l00012"></a>00012 <span class="comment"> | This file is part of the MRPT project. |</span>
<a name="l00013"></a>00013 <span class="comment"> | |</span>
<a name="l00014"></a>00014 <span class="comment"> | MRPT is free software: you can redistribute it and/or modify |</span>
<a name="l00015"></a>00015 <span class="comment"> | it under the terms of the GNU General Public License as published by |</span>
<a name="l00016"></a>00016 <span class="comment"> | the Free Software Foundation, either version 3 of the License, or |</span>
<a name="l00017"></a>00017 <span class="comment"> | (at your option) any later version. |</span>
<a name="l00018"></a>00018 <span class="comment"> | |</span>
<a name="l00019"></a>00019 <span class="comment"> | MRPT is distributed in the hope that it will be useful, |</span>
<a name="l00020"></a>00020 <span class="comment"> | but WITHOUT ANY WARRANTY; without even the implied warranty of |</span>
<a name="l00021"></a>00021 <span class="comment"> | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |</span>
<a name="l00022"></a>00022 <span class="comment"> | GNU General Public License for more details. |</span>
<a name="l00023"></a>00023 <span class="comment"> | |</span>
<a name="l00024"></a>00024 <span class="comment"> | You should have received a copy of the GNU General Public License |</span>
<a name="l00025"></a>00025 <span class="comment"> | along with MRPT. If not, see <http://www.gnu.org/licenses/>. |</span>
<a name="l00026"></a>00026 <span class="comment"> | |</span>
<a name="l00027"></a>00027 <span class="comment"> +---------------------------------------------------------------------------+ */</span>
<a name="l00028"></a>00028 <span class="preprocessor">#ifndef CRejectionSamplingCapable_H</span>
<a name="l00029"></a>00029 <span class="preprocessor"></span><span class="preprocessor">#define CRejectionSamplingCapable_H</span>
<a name="l00030"></a>00030 <span class="preprocessor"></span>
<a name="l00031"></a>00031 <span class="preprocessor">#include <<a class="code" href="utils__defs_8h.html">mrpt/utils/utils_defs.h</a>></span>
<a name="l00032"></a>00032 <span class="preprocessor">#include <<a class="code" href="_c_probability_particle_8h.html">mrpt/bayes/CProbabilityParticle.h</a>></span>
<a name="l00033"></a>00033 <span class="preprocessor">#include <<a class="code" href="random_8h.html">mrpt/random.h</a>></span>
<a name="l00034"></a>00034
<a name="l00035"></a>00035 <span class="keyword">namespace </span>mrpt
<a name="l00036"></a>00036 {<span class="comment"></span>
<a name="l00037"></a>00037 <span class="comment">/// \ingroup mrpt_bayes_grp</span>
<a name="l00038"></a>00038 <span class="comment"></span><span class="keyword">namespace </span>bayes
<a name="l00039"></a>00039 {<span class="comment"></span>
<a name="l00040"></a>00040 <span class="comment"> /** A base class for implementing rejection sampling in a generic state space.</span>
<a name="l00041"></a>00041 <span class="comment"> * See the main method CRejectionSamplingCapable::rejectionSampling</span>
<a name="l00042"></a>00042 <span class="comment"> * To use this class, create your own class as a child of this one and implement the desired</span>
<a name="l00043"></a>00043 <span class="comment"> * virtual methods, and add any required internal data.</span>
<a name="l00044"></a>00044 <span class="comment"> * \ingroup mrpt_bayes_grp</span>
<a name="l00045"></a>00045 <span class="comment"> */</span>
<a name="l00046"></a>00046 <span class="keyword">template</span> <<span class="keyword">class</span> TStateSpace>
<a name="l00047"></a>00047 <span class="keyword">class </span>CRejectionSamplingCapable
<a name="l00048"></a>00048 {
<a name="l00049"></a>00049 <span class="keyword">public</span>:
<a name="l00050"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#a6c35abe1d7247665e9e7431aedee9e4f">00050</a> <span class="keyword">typedef</span> <a class="code" href="structmrpt_1_1bayes_1_1_c_probability_particle.html" title="A template class for holding a the data and the weight of a particle.">CProbabilityParticle<TStateSpace></a> <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#a6c35abe1d7247665e9e7431aedee9e4f">TParticle</a>;
<a name="l00051"></a>00051 <span class="comment"></span>
<a name="l00052"></a>00052 <span class="comment"> /** Virtual destructor</span>
<a name="l00053"></a>00053 <span class="comment"> */</span>
<a name="l00054"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#adfb6b788cf338e5f2e3c72566ece1efc">00054</a> <span class="keyword">virtual</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#adfb6b788cf338e5f2e3c72566ece1efc" title="Virtual destructor.">~CRejectionSamplingCapable</a>()
<a name="l00055"></a>00055 {
<a name="l00056"></a>00056 }
<a name="l00057"></a>00057 <span class="comment"></span>
<a name="l00058"></a>00058 <span class="comment"> /** Generates a set of N independent samples via rejection sampling.</span>
<a name="l00059"></a>00059 <span class="comment"> * \param desiredSamples The number of desired samples to generate</span>
<a name="l00060"></a>00060 <span class="comment"> * \param outSamples The output samples.</span>
<a name="l00061"></a>00061 <span class="comment"> * \param timeoutTrials The maximum number of rejection trials for each generated sample (i.e. the maximum number of iterations). This can be used to set a limit to the time complexity of the algorithm for difficult probability densities.</span>
<a name="l00062"></a>00062 <span class="comment"> * All will have equal importance weights (a property of rejection sampling), although those samples</span>
<a name="l00063"></a>00063 <span class="comment"> * generated at timeout will have a different importance weights.</span>
<a name="l00064"></a>00064 <span class="comment"> */</span>
<a name="l00065"></a><a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#af0597f8c63106e2a4b64365147cf931f">00065</a> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#af0597f8c63106e2a4b64365147cf931f" title="Generates a set of N independent samples via rejection sampling.">rejectionSampling</a>(
<a name="l00066"></a>00066 <span class="keywordtype">size_t</span> desiredSamples,
<a name="l00067"></a>00067 <a class="code" href="classstd_1_1vector.html" title="STL class.">std::vector<TParticle></a> &outSamples,
<a name="l00068"></a>00068 <span class="keywordtype">size_t</span> timeoutTrials = 1000)
<a name="l00069"></a>00069 {
<a name="l00070"></a>00070 <a class="code" href="mrpt__macros_8h.html#a45b840af519f33816311acdbb28d7c10">MRPT_START</a>
<a name="l00071"></a>00071
<a name="l00072"></a>00072 TStateSpace x;
<a name="l00073"></a>00073 <span class="keyword">typename</span> std<a class="code" href="classstd_1_1vector_1_1iterator.html" title="STL iterator class.">::vector<TParticle>::iterator</a> it;
<a name="l00074"></a>00074
<a name="l00075"></a>00075 <span class="comment">// Set output size:</span>
<a name="l00076"></a>00076 <span class="keywordflow">if</span> ( outSamples.size() != desiredSamples )
<a name="l00077"></a>00077 {
<a name="l00078"></a>00078 <span class="comment">// Free old memory:</span>
<a name="l00079"></a>00079 <span class="keywordflow">for</span> (it = outSamples.begin();it!=outSamples.end();it++)
<a name="l00080"></a>00080 <span class="keyword">delete</span> (it->d);
<a name="l00081"></a>00081 outSamples.clear();
<a name="l00082"></a>00082
<a name="l00083"></a>00083 <span class="comment">// Reserve new memory:</span>
<a name="l00084"></a>00084 outSamples.resize( desiredSamples );
<a name="l00085"></a>00085 <span class="keywordflow">for</span> (it = outSamples.begin();it!=outSamples.end();it++)
<a name="l00086"></a>00086 it->d = <span class="keyword">new</span> TStateSpace;
<a name="l00087"></a>00087 }
<a name="l00088"></a>00088
<a name="l00089"></a>00089 <span class="comment">// Rejection sampling loop:</span>
<a name="l00090"></a>00090 <span class="keywordtype">double</span> acceptanceProb;
<a name="l00091"></a>00091 <span class="keywordflow">for</span> (it = outSamples.begin();it!=outSamples.end();it++)
<a name="l00092"></a>00092 {
<a name="l00093"></a>00093 <span class="keywordtype">size_t</span> timeoutCount = 0;
<a name="l00094"></a>00094 <span class="keywordtype">double</span> bestLik = -1e250;
<a name="l00095"></a>00095 TStateSpace bestVal;
<a name="l00096"></a>00096 <span class="keywordflow">do</span>
<a name="l00097"></a>00097 {
<a name="l00098"></a>00098 <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#addc288e07f0bfea667f0b30c235007d2" title="Generates one sample, drawing from some proposal distribution.">RS_drawFromProposal</a>( *it->d );
<a name="l00099"></a>00099 acceptanceProb = <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#a6cf91003f69f1cb70d8f0b18f3a49b79" title="Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the st...">RS_observationLikelihood</a>( *it->d );
<a name="l00100"></a>00100 <a class="code" href="mrpt__macros_8h.html#a47eb5a445c2bf3d9190396510ea9683e">ASSERT_</a>(acceptanceProb>=0 && acceptanceProb<=1);
<a name="l00101"></a>00101 <span class="keywordflow">if</span> (acceptanceProb>bestLik)
<a name="l00102"></a>00102 {
<a name="l00103"></a>00103 bestLik = acceptanceProb;
<a name="l00104"></a>00104 bestVal = *it->d;
<a name="l00105"></a>00105 }
<a name="l00106"></a>00106 } <span class="keywordflow">while</span> ( acceptanceProb < <a class="code" href="namespacemrpt_1_1random.html#a4743bfa8fcb282b6f5d66395ccabaa73" title="A static instance of a CRandomGenerator class, for use in single-thread applications.">mrpt::random::randomGenerator</a>.drawUniform(0.0,0.999) &&
<a name="l00107"></a>00107 (++timeoutCount)<timeoutTrials );
<a name="l00108"></a>00108
<a name="l00109"></a>00109 <span class="comment">// Save weights:</span>
<a name="l00110"></a>00110 <span class="keywordflow">if</span> (timeoutCount>=timeoutTrials)
<a name="l00111"></a>00111 {
<a name="l00112"></a>00112 it->log_w = log(bestLik);
<a name="l00113"></a>00113 *it->d = bestVal;
<a name="l00114"></a>00114 }
<a name="l00115"></a>00115 <span class="keywordflow">else</span>
<a name="l00116"></a>00116 {
<a name="l00117"></a>00117 it->log_w = 0; <span class="comment">// log(1.0);</span>
<a name="l00118"></a>00118 }
<a name="l00119"></a>00119 } <span class="comment">// end for it</span>
<a name="l00120"></a>00120
<a name="l00121"></a>00121 <a class="code" href="mrpt__macros_8h.html#a88a917260793b56abd83ad2a0d849eb1">MRPT_END</a>
<a name="l00122"></a>00122 }
<a name="l00123"></a>00123
<a name="l00124"></a>00124 <span class="keyword">protected</span>:<span class="comment"></span>
<a name="l00125"></a>00125 <span class="comment"> /** Generates one sample, drawing from some proposal distribution.</span>
<a name="l00126"></a>00126 <span class="comment"> */</span>
<a name="l00127"></a>00127 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#addc288e07f0bfea667f0b30c235007d2" title="Generates one sample, drawing from some proposal distribution.">RS_drawFromProposal</a>( TStateSpace &outSample ) = 0;
<a name="l00128"></a>00128 <span class="comment"></span>
<a name="l00129"></a>00129 <span class="comment"> /** Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the state space (values in the range [0,1]).</span>
<a name="l00130"></a>00130 <span class="comment"> */</span>
<a name="l00131"></a>00131 <span class="keyword">virtual</span> <span class="keywordtype">double</span> <a class="code" href="classmrpt_1_1bayes_1_1_c_rejection_sampling_capable.html#a6cf91003f69f1cb70d8f0b18f3a49b79" title="Returns the NORMALIZED observation likelihood (linear, not exponential!!!) at a given point of the st...">RS_observationLikelihood</a>( <span class="keyword">const</span> TStateSpace &x) = 0;
<a name="l00132"></a>00132
<a name="l00133"></a>00133 }; <span class="comment">// End of class def.</span>
<a name="l00134"></a>00134
<a name="l00135"></a>00135 } <span class="comment">// End of namespace</span>
<a name="l00136"></a>00136 } <span class="comment">// End of namespace</span>
<a name="l00137"></a>00137
<a name="l00138"></a>00138 <span class="preprocessor">#endif</span>
</pre></div></div>
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