<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html><head><meta http-equiv="Content-Type" content="text/html;charset=iso-8859-1">
<title>CProbabilityDensityFunction.h Source File</title>
<link href="doxygen.css" rel="stylesheet" type="text/css">
<link href="tabs.css" rel="stylesheet" type="text/css">
</head><body>
<div align="left"><a href="http://www.mrpt.org/">Main MRPT website</a> > <b>C++ reference</b> </div>
<div align="right">
<a href="index.html"><img border="0" src="mrpt_logo.png" alt="MRPT logo"></a>
</div>
<!-- Generated by Doxygen 1.7.5 -->
<script type="text/javascript">
var searchBox = new SearchBox("searchBox", "search",false,'Search');
</script>
<div id="navrow1" class="tabs">
<ul class="tablist">
<li><a href="index.html"><span>Main Page</span></a></li>
<li><a href="pages.html"><span>Related Pages</span></a></li>
<li><a href="modules.html"><span>Modules</span></a></li>
<li><a href="namespaces.html"><span>Namespaces</span></a></li>
<li><a href="annotated.html"><span>Classes</span></a></li>
<li class="current"><a href="files.html"><span>Files</span></a></li>
<li>
<div id="MSearchBox" class="MSearchBoxInactive">
<div class="left">
<form id="FSearchBox" action="search.php" method="get">
<img id="MSearchSelect" src="search/mag.png" alt=""/>
<input type="text" id="MSearchField" name="query" value="Search" size="20" accesskey="S"
onfocus="searchBox.OnSearchFieldFocus(true)"
onblur="searchBox.OnSearchFieldFocus(false)"/>
</form>
</div><div class="right"></div>
</div>
</li>
</ul>
</div>
<div id="navrow2" class="tabs2">
<ul class="tablist">
<li><a href="files.html"><span>File List</span></a></li>
<li><a href="globals.html"><span>File Members</span></a></li>
</ul>
</div>
<div class="header">
<div class="headertitle">
<div class="title">CProbabilityDensityFunction.h</div> </div>
</div>
<div class="contents">
<a href="_c_probability_density_function_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 CProbabilityDensityFunction_H</span>
<a name="l00029"></a>00029 <span class="preprocessor"></span><span class="preprocessor">#define CProbabilityDensityFunction_H</span>
<a name="l00030"></a>00030 <span class="preprocessor"></span>
<a name="l00031"></a>00031 <span class="preprocessor">#include <<a class="code" href="_c_matrix_d_8h.html">mrpt/math/CMatrixD.h</a>></span>
<a name="l00032"></a>00032 <span class="preprocessor">#include <<a class="code" href="_c_matrix_fixed_numeric_8h.html">mrpt/math/CMatrixFixedNumeric.h</a>></span>
<a name="l00033"></a>00033
<a name="l00034"></a>00034 <span class="keyword">namespace </span>mrpt
<a name="l00035"></a>00035 {
<a name="l00036"></a>00036 <span class="keyword">namespace </span>poses { <span class="keyword">class </span>CPose3D; }
<a name="l00037"></a>00037
<a name="l00038"></a>00038 <span class="keyword">namespace </span>utils
<a name="l00039"></a>00039 {
<a name="l00040"></a>00040 <span class="keyword">using namespace </span>mrpt::math;
<a name="l00041"></a>00041 <span class="comment"></span>
<a name="l00042"></a>00042 <span class="comment"> /** A generic template for probability density distributions (PDFs).</span>
<a name="l00043"></a>00043 <span class="comment"> * This template is used as base for many classes in mrpt::poses</span>
<a name="l00044"></a>00044 <span class="comment"> * Any derived class must implement \a getMean() and a getCovarianceAndMean().</span>
<a name="l00045"></a>00045 <span class="comment"> * Other methods such as \a getMean() or \a getCovariance() are implemented here for convenience.</span>
<a name="l00046"></a>00046 <span class="comment"> * \sa mprt::poses::CPosePDF, mprt::poses::CPose3DPDF, mprt::poses::CPointPDF</span>
<a name="l00047"></a>00047 <span class="comment"> * \ingroup mrpt_base_grp</span>
<a name="l00048"></a>00048 <span class="comment"> */</span>
<a name="l00049"></a>00049 <span class="keyword">template</span> <<span class="keyword">class</span> TDATA, <span class="keywordtype">size_t</span> STATE_LEN>
<a name="l00050"></a>00050 <span class="keyword">class </span>CProbabilityDensityFunction
<a name="l00051"></a>00051 {
<a name="l00052"></a>00052 <span class="keyword">public</span>:
<a name="l00053"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a77a06347b68aa3c08de63c790d88eb12">00053</a> <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">size_t</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a77a06347b68aa3c08de63c790d88eb12" title="The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll)...">state_length</a> = STATE_LEN; <span class="comment">//!< The length of the variable, for example, 3 for a 3D point, 6 for a 3D pose (x y z yaw pitch roll).</span>
<a name="l00054"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ab4d442c6713a2aaac04cf79bee93c251">00054</a> <span class="comment"></span> <span class="keyword">typedef</span> TDATA <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ab4d442c6713a2aaac04cf79bee93c251" title="The type of the state the PDF represents.">type_value</a>; <span class="comment">//!< The type of the state the PDF represents</span>
<a name="l00055"></a>00055 <span class="comment"></span><span class="comment"></span>
<a name="l00056"></a>00056 <span class="comment"> /** Returns the mean, or mathematical expectation of the probability density distribution (PDF).</span>
<a name="l00057"></a>00057 <span class="comment"> * \sa getCovarianceAndMean</span>
<a name="l00058"></a>00058 <span class="comment"> */</span>
<a name="l00059"></a>00059 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#afc168fcbcba4191a0e64fc2a3b7c4c78" title="Returns the mean, or mathematical expectation of the probability density distribution (PDF)...">getMean</a>(TDATA &mean_point) <span class="keyword">const</span> = 0;
<a name="l00060"></a>00060 <span class="comment"></span>
<a name="l00061"></a>00061 <span class="comment"> /** Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.</span>
<a name="l00062"></a>00062 <span class="comment"> * \sa getMean</span>
<a name="l00063"></a>00063 <span class="comment"> */</span>
<a name="l00064"></a>00064 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aef4a7a5d215e4c7e855286ad4a4d1bbe" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceAndMean</a>(<a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html" title="A numeric matrix of compile-time fixed size.">CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN></a> &<a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>,TDATA &mean_point) <span class="keyword">const</span> = 0;
<a name="l00065"></a>00065 <span class="comment"></span>
<a name="l00066"></a>00066 <span class="comment"> /** Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean, both at once.</span>
<a name="l00067"></a>00067 <span class="comment"> * \sa getMean</span>
<a name="l00068"></a>00068 <span class="comment"> */</span>
<a name="l00069"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a8a5db2a590d8fcd23408a3d8a8a1f76c">00069</a> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a8a5db2a590d8fcd23408a3d8a8a1f76c" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceDynAndMean</a>(<a class="code" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html" title="A matrix of dynamic size.">CMatrixDouble</a> &<a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>,TDATA &mean_point)<span class="keyword"> const</span>
<a name="l00070"></a>00070 <span class="keyword"> </span>{
<a name="l00071"></a>00071 <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html" title="A numeric matrix of compile-time fixed size.">CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN></a> C;
<a name="l00072"></a>00072 this-><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aef4a7a5d215e4c7e855286ad4a4d1bbe" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceAndMean</a>(C,mean_point);
<a name="l00073"></a>00073 cov = C; <span class="comment">// Convert to dynamic size matrix</span>
<a name="l00074"></a>00074 }
<a name="l00075"></a>00075 <span class="comment"></span>
<a name="l00076"></a>00076 <span class="comment"> /** Returns the mean, or mathematical expectation of the probability density distribution (PDF).</span>
<a name="l00077"></a>00077 <span class="comment"> * \sa getCovariance</span>
<a name="l00078"></a>00078 <span class="comment"> */</span>
<a name="l00079"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ad6c0c9844ac63db9c793652e4619c549">00079</a> <span class="keyword">inline</span> TDATA <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ad6c0c9844ac63db9c793652e4619c549" title="Returns the mean, or mathematical expectation of the probability density distribution (PDF)...">getMeanVal</a>()<span class="keyword"> const</span>
<a name="l00080"></a>00080 <span class="keyword"> </span>{
<a name="l00081"></a>00081 TDATA p;
<a name="l00082"></a>00082 <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#afc168fcbcba4191a0e64fc2a3b7c4c78" title="Returns the mean, or mathematical expectation of the probability density distribution (PDF)...">getMean</a>(p);
<a name="l00083"></a>00083 <span class="keywordflow">return</span> p;
<a name="l00084"></a>00084 }
<a name="l00085"></a>00085 <span class="comment"></span>
<a name="l00086"></a>00086 <span class="comment"> /** Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)</span>
<a name="l00087"></a>00087 <span class="comment"> * \sa getMean, getCovarianceAndMean</span>
<a name="l00088"></a>00088 <span class="comment"> */</span>
<a name="l00089"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a76a1c94c45614ec2ab8f4b209d126745">00089</a> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a689312caf79ee5268fa913e3fa5c82c0" title="Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)">getCovariance</a>(<a class="code" href="classmrpt_1_1math_1_1_c_matrix_template_numeric.html" title="A matrix of dynamic size.">CMatrixDouble</a> &<a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>)<span class="keyword"> const</span>
<a name="l00090"></a>00090 <span class="keyword"> </span>{
<a name="l00091"></a>00091 TDATA p;
<a name="l00092"></a>00092 this-><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a8a5db2a590d8fcd23408a3d8a8a1f76c" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceDynAndMean</a>(cov,p);
<a name="l00093"></a>00093 }
<a name="l00094"></a>00094 <span class="comment"></span>
<a name="l00095"></a>00095 <span class="comment"> /** Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)</span>
<a name="l00096"></a>00096 <span class="comment"> * \sa getMean, getCovarianceAndMean</span>
<a name="l00097"></a>00097 <span class="comment"> */</span>
<a name="l00098"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a9ac7187b742c121c3338cb767b7994ba">00098</a> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a689312caf79ee5268fa913e3fa5c82c0" title="Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)">getCovariance</a>(<a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html" title="A numeric matrix of compile-time fixed size.">CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN></a> &<a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>)<span class="keyword"> const</span>
<a name="l00099"></a>00099 <span class="keyword"> </span>{
<a name="l00100"></a>00100 TDATA p;
<a name="l00101"></a>00101 this-><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aef4a7a5d215e4c7e855286ad4a4d1bbe" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceAndMean</a>(cov,p);
<a name="l00102"></a>00102 }
<a name="l00103"></a>00103 <span class="comment"></span>
<a name="l00104"></a>00104 <span class="comment"> /** Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)</span>
<a name="l00105"></a>00105 <span class="comment"> * \sa getMean</span>
<a name="l00106"></a>00106 <span class="comment"> */</span>
<a name="l00107"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a689312caf79ee5268fa913e3fa5c82c0">00107</a> <span class="keyword">inline</span> <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html" title="A numeric matrix of compile-time fixed size.">CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN></a> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a689312caf79ee5268fa913e3fa5c82c0" title="Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)">getCovariance</a>()<span class="keyword"> const</span>
<a name="l00108"></a>00108 <span class="keyword"> </span>{
<a name="l00109"></a>00109 <a class="code" href="classmrpt_1_1math_1_1_c_matrix_fixed_numeric.html" title="A numeric matrix of compile-time fixed size.">CMatrixFixedNumeric<double,STATE_LEN,STATE_LEN></a> <a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>;
<a name="l00110"></a>00110 TDATA p;
<a name="l00111"></a>00111 this-><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aef4a7a5d215e4c7e855286ad4a4d1bbe" title="Returns an estimate of the pose covariance matrix (STATE_LENxSTATE_LEN cov matrix) and the mean...">getCovarianceAndMean</a>(cov,p);
<a name="l00112"></a>00112 <span class="keywordflow">return</span> <a class="code" href="namespacemrpt_1_1math.html#a43f4e051fc574fd75b6800ad4fb25037" title="Computes the covariance matrix from a list of samples in an NxM matrix, where each row is a sample...">cov</a>;
<a name="l00113"></a>00113 }
<a name="l00114"></a>00114 <span class="comment"></span>
<a name="l00115"></a>00115 <span class="comment"> /** Save PDF's particles to a text file. See derived classes for more information about the format of generated files.</span>
<a name="l00116"></a>00116 <span class="comment"> */</span>
<a name="l00117"></a>00117 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a960b9e93abcf834b4bb5ce5f880b2570" title="Save PDF's particles to a text file.">saveToTextFile</a>(<span class="keyword">const</span> <a class="code" href="classstd_1_1string.html" title="STL class.">std::string</a> &file) <span class="keyword">const</span> = 0;
<a name="l00118"></a>00118 <span class="comment"></span>
<a name="l00119"></a>00119 <span class="comment"> /** Draws a single sample from the distribution</span>
<a name="l00120"></a>00120 <span class="comment"> */</span>
<a name="l00121"></a>00121 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ae8879d10e9d7a6c94211dd0ffffc4c9d" title="Draws a single sample from the distribution.">drawSingleSample</a>( TDATA &outPart ) <span class="keyword">const</span> = 0;
<a name="l00122"></a>00122 <span class="comment"></span>
<a name="l00123"></a>00123 <span class="comment"> /** Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors, where each row contains a (x,y,z,yaw,pitch,roll) datum.</span>
<a name="l00124"></a>00124 <span class="comment"> * This base method just call N times to drawSingleSample, but derived classes should implemented optimized method for each particular PDF.</span>
<a name="l00125"></a>00125 <span class="comment"> */</span>
<a name="l00126"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aa437cf2c11cb0e937e851a0f498a4fb2">00126</a> <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aa437cf2c11cb0e937e851a0f498a4fb2" title="Draws a number of samples from the distribution, and saves as a list of 1xSTATE_LEN vectors...">drawManySamples</a>( <span class="keywordtype">size_t</span> N, <a class="code" href="classstd_1_1vector.html">std::vector<vector_double></a> & outSamples )<span class="keyword"> const</span>
<a name="l00127"></a>00127 <span class="keyword"> </span>{
<a name="l00128"></a>00128 outSamples.resize(N);
<a name="l00129"></a>00129 TDATA pnt;
<a name="l00130"></a>00130 <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i=0;i<N;i++)
<a name="l00131"></a>00131 {
<a name="l00132"></a>00132 this-><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#ae8879d10e9d7a6c94211dd0ffffc4c9d" title="Draws a single sample from the distribution.">drawSingleSample</a>(pnt);
<a name="l00133"></a>00133 pnt.getAsVector(outSamples[i]);
<a name="l00134"></a>00134 }
<a name="l00135"></a>00135 }
<a name="l00136"></a>00136 <span class="comment"></span>
<a name="l00137"></a>00137 <span class="comment"> /** This can be used to convert a PDF from local coordinates to global, providing the point (newReferenceBase) from which</span>
<a name="l00138"></a>00138 <span class="comment"> * "to project" the current pdf. Result PDF substituted the currently stored one in the object.</span>
<a name="l00139"></a>00139 <span class="comment"> */</span>
<a name="l00140"></a>00140 <span class="keyword">virtual</span> <span class="keywordtype">void</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#aac79fa433163e2ffe0cb3c12d02e61ba" title="This can be used to convert a PDF from local coordinates to global, providing the point (newReference...">changeCoordinatesReference</a>( <span class="keyword">const</span> <a class="code" href="classmrpt_1_1poses_1_1_c_pose3_d.html" title="A class used to store a 3D pose (a 3D translation + a rotation in 3D).">mrpt::poses::CPose3D</a> &newReferenceBase ) = 0;
<a name="l00141"></a>00141 <span class="comment"></span>
<a name="l00142"></a>00142 <span class="comment"> /** Compute the entropy of the estimated covariance matrix.</span>
<a name="l00143"></a>00143 <span class="comment"> * \sa http://en.wikipedia.org/wiki/Multivariate_normal_distribution#Entropy</span>
<a name="l00144"></a>00144 <span class="comment"> */</span>
<a name="l00145"></a><a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a311648912f182acf9fc0896208492216">00145</a> <span class="keyword">inline</span> <span class="keywordtype">double</span> <a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a311648912f182acf9fc0896208492216" title="Compute the entropy of the estimated covariance matrix.">getCovarianceEntropy</a>()<span class="keyword"> const</span>
<a name="l00146"></a>00146 <span class="keyword"> </span>{
<a name="l00147"></a>00147 <span class="keyword">static</span> <span class="keyword">const</span> <span class="keywordtype">double</span> ln_2PI= 1.8378770664093454835606594728112;
<a name="l00148"></a>00148 <span class="keywordflow">return</span> 0.5*( STATE_LEN + STATE_LEN * ln_2PI + log( std::max(<a class="code" href="classmrpt_1_1utils_1_1_c_probability_density_function.html#a689312caf79ee5268fa913e3fa5c82c0" title="Returns the estimate of the covariance matrix (STATE_LEN x STATE_LEN covariance matrix)">getCovariance</a>().<a class="code" href="eigen__plugins_8h.html#a96d156d50856525aa2e9e4e106012f78">det</a>(), std::numeric_limits<double>::epsilon() ) ) );
<a name="l00149"></a>00149 }
<a name="l00150"></a>00150
<a name="l00151"></a>00151 }; <span class="comment">// End of class def.</span>
<a name="l00152"></a>00152
<a name="l00153"></a>00153 } <span class="comment">// End of namespace</span>
<a name="l00154"></a>00154 } <span class="comment">// End of namespace</span>
<a name="l00155"></a>00155
<a name="l00156"></a>00156 <span class="preprocessor">#endif</span>
</pre></div></div>
</div>
<br><hr><br> <table border="0" width="100%"> <tr> <td> Page generated by <a href="http://www.doxygen.org" target="_blank">Doxygen 1.7.5</a> for MRPT 0.9.5 SVN: at Sun Sep 25 17:20:18 UTC 2011</td><td></td> <td width="100"> </td> <td width="150"> </td></tr> </table> </body></html>
