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11/13/08 19:59:21 (16 years ago)
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smidl
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dokumentace

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  • doc/html/libKF_8h-source.html

    r181 r210  
    8686<a name="l00121"></a>00121         <span class="keywordtype">void</span> <a class="code" href="classKalman.html#7750ffd73f261828a32c18aaeb65c75c" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    8787<a name="l00123"></a><a class="code" href="classKalman.html#67cccaf1c4dcdcd1df110e15ef326bfe">00123</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>&amp; <a class="code" href="classKalman.html#67cccaf1c4dcdcd1df110e15ef326bfe" title="access function">_epdf</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>;} 
    88 <a name="l00125"></a><a class="code" href="classKalman.html#980fcd41c6c548c5da7b8b67c8e6da79">00125</a>         mat&amp; <a class="code" href="classKalman.html#980fcd41c6c548c5da7b8b67c8e6da79" title="access function">__K</a>() {<span class="keywordflow">return</span> <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>;} 
    89 <a name="l00127"></a><a class="code" href="classKalman.html#ac9540f3850b74d89a5fe4db6fc358ce">00127</a>         vec <a class="code" href="classKalman.html#ac9540f3850b74d89a5fe4db6fc358ce" title="access function">_dP</a>() {<span class="keywordflow">return</span> <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>-&gt;getD();} 
    90 <a name="l00128"></a>00128 }; 
    91 <a name="l00129"></a>00129  
    92 <a name="l00132"></a><a class="code" href="classKalmanCh.html">00132</a> <span class="keyword">class </span><a class="code" href="classKalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;chmat&gt;{ 
    93 <a name="l00133"></a>00133 <span class="keyword">protected</span>: 
    94 <a name="l00135"></a><a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798">00135</a> mat <a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798" title="pre array (triangular matrix)">preA</a>; 
    95 <a name="l00137"></a><a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87">00137</a> mat <a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87" title="post array (triangular matrix)">postA</a>; 
    96 <a name="l00138"></a>00138  
    97 <a name="l00139"></a>00139 <span class="keyword">public</span>: 
    98 <a name="l00141"></a><a class="code" href="classKalmanCh.html#d11f110cccaa66177514632d37b086bb">00141</a>         <a class="code" href="classKalmanCh.html#d11f110cccaa66177514632d37b086bb" title="Default constructor.">KalmanCh</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ):<a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>&gt;(rvx0,rvy0,rvu0),<a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798" title="pre array (triangular matrix)">preA</a>(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>),<a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87" title="post array (triangular matrix)">postA</a>(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>){}; 
    99 <a name="l00143"></a>00143         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#92fb227287af05c9f0078d523c7c9793" title="Set parameters with check of relevance.">set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span> mat &amp;B0,<span class="keyword">const</span> mat &amp;C0,<span class="keyword">const</span> mat &amp;D0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;R0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;Q0 ); 
    100 <a name="l00144"></a><a class="code" href="classKalmanCh.html#b261b20f6210d4c85131d33302df0adc">00144</a>         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#b261b20f6210d4c85131d33302df0adc" title="Set estimate values, used e.g. in initialization.">set_est</a> ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;P0 ) { 
    101 <a name="l00145"></a>00145                 <a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>.<a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af" title="Set mean value mu and covariance R.">set_parameters</a> ( mu0,P0 ); 
    102 <a name="l00146"></a>00146         }; 
    103 <a name="l00147"></a>00147          
     88<a name="l00124"></a><a class="code" href="classKalman.html#11f82ef04e3dbc54bd1d3d89edb6aa07">00124</a>         <span class="keyword">const</span> <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;sq_T&gt;</a>* <a class="code" href="classKalman.html#11f82ef04e3dbc54bd1d3d89edb6aa07" title="Returns a pointer to the epdf representing posterior density on parameters. Use with...">_e</a>()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &amp;<a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>;} 
     89<a name="l00126"></a><a class="code" href="classKalman.html#980fcd41c6c548c5da7b8b67c8e6da79">00126</a>         mat&amp; <a class="code" href="classKalman.html#980fcd41c6c548c5da7b8b67c8e6da79" title="access function">__K</a>() {<span class="keywordflow">return</span> <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>;} 
     90<a name="l00128"></a><a class="code" href="classKalman.html#ac9540f3850b74d89a5fe4db6fc358ce">00128</a>         vec <a class="code" href="classKalman.html#ac9540f3850b74d89a5fe4db6fc358ce" title="access function">_dP</a>() {<span class="keywordflow">return</span> <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>-&gt;getD();} 
     91<a name="l00129"></a>00129 }; 
     92<a name="l00130"></a>00130  
     93<a name="l00133"></a><a class="code" href="classKalmanCh.html">00133</a> <span class="keyword">class </span><a class="code" href="classKalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;chmat&gt;{ 
     94<a name="l00134"></a>00134 <span class="keyword">protected</span>: 
     95<a name="l00136"></a><a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798">00136</a> mat <a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798" title="pre array (triangular matrix)">preA</a>; 
     96<a name="l00138"></a><a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87">00138</a> mat <a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87" title="post array (triangular matrix)">postA</a>; 
     97<a name="l00139"></a>00139  
     98<a name="l00140"></a>00140 <span class="keyword">public</span>: 
     99<a name="l00142"></a><a class="code" href="classKalmanCh.html#d11f110cccaa66177514632d37b086bb">00142</a>         <a class="code" href="classKalmanCh.html#d11f110cccaa66177514632d37b086bb" title="Default constructor.">KalmanCh</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ):<a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a>&gt;(rvx0,rvy0,rvu0),<a class="code" href="classKalmanCh.html#94ee9da75b0e0f632e4a354988ca3798" title="pre array (triangular matrix)">preA</a>(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>),<a class="code" href="classKalmanCh.html#0d31a26dc72b5846cfe5af3ccb63ac87" title="post array (triangular matrix)">postA</a>(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>){}; 
     100<a name="l00144"></a>00144         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#92fb227287af05c9f0078d523c7c9793" title="Set parameters with check of relevance.">set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span> mat &amp;B0,<span class="keyword">const</span> mat &amp;C0,<span class="keyword">const</span> mat &amp;D0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;R0,<span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;Q0 ); 
     101<a name="l00145"></a><a class="code" href="classKalmanCh.html#b261b20f6210d4c85131d33302df0adc">00145</a>         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#b261b20f6210d4c85131d33302df0adc" title="Set estimate values, used e.g. in initialization.">set_est</a> ( <span class="keyword">const</span> vec &amp;mu0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> &amp;P0 ) { 
     102<a name="l00146"></a>00146                 <a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>.<a class="code" href="classenorm.html#1394a65caa6e00d42e00cc99b12227af" title="Set mean value mu and covariance R.">set_parameters</a> ( mu0,P0 ); 
     103<a name="l00147"></a>00147         }; 
    104104<a name="l00148"></a>00148          
    105 <a name="l00162"></a>00162         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#cca758192846940409822b9bd778d4e1" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    106 <a name="l00163"></a>00163 }; 
    107 <a name="l00164"></a>00164  
    108 <a name="l00170"></a><a class="code" href="classEKFfull.html">00170</a> <span class="keyword">class </span><a class="code" href="classEKFfull.html" title="Extended Kalman Filter in full matrices.">EKFfull</a> : <span class="keyword">public</span> <a class="code" href="classKalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</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> { 
    109 <a name="l00171"></a>00171  
    110 <a name="l00173"></a>00173         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
    111 <a name="l00175"></a>00175         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
    112 <a name="l00176"></a>00176          
    113 <a name="l00177"></a>00177         <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;fsqmat&gt;</a> E;  
    114 <a name="l00178"></a>00178 <span class="keyword">public</span>: 
    115 <a name="l00180"></a>00180         <a class="code" href="classEKFfull.html#67ac4de96fd025197da767fe0472c7f7" title="Default constructor.">EKFfull</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu ); 
    116 <a name="l00182"></a>00182         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#fc753106e0d4cf68e4f2160fd54458c0" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> mat Q0, <span class="keyword">const</span> mat R0 ); 
    117 <a name="l00184"></a>00184         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#8ca46f177e395fa714bbd8bd29ea43e0" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    118 <a name="l00186"></a><a class="code" href="classEKFfull.html#7bb76ea74c144ea0b36db99f94750b7b">00186</a>         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#7bb76ea74c144ea0b36db99f94750b7b" title="set estimates">set_est</a> (vec mu0, mat P0){<a class="code" href="classKalmanFull.html#fb5aec635e2720cc5ac31bc01c18a68a" title="Mean value of the posterior density.">mu</a>=mu0;<a class="code" href="classKalmanFull.html#b75dc059e84fa8ffc076203b30f926cc" title="Variance of the posterior density.">P</a>=P0;}; 
    119 <a name="l00188"></a><a class="code" href="classEKFfull.html#170a748ad944bdebb0b3073463876abe">00188</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>&amp; <a class="code" href="classEKFfull.html#170a748ad944bdebb0b3073463876abe" title="dummy!">_epdf</a>()<span class="keyword">const</span>{<span class="keywordflow">return</span> E;}; 
    120 <a name="l00189"></a>00189 }; 
    121 <a name="l00190"></a>00190  
    122 <a name="l00196"></a>00196 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    123 <a name="l00197"></a><a class="code" href="classEKF.html">00197</a> <span class="keyword">class </span><a class="code" href="classEKF.html" title="Extended Kalman Filter.">EKF</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;fsqmat&gt; { 
    124 <a name="l00199"></a>00199         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
    125 <a name="l00201"></a>00201         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
    126 <a name="l00202"></a>00202 <span class="keyword">public</span>: 
    127 <a name="l00204"></a>00204         <a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e" title="Default constructor.">EKF</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ); 
    128 <a name="l00206"></a>00206         <span class="keywordtype">void</span> <a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> sq_T Q0, <span class="keyword">const</span> sq_T R0 ); 
    129 <a name="l00208"></a>00208         <span class="keywordtype">void</span> <a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    130 <a name="l00209"></a>00209 }; 
    131 <a name="l00210"></a>00210  
    132 <a name="l00217"></a><a class="code" href="classEKFCh.html">00217</a> <span class="keyword">class </span><a class="code" href="classEKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a> : <span class="keyword">public</span> <a class="code" href="classKalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> { 
    133 <a name="l00219"></a>00219         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
    134 <a name="l00221"></a>00221         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
    135 <a name="l00222"></a>00222 <span class="keyword">public</span>: 
    136 <a name="l00224"></a>00224         <a class="code" href="classEKFCh.html#e9e39a9204db3dda88d06e47c1e19064" title="Default constructor.">EKFCh</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ); 
    137 <a name="l00226"></a>00226         <span class="keywordtype">void</span> <a class="code" href="classEKFCh.html#0216bed270df59fe65d0d62d41f8257c" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> Q0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> R0 ); 
    138 <a name="l00228"></a>00228         <span class="keywordtype">void</span> <a class="code" href="classEKFCh.html#96f6edda324a0b7ef8b4e86cc7af60c1" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
    139 <a name="l00229"></a>00229 }; 
    140 <a name="l00230"></a>00230  
    141 <a name="l00235"></a><a class="code" href="classKFcondQR.html">00235</a> <span class="keyword">class </span><a class="code" href="classKFcondQR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondQR</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
    142 <a name="l00236"></a>00236 <span class="comment">//protected:</span> 
    143 <a name="l00237"></a>00237 <span class="keyword">public</span>: 
    144 <a name="l00239"></a><a class="code" href="classKFcondQR.html#3f3968f92c7bbe4b0902d5e14ecc1cb4">00239</a>         <a class="code" href="classKFcondQR.html#3f3968f92c7bbe4b0902d5e14ecc1cb4" title="Default constructor.">KFcondQR</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvRQ ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( rvx, rvy,rvu ),<a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( rvRQ ) {}; 
    145 <a name="l00240"></a>00240  
    146 <a name="l00241"></a>00241         <span class="keywordtype">void</span> <a class="code" href="classKFcondQR.html#c9ecf292a85327aa6309c9fd70ceb606" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;RQ ); 
    147 <a name="l00242"></a>00242 }; 
    148 <a name="l00243"></a>00243  
    149 <a name="l00248"></a><a class="code" href="classKFcondR.html">00248</a> <span class="keyword">class </span><a class="code" href="classKFcondR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondR</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
    150 <a name="l00249"></a>00249 <span class="comment">//protected:</span> 
    151 <a name="l00250"></a>00250 <span class="keyword">public</span>: 
    152 <a name="l00252"></a><a class="code" href="classKFcondR.html#d2acbb8e66c7ee592b1a9da5b429a69e">00252</a>         <a class="code" href="classKFcondR.html#d2acbb8e66c7ee592b1a9da5b429a69e" title="Default constructor.">KFcondR</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvR ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( rvx, rvy,rvu ),<a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( rvR ) {}; 
    153 <a name="l00253"></a>00253  
    154 <a name="l00254"></a>00254         <span class="keywordtype">void</span> <a class="code" href="classKFcondR.html#8c0721e47879bb8840d829db7a174a7f" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> ); 
    155 <a name="l00255"></a>00255 }; 
    156 <a name="l00256"></a>00256  
     105<a name="l00149"></a>00149          
     106<a name="l00163"></a>00163         <span class="keywordtype">void</span> <a class="code" href="classKalmanCh.html#cca758192846940409822b9bd778d4e1" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     107<a name="l00164"></a>00164 }; 
     108<a name="l00165"></a>00165  
     109<a name="l00171"></a><a class="code" href="classEKFfull.html">00171</a> <span class="keyword">class </span><a class="code" href="classEKFfull.html" title="Extended Kalman Filter in full matrices.">EKFfull</a> : <span class="keyword">public</span> <a class="code" href="classKalmanFull.html" title="Basic Kalman filter with full matrices (education purpose only)! Will be deleted...">KalmanFull</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> { 
     110<a name="l00172"></a>00172  
     111<a name="l00174"></a>00174         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
     112<a name="l00176"></a>00176         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
     113<a name="l00177"></a>00177          
     114<a name="l00178"></a>00178         <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;fsqmat&gt;</a> E;  
     115<a name="l00179"></a>00179 <span class="keyword">public</span>: 
     116<a name="l00181"></a>00181         <a class="code" href="classEKFfull.html#67ac4de96fd025197da767fe0472c7f7" title="Default constructor.">EKFfull</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu ); 
     117<a name="l00183"></a>00183         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#fc753106e0d4cf68e4f2160fd54458c0" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> mat Q0, <span class="keyword">const</span> mat R0 ); 
     118<a name="l00185"></a>00185         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#8ca46f177e395fa714bbd8bd29ea43e0" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     119<a name="l00187"></a><a class="code" href="classEKFfull.html#7bb76ea74c144ea0b36db99f94750b7b">00187</a>         <span class="keywordtype">void</span> <a class="code" href="classEKFfull.html#7bb76ea74c144ea0b36db99f94750b7b" title="set estimates">set_est</a> (vec mu0, mat P0){<a class="code" href="classKalmanFull.html#fb5aec635e2720cc5ac31bc01c18a68a" title="Mean value of the posterior density.">mu</a>=mu0;<a class="code" href="classKalmanFull.html#b75dc059e84fa8ffc076203b30f926cc" title="Variance of the posterior density.">P</a>=P0;}; 
     120<a name="l00189"></a><a class="code" href="classEKFfull.html#170a748ad944bdebb0b3073463876abe">00189</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>&amp; <a class="code" href="classEKFfull.html#170a748ad944bdebb0b3073463876abe" title="dummy!">_epdf</a>()<span class="keyword">const</span>{<span class="keywordflow">return</span> E;}; 
     121<a name="l00190"></a><a class="code" href="classEKFfull.html#820987401e922a03c7d36013e42d8c48">00190</a>         <span class="keyword">const</span> <a class="code" href="classenorm.html" title="Gaussian density with positive definite (decomposed) covariance matrix.">enorm&lt;fsqmat&gt;</a>* <a class="code" href="classEKFfull.html#820987401e922a03c7d36013e42d8c48" title="Returns a pointer to the epdf representing posterior density on parameters. Use with...">_e</a>()<span class="keyword">const</span>{<span class="keywordflow">return</span> &amp;E;}; 
     122<a name="l00191"></a>00191 }; 
     123<a name="l00192"></a>00192  
     124<a name="l00198"></a>00198 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     125<a name="l00199"></a><a class="code" href="classEKF.html">00199</a> <span class="keyword">class </span><a class="code" href="classEKF.html" title="Extended Kalman Filter.">EKF</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;fsqmat&gt; { 
     126<a name="l00201"></a>00201         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
     127<a name="l00203"></a>00203         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
     128<a name="l00204"></a>00204 <span class="keyword">public</span>: 
     129<a name="l00206"></a>00206         <a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e" title="Default constructor.">EKF</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ); 
     130<a name="l00208"></a>00208         <span class="keywordtype">void</span> <a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> sq_T Q0, <span class="keyword">const</span> sq_T R0 ); 
     131<a name="l00210"></a>00210         <span class="keywordtype">void</span> <a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     132<a name="l00211"></a>00211 }; 
     133<a name="l00212"></a>00212  
     134<a name="l00219"></a><a class="code" href="classEKFCh.html">00219</a> <span class="keyword">class </span><a class="code" href="classEKFCh.html" title="Extended Kalman Filter in Square root.">EKFCh</a> : <span class="keyword">public</span> <a class="code" href="classKalmanCh.html" title="Kalman filter in square root form.">KalmanCh</a> { 
     135<a name="l00221"></a>00221         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu; 
     136<a name="l00223"></a>00223         <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu; 
     137<a name="l00224"></a>00224 <span class="keyword">public</span>: 
     138<a name="l00226"></a>00226         <a class="code" href="classEKFCh.html#e9e39a9204db3dda88d06e47c1e19064" title="Default constructor.">EKFCh</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ); 
     139<a name="l00228"></a>00228         <span class="keywordtype">void</span> <a class="code" href="classEKFCh.html#0216bed270df59fe65d0d62d41f8257c" title="Set nonlinear functions for mean values and covariance matrices.">set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu, <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> Q0, <span class="keyword">const</span> <a class="code" href="classchmat.html" title="Symmetric matrix stored in square root decomposition using upper cholesky.">chmat</a> R0 ); 
     140<a name="l00230"></a>00230         <span class="keywordtype">void</span> <a class="code" href="classEKFCh.html#96f6edda324a0b7ef8b4e86cc7af60c1" title="Here dt = [yt;ut] of appropriate dimensions.">bayes</a> ( <span class="keyword">const</span> vec &amp;dt ); 
     141<a name="l00231"></a>00231 }; 
     142<a name="l00232"></a>00232  
     143<a name="l00237"></a><a class="code" href="classKFcondQR.html">00237</a> <span class="keyword">class </span><a class="code" href="classKFcondQR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondQR</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
     144<a name="l00238"></a>00238 <span class="comment">//protected:</span> 
     145<a name="l00239"></a>00239 <span class="keyword">public</span>: 
     146<a name="l00241"></a><a class="code" href="classKFcondQR.html#3f3968f92c7bbe4b0902d5e14ecc1cb4">00241</a>         <a class="code" href="classKFcondQR.html#3f3968f92c7bbe4b0902d5e14ecc1cb4" title="Default constructor.">KFcondQR</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvRQ ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( rvx, rvy,rvu ),<a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( rvRQ ) {}; 
     147<a name="l00242"></a>00242  
     148<a name="l00243"></a>00243         <span class="keywordtype">void</span> <a class="code" href="classKFcondQR.html#c9ecf292a85327aa6309c9fd70ceb606" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;RQ ); 
     149<a name="l00244"></a>00244 }; 
     150<a name="l00245"></a>00245  
     151<a name="l00250"></a><a class="code" href="classKFcondR.html">00250</a> <span class="keyword">class </span><a class="code" href="classKFcondR.html" title="Kalman Filter with conditional diagonal matrices R and Q.">KFcondR</a> : <span class="keyword">public</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;ldmat&gt;, <span class="keyword">public</span> <a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> { 
     152<a name="l00251"></a>00251 <span class="comment">//protected:</span> 
     153<a name="l00252"></a>00252 <span class="keyword">public</span>: 
     154<a name="l00254"></a><a class="code" href="classKFcondR.html#d2acbb8e66c7ee592b1a9da5b429a69e">00254</a>         <a class="code" href="classKFcondR.html#d2acbb8e66c7ee592b1a9da5b429a69e" title="Default constructor.">KFcondR</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvR ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;<a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a>&gt; ( rvx, rvy,rvu ),<a class="code" href="classBMcond.html" title="Conditional Bayesian Filter.">BMcond</a> ( rvR ) {}; 
     155<a name="l00255"></a>00255  
     156<a name="l00256"></a>00256         <span class="keywordtype">void</span> <a class="code" href="classKFcondR.html#8c0721e47879bb8840d829db7a174a7f" title="Substitute val for rvc.">condition</a> ( <span class="keyword">const</span> vec &amp;<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> ); 
     157<a name="l00257"></a>00257 }; 
    157158<a name="l00258"></a>00258  
    158 <a name="l00259"></a>00259 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    159 <a name="l00260"></a><a class="code" href="classKalman.html#ce38e31810aea4db45a83ad05eaba009">00260</a> <a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3" title="Default constructor.">Kalman&lt;sq_T&gt;::Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;</a> &amp;K0 ) : <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( K0.rv ),rvy ( K0.rvy ),rvu ( K0.rvu ), 
    160 <a name="l00261"></a>00261                 dimx ( rv.count() ), dimy ( rvy.count() ),dimu ( rvu.count() ), 
    161 <a name="l00262"></a>00262                 A ( dimx,dimx ), B ( dimx,dimu ), C ( dimy,dimx ), D ( dimy,dimu ), 
    162 <a name="l00263"></a>00263                 Q(dimx), R(dimy), 
    163 <a name="l00264"></a>00264                 est ( rv ), fy ( rvy ), _yp(fy._mu()),_Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
    164 <a name="l00265"></a>00265  
    165 <a name="l00266"></a>00266         this-&gt;<a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a" title="Set parameters with check of relevance.">set_parameters</a> ( K0.<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>, K0.<a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>, K0.<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, K0.<a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>, K0.<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>, K0.<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> ); 
     159<a name="l00260"></a>00260  
     160<a name="l00261"></a>00261 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     161<a name="l00262"></a><a class="code" href="classKalman.html#ce38e31810aea4db45a83ad05eaba009">00262</a> <a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3" title="Default constructor.">Kalman&lt;sq_T&gt;::Kalman</a> ( <span class="keyword">const</span> <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman&lt;sq_T&gt;</a> &amp;K0 ) : <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( K0.rv ),rvy ( K0.rvy ),rvu ( K0.rvu ), 
     162<a name="l00263"></a>00263                 dimx ( rv.count() ), dimy ( rvy.count() ),dimu ( rvu.count() ), 
     163<a name="l00264"></a>00264                 A ( dimx,dimx ), B ( dimx,dimu ), C ( dimy,dimx ), D ( dimy,dimu ), 
     164<a name="l00265"></a>00265                 Q(dimx), R(dimy), 
     165<a name="l00266"></a>00266                 est ( rv ), fy ( rvy ), _yp(fy._mu()),_Ry(fy._R()), _mu(est._mu()), _P(est._R()) { 
    166166<a name="l00267"></a>00267  
    167 <a name="l00268"></a>00268 <span class="comment">// copy values in pointers</span> 
    168 <a name="l00269"></a>00269         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = K0.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>; 
    169 <a name="l00270"></a>00270         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> = K0.<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>; 
    170 <a name="l00271"></a>00271         <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> = K0.<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>; 
    171 <a name="l00272"></a>00272         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> = K0.<a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>; 
    172 <a name="l00273"></a>00273  
    173 <a name="l00274"></a>00274 } 
     167<a name="l00268"></a>00268         this-&gt;<a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a" title="Set parameters with check of relevance.">set_parameters</a> ( K0.<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>, K0.<a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>, K0.<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, K0.<a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>, K0.<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>, K0.<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> ); 
     168<a name="l00269"></a>00269  
     169<a name="l00270"></a>00270 <span class="comment">// copy values in pointers</span> 
     170<a name="l00271"></a>00271         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = K0.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>; 
     171<a name="l00272"></a>00272         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> = K0.<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>; 
     172<a name="l00273"></a>00273         <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> = K0.<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>; 
     173<a name="l00274"></a>00274         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> = K0.<a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>; 
    174174<a name="l00275"></a>00275  
    175 <a name="l00276"></a>00276 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    176 <a name="l00277"></a><a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3">00277</a> <a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3" title="Default constructor.">Kalman&lt;sq_T&gt;::Kalman</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( rvx ),<a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a> ( rvy0 ),<a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ( rvu0 ), 
    177 <a name="l00278"></a>00278                 <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ( rvx.count() ), <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ( <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>.count() ),<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ( <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>.count() ), 
    178 <a name="l00279"></a>00279                 <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ( <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a> ( <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a> ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a> ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), 
    179 <a name="l00280"></a>00280                 <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>(<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>), <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> (<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>), 
    180 <a name="l00281"></a>00281                 <a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a> ( rvx ), <a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a> ( <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a> ),  <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>(<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>()),<a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>(<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>._R()),<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>(<a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>()), <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>(<a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>._R()) { 
    181 <a name="l00282"></a>00282 }; 
    182 <a name="l00283"></a>00283  
    183 <a name="l00284"></a>00284 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    184 <a name="l00285"></a><a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a">00285</a> <span class="keywordtype">void</span> <a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a" title="Set parameters with check of relevance.">Kalman&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span>  mat &amp;B0, <span class="keyword">const</span> mat &amp;C0, <span class="keyword">const</span> mat &amp;D0, <span class="keyword">const</span> sq_T &amp;R0, <span class="keyword">const</span> sq_T &amp;Q0 ) { 
    185 <a name="l00286"></a>00286         it_assert_debug ( A0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: A is not square"</span> ); 
    186 <a name="l00287"></a>00287         it_assert_debug ( B0.rows() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: B is not compatible"</span> ); 
    187 <a name="l00288"></a>00288         it_assert_debug ( C0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: C is not square"</span> ); 
    188 <a name="l00289"></a>00289         it_assert_debug ( ( D0.rows() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ) || ( D0.cols() ==<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), <span class="stringliteral">"Kalman: D is not compatible"</span> ); 
    189 <a name="l00290"></a>00290         it_assert_debug ( ( R0.cols() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ) || ( R0.rows() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ), <span class="stringliteral">"Kalman: R is not compatible"</span> ); 
    190 <a name="l00291"></a>00291         it_assert_debug ( ( Q0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ) || ( Q0.rows() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <span class="stringliteral">"Kalman: Q is not compatible"</span> ); 
    191 <a name="l00292"></a>00292  
    192 <a name="l00293"></a>00293         <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> = A0; 
    193 <a name="l00294"></a>00294         <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a> = B0; 
    194 <a name="l00295"></a>00295         <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a> = C0; 
    195 <a name="l00296"></a>00296         <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a> = D0; 
    196 <a name="l00297"></a>00297         <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> = R0; 
    197 <a name="l00298"></a>00298         <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> = Q0; 
    198 <a name="l00299"></a>00299 } 
    199 <a name="l00300"></a>00300  
    200 <a name="l00301"></a>00301 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    201 <a name="l00302"></a><a class="code" href="classKalman.html#7750ffd73f261828a32c18aaeb65c75c">00302</a> <span class="keywordtype">void</span> <a class="code" href="classKalman.html#7750ffd73f261828a32c18aaeb65c75c" title="Here dt = [yt;ut] of appropriate dimensions.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
    202 <a name="l00303"></a>00303         it_assert_debug ( dt.length() == ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
    203 <a name="l00304"></a>00304  
    204 <a name="l00305"></a>00305         sq_T iRy(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>); 
    205 <a name="l00306"></a>00306         vec u = dt.get ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a>-1 ); 
    206 <a name="l00307"></a>00307         vec y = dt.get ( 0,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>-1 ); 
    207 <a name="l00308"></a>00308         <span class="comment">//Time update</span> 
    208 <a name="l00309"></a>00309         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>* <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> + <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>*u; 
    209 <a name="l00310"></a>00310         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    210 <a name="l00311"></a>00311         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ); 
    211 <a name="l00312"></a>00312         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>  +=<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>; 
    212 <a name="l00313"></a>00313  
    213 <a name="l00314"></a>00314         <span class="comment">//Data update</span> 
    214 <a name="l00315"></a>00315         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    215 <a name="l00316"></a>00316         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ); 
    216 <a name="l00317"></a>00317         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>  +=<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>; 
    217 <a name="l00318"></a>00318  
    218 <a name="l00319"></a>00319         mat Pfull = <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.to_mat(); 
     175<a name="l00276"></a>00276 } 
     176<a name="l00277"></a>00277  
     177<a name="l00278"></a>00278 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     178<a name="l00279"></a><a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3">00279</a> <a class="code" href="classKalman.html#3d56b0a97b8c1e25fdd3b10eef3c2ad3" title="Default constructor.">Kalman&lt;sq_T&gt;::Kalman</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classBM.html" title="Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities.">BM</a> ( rvx ),<a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a> ( rvy0 ),<a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a> ( rvu0 ), 
     179<a name="l00280"></a>00280                 <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ( rvx.count() ), <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ( <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a>.count() ),<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ( <a class="code" href="classKalman.html#44a16ffd5ac1e6e39bae34fea9e1e498" title="Indetifier of exogeneous rv.">rvu</a>.count() ), 
     180<a name="l00281"></a>00281                 <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ( <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a> ( <a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>,<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a> ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a> ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), 
     181<a name="l00282"></a>00282                 <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>(<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>), <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> (<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>), 
     182<a name="l00283"></a>00283                 <a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a> ( rvx ), <a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a> ( <a class="code" href="classKalman.html#7501230c2fafa3655887d2da23b3184c" title="Indetifier of output rv.">rvy</a> ),  <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>(<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>()),<a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>(<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>._R()),<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>(<a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>.<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>()), <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>(<a class="code" href="classKalman.html#5568c74bac67ae6d3b1061dba60c9424" title="posterior density on $x_t$">est</a>._R()) { 
     183<a name="l00284"></a>00284 }; 
     184<a name="l00285"></a>00285  
     185<a name="l00286"></a>00286 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     186<a name="l00287"></a><a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a">00287</a> <span class="keywordtype">void</span> <a class="code" href="classKalman.html#239b28a0380946f5749b2f8d2807f93a" title="Set parameters with check of relevance.">Kalman&lt;sq_T&gt;::set_parameters</a> ( <span class="keyword">const</span> mat &amp;A0,<span class="keyword">const</span>  mat &amp;B0, <span class="keyword">const</span> mat &amp;C0, <span class="keyword">const</span> mat &amp;D0, <span class="keyword">const</span> sq_T &amp;R0, <span class="keyword">const</span> sq_T &amp;Q0 ) { 
     187<a name="l00288"></a>00288         it_assert_debug ( A0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: A is not square"</span> ); 
     188<a name="l00289"></a>00289         it_assert_debug ( B0.rows() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: B is not compatible"</span> ); 
     189<a name="l00290"></a>00290         it_assert_debug ( C0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a>, <span class="stringliteral">"Kalman: C is not square"</span> ); 
     190<a name="l00291"></a>00291         it_assert_debug ( ( D0.rows() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ) || ( D0.cols() ==<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ), <span class="stringliteral">"Kalman: D is not compatible"</span> ); 
     191<a name="l00292"></a>00292         it_assert_debug ( ( R0.cols() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ) || ( R0.rows() ==<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a> ), <span class="stringliteral">"Kalman: R is not compatible"</span> ); 
     192<a name="l00293"></a>00293         it_assert_debug ( ( Q0.cols() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ) || ( Q0.rows() ==<a class="code" href="classKalman.html#39c8c403b46fa3b8c7da77cb2e3729eb" title="cache of rv.count()">dimx</a> ), <span class="stringliteral">"Kalman: Q is not compatible"</span> ); 
     193<a name="l00294"></a>00294  
     194<a name="l00295"></a>00295         <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> = A0; 
     195<a name="l00296"></a>00296         <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a> = B0; 
     196<a name="l00297"></a>00297         <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a> = C0; 
     197<a name="l00298"></a>00298         <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a> = D0; 
     198<a name="l00299"></a>00299         <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> = R0; 
     199<a name="l00300"></a>00300         <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> = Q0; 
     200<a name="l00301"></a>00301 } 
     201<a name="l00302"></a>00302  
     202<a name="l00303"></a>00303 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     203<a name="l00304"></a><a class="code" href="classKalman.html#7750ffd73f261828a32c18aaeb65c75c">00304</a> <span class="keywordtype">void</span> <a class="code" href="classKalman.html#7750ffd73f261828a32c18aaeb65c75c" title="Here dt = [yt;ut] of appropriate dimensions.">Kalman&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
     204<a name="l00305"></a>00305         it_assert_debug ( dt.length() == ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
     205<a name="l00306"></a>00306  
     206<a name="l00307"></a>00307         sq_T iRy(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>); 
     207<a name="l00308"></a>00308         vec u = dt.get ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a>-1 ); 
     208<a name="l00309"></a>00309         vec y = dt.get ( 0,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>-1 ); 
     209<a name="l00310"></a>00310         <span class="comment">//Time update</span> 
     210<a name="l00311"></a>00311         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>* <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> + <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>*u; 
     211<a name="l00312"></a>00312         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     212<a name="l00313"></a>00313         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ); 
     213<a name="l00314"></a>00314         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>  +=<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>; 
     214<a name="l00315"></a>00315  
     215<a name="l00316"></a>00316         <span class="comment">//Data update</span> 
     216<a name="l00317"></a>00317         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     217<a name="l00318"></a>00318         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.mult_sym ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ); 
     218<a name="l00319"></a>00319         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>  +=<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>; 
    219219<a name="l00320"></a>00320  
    220 <a name="l00321"></a>00321         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>.inv ( iRy ); <span class="comment">// result is in _iRy;</span> 
    221 <a name="l00322"></a>00322         <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
    222 <a name="l00323"></a>00323  
    223 <a name="l00324"></a>00324         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    224 <a name="l00325"></a>00325         iRy.mult_sym_t ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>*Pfull,pom ); 
    225 <a name="l00326"></a>00326         (<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
    226 <a name="l00327"></a>00327         (<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> ) = <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>* <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>  +<a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>*u; <span class="comment">//y prediction</span> 
    227 <a name="l00328"></a>00328         (<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> ) += <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>* ( y- <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>  ); 
    228 <a name="l00329"></a>00329  
    229 <a name="l00330"></a>00330  
    230 <a name="l00331"></a>00331         <span class="keywordflow">if</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>==<span class="keyword">true</span> ) { <span class="comment">//likelihood of observation y</span> 
    231 <a name="l00332"></a>00332                 <a class="code" href="classBM.html#5623fef6572a08c2b53b8c87b82dc979" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.evalpdflog ( y ); 
    232 <a name="l00333"></a>00333         } 
    233 <a name="l00334"></a>00334  
    234 <a name="l00335"></a>00335 <span class="comment">//cout &lt;&lt; "y: " &lt;&lt; y-(*_yp) &lt;&lt;" R: " &lt;&lt; _Ry-&gt;to_mat() &lt;&lt; " iR: " &lt;&lt; _iRy-&gt;to_mat() &lt;&lt; " ll: " &lt;&lt; ll &lt;&lt;endl;</span> 
     220<a name="l00321"></a>00321         mat Pfull = <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.to_mat(); 
     221<a name="l00322"></a>00322  
     222<a name="l00323"></a>00323         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>.inv ( iRy ); <span class="comment">// result is in _iRy;</span> 
     223<a name="l00324"></a>00324         <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
     224<a name="l00325"></a>00325  
     225<a name="l00326"></a>00326         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     226<a name="l00327"></a>00327         iRy.mult_sym_t ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>*Pfull,pom ); 
     227<a name="l00328"></a>00328         (<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
     228<a name="l00329"></a>00329         (<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> ) = <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>* <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>  +<a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>*u; <span class="comment">//y prediction</span> 
     229<a name="l00330"></a>00330         (<a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> ) += <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>* ( y- <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a>  ); 
     230<a name="l00331"></a>00331  
     231<a name="l00332"></a>00332  
     232<a name="l00333"></a>00333         <span class="keywordflow">if</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>==<span class="keyword">true</span> ) { <span class="comment">//likelihood of observation y</span> 
     233<a name="l00334"></a>00334                 <a class="code" href="classBM.html#5623fef6572a08c2b53b8c87b82dc979" title="Logarithm of marginalized data likelihood.">ll</a>=<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.evalpdflog ( y ); 
     234<a name="l00335"></a>00335         } 
    235235<a name="l00336"></a>00336  
    236 <a name="l00337"></a>00337 }; 
    237 <a name="l00338"></a>00338   
    238 <a name="l00339"></a>00339  
    239 <a name="l00340"></a>00340  
    240 <a name="l00341"></a>00341 <span class="comment">//TODO why not const pointer??</span> 
     236<a name="l00337"></a>00337 <span class="comment">//cout &lt;&lt; "y: " &lt;&lt; y-(*_yp) &lt;&lt;" R: " &lt;&lt; _Ry-&gt;to_mat() &lt;&lt; " iR: " &lt;&lt; _iRy-&gt;to_mat() &lt;&lt; " ll: " &lt;&lt; ll &lt;&lt;endl;</span> 
     237<a name="l00338"></a>00338  
     238<a name="l00339"></a>00339 }; 
     239<a name="l00340"></a>00340   
     240<a name="l00341"></a>00341  
    241241<a name="l00342"></a>00342  
    242 <a name="l00343"></a>00343 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    243 <a name="l00344"></a><a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e">00344</a> <a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e" title="Default constructor.">EKF&lt;sq_T&gt;::EKF</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;sq_T&gt; ( rvx0,rvy0,rvu0 ) {} 
    244 <a name="l00345"></a>00345  
    245 <a name="l00346"></a>00346 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    246 <a name="l00347"></a><a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66">00347</a> <span class="keywordtype">void</span> <a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66" title="Set nonlinear functions for mean values and covariance matrices.">EKF&lt;sq_T&gt;::set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu0,  <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu0,<span class="keyword">const</span> sq_T Q0,<span class="keyword">const</span> sq_T R0 ) { 
    247 <a name="l00348"></a>00348         pfxu = pfxu0; 
    248 <a name="l00349"></a>00349         phxu = phxu0; 
    249 <a name="l00350"></a>00350  
    250 <a name="l00351"></a>00351         <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
    251 <a name="l00352"></a>00352         pfxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>,<span class="keyword">true</span> ); 
    252 <a name="l00353"></a>00353 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
    253 <a name="l00354"></a>00354         <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>.clear(); 
    254 <a name="l00355"></a>00355         phxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>,<span class="keyword">true</span> ); 
    255 <a name="l00356"></a>00356 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
    256 <a name="l00357"></a>00357         <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>.clear(); 
    257 <a name="l00358"></a>00358  
    258 <a name="l00359"></a>00359         <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> = R0; 
    259 <a name="l00360"></a>00360         <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> = Q0; 
    260 <a name="l00361"></a>00361 } 
    261 <a name="l00362"></a>00362  
    262 <a name="l00363"></a>00363 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
    263 <a name="l00364"></a><a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7">00364</a> <span class="keywordtype">void</span> <a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7" title="Here dt = [yt;ut] of appropriate dimensions.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
    264 <a name="l00365"></a>00365         it_assert_debug ( dt.length() == ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
    265 <a name="l00366"></a>00366  
    266 <a name="l00367"></a>00367         sq_T iRy(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>); 
    267 <a name="l00368"></a>00368         vec u = dt.get ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a>-1 ); 
    268 <a name="l00369"></a>00369         vec y = dt.get ( 0,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>-1 ); 
    269 <a name="l00370"></a>00370         <span class="comment">//Time update</span> 
    270 <a name="l00371"></a>00371         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = pfxu-&gt;<a class="code" href="classdiffbifn.html#ad7673e16aa1a046b131b24c731c4632" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>, u ); 
    271 <a name="l00372"></a>00372         pfxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u,<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>,<span class="keyword">false</span> ); <span class="comment">//update A by a derivative of fx</span> 
    272 <a name="l00373"></a>00373  
    273 <a name="l00374"></a>00374         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
    274 <a name="l00375"></a>00375         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ); 
    275 <a name="l00376"></a>00376         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> +=<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>; 
    276 <a name="l00377"></a>00377  
    277 <a name="l00378"></a>00378         <span class="comment">//Data update</span> 
    278 <a name="l00379"></a>00379         phxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u,<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>,<span class="keyword">false</span> ); <span class="comment">//update C by a derivative hx</span> 
    279 <a name="l00380"></a>00380         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
    280 <a name="l00381"></a>00381         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ); 
    281 <a name="l00382"></a>00382         ( <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ) +=<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>; 
    282 <a name="l00383"></a>00383  
    283 <a name="l00384"></a>00384         mat Pfull = <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#f54fc955e8e3b43d15afa92124bc24b3" title="Conversion to full matrix.">to_mat</a>(); 
     242<a name="l00343"></a>00343 <span class="comment">//TODO why not const pointer??</span> 
     243<a name="l00344"></a>00344  
     244<a name="l00345"></a>00345 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     245<a name="l00346"></a><a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e">00346</a> <a class="code" href="classEKF.html#ea4f3254cacf0a92d2a820b1201d049e" title="Default constructor.">EKF&lt;sq_T&gt;::EKF</a> ( <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvx0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvy0, <a class="code" href="classRV.html" title="Class representing variables, most often random variables.">RV</a> rvu0 ) : <a class="code" href="classKalman.html" title="Kalman filter with covariance matrices in square root form.">Kalman</a>&lt;sq_T&gt; ( rvx0,rvy0,rvu0 ) {} 
     246<a name="l00347"></a>00347  
     247<a name="l00348"></a>00348 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     248<a name="l00349"></a><a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66">00349</a> <span class="keywordtype">void</span> <a class="code" href="classEKF.html#28d058ae4d24d992d2f055419a06ee66" title="Set nonlinear functions for mean values and covariance matrices.">EKF&lt;sq_T&gt;::set_parameters</a> ( <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* pfxu0,  <a class="code" href="classdiffbifn.html" title="Class representing a differentiable function of two variables .">diffbifn</a>* phxu0,<span class="keyword">const</span> sq_T Q0,<span class="keyword">const</span> sq_T R0 ) { 
     249<a name="l00350"></a>00350         pfxu = pfxu0; 
     250<a name="l00351"></a>00351         phxu = phxu0; 
     251<a name="l00352"></a>00352  
     252<a name="l00353"></a>00353         <span class="comment">//initialize matrices A C, later, these will be only updated!</span> 
     253<a name="l00354"></a>00354         pfxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>,<span class="keyword">true</span> ); 
     254<a name="l00355"></a>00355 <span class="comment">//      pfxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),B,true );</span> 
     255<a name="l00356"></a>00356         <a class="code" href="classKalman.html#dc87704284a6c0bca13bf51f4345a50a" title="Matrix B.">B</a>.clear(); 
     256<a name="l00357"></a>00357         phxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,zeros ( <a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>,<span class="keyword">true</span> ); 
     257<a name="l00358"></a>00358 <span class="comment">//      phxu-&gt;dfdu_cond ( *_mu,zeros ( dimu ),D,true );</span> 
     258<a name="l00359"></a>00359         <a class="code" href="classKalman.html#d69f774ba3335c970c1c5b1d182f4dd1" title="Matrix D.">D</a>.clear(); 
     259<a name="l00360"></a>00360  
     260<a name="l00361"></a>00361         <a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a> = R0; 
     261<a name="l00362"></a>00362         <a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a> = Q0; 
     262<a name="l00363"></a>00363 } 
     263<a name="l00364"></a>00364  
     264<a name="l00365"></a>00365 <span class="keyword">template</span>&lt;<span class="keyword">class</span> sq_T&gt; 
     265<a name="l00366"></a><a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7">00366</a> <span class="keywordtype">void</span> <a class="code" href="classEKF.html#c79c62c9b3e0b56b3aaa1b6f1d9a7af7" title="Here dt = [yt;ut] of appropriate dimensions.">EKF&lt;sq_T&gt;::bayes</a> ( <span class="keyword">const</span> vec &amp;dt ) { 
     266<a name="l00367"></a>00367         it_assert_debug ( dt.length() == ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a> ),<span class="stringliteral">"KalmanFull::bayes wrong size of dt"</span> ); 
     267<a name="l00368"></a>00368  
     268<a name="l00369"></a>00369         sq_T iRy(<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>); 
     269<a name="l00370"></a>00370         vec u = dt.get ( <a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>+<a class="code" href="classKalman.html#b0153795a1444b6968a86409c778d9ce" title="cache of rvu.count()">dimu</a>-1 ); 
     270<a name="l00371"></a>00371         vec y = dt.get ( 0,<a class="code" href="classKalman.html#ba17b956df1e38b31fbbc299c8213b6a" title="cache of rvy.count()">dimy</a>-1 ); 
     271<a name="l00372"></a>00372         <span class="comment">//Time update</span> 
     272<a name="l00373"></a>00373         <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> = pfxu-&gt;<a class="code" href="classdiffbifn.html#ad7673e16aa1a046b131b24c731c4632" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>, u ); 
     273<a name="l00374"></a>00374         pfxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u,<a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a>,<span class="keyword">false</span> ); <span class="comment">//update A by a derivative of fx</span> 
     274<a name="l00375"></a>00375  
     275<a name="l00376"></a>00376         <span class="comment">//P  = A*P*A.transpose() + Q; in sq_T</span> 
     276<a name="l00377"></a>00377         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classKalman.html#5e02efe86ee91e9c74b93b425fe060b9" title="Matrix A.">A</a> ); 
     277<a name="l00378"></a>00378         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> +=<a class="code" href="classKalman.html#9b69015c800eb93f3ee49da23a6f55d9" title="Matrix Q in square-root form.">Q</a>; 
     278<a name="l00379"></a>00379  
     279<a name="l00380"></a>00380         <span class="comment">//Data update</span> 
     280<a name="l00381"></a>00381         phxu-&gt;<a class="code" href="classdiffbifn.html#6d217a02d4fa13931258d4bebdd0feb4" title="Evaluates  and writes result into A .">dfdx_cond</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u,<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>,<span class="keyword">false</span> ); <span class="comment">//update C by a derivative hx</span> 
     281<a name="l00382"></a>00382         <span class="comment">//_Ry = C*P*C.transpose() + R; in sq_T</span> 
     282<a name="l00383"></a>00383         <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#5530d2756b5d991de755e6121c9a452e" title="Inplace symmetric multiplication by a SQUARE matrix , i.e. .">mult_sym</a> ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>, <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ); 
     283<a name="l00384"></a>00384         ( <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a> ) +=<a class="code" href="classKalman.html#11d171dc0e0ab111c56a70f98b97b3ec" title="Matrix R in square-root form.">R</a>; 
    284284<a name="l00385"></a>00385  
    285 <a name="l00386"></a>00386         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>.<a class="code" href="classfsqmat.html#9fa853e1ca28f2a1a1c43377e798ecb1" title="Matrix inversion preserving the chosen form.">inv</a> ( iRy ); <span class="comment">// result is in _iRy;</span> 
    286 <a name="l00387"></a>00387         <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
    287 <a name="l00388"></a>00388  
    288 <a name="l00389"></a>00389         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
    289 <a name="l00390"></a>00390         iRy.mult_sym_t ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>*Pfull,pom ); 
    290 <a name="l00391"></a>00391         (<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
    291 <a name="l00392"></a>00392         <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> = phxu-&gt;<a class="code" href="classdiffbifn.html#ad7673e16aa1a046b131b24c731c4632" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u ); <span class="comment">//y prediction</span> 
    292 <a name="l00393"></a>00393         ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> ) += <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>* ( y-<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> ); 
    293 <a name="l00394"></a>00394  
    294 <a name="l00395"></a>00395         <span class="keywordflow">if</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>==<span class="keyword">true</span> ) {<a class="code" href="classBM.html#5623fef6572a08c2b53b8c87b82dc979" title="Logarithm of marginalized data likelihood.">ll</a>+=<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.<a class="code" href="classeEF.html#6466e8d4aa9dd64698ed288cbb1afc03" title="Evaluate normalized log-probability.">evalpdflog</a> ( y );} 
    295 <a name="l00396"></a>00396 }; 
    296 <a name="l00397"></a>00397  
    297 <a name="l00398"></a>00398  
    298 <a name="l00399"></a>00399 <span class="preprocessor">#endif // KF_H</span> 
    299 <a name="l00400"></a>00400 <span class="preprocessor"></span> 
    300 <a name="l00401"></a>00401  
     285<a name="l00386"></a>00386         mat Pfull = <a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a>.<a class="code" href="classfsqmat.html#f54fc955e8e3b43d15afa92124bc24b3" title="Conversion to full matrix.">to_mat</a>(); 
     286<a name="l00387"></a>00387  
     287<a name="l00388"></a>00388         <a class="code" href="classKalman.html#45c9f928d2d62e0c884900fb3380f904" title="cache of fy.R">_Ry</a>.<a class="code" href="classfsqmat.html#9fa853e1ca28f2a1a1c43377e798ecb1" title="Matrix inversion preserving the chosen form.">inv</a> ( iRy ); <span class="comment">// result is in _iRy;</span> 
     288<a name="l00389"></a>00389         <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a> = Pfull*<a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>.transpose() * ( iRy.to_mat() ); 
     289<a name="l00390"></a>00390  
     290<a name="l00391"></a>00391         sq_T pom ( ( <span class="keywordtype">int</span> ) Pfull.rows() ); 
     291<a name="l00392"></a>00392         iRy.mult_sym_t ( <a class="code" href="classKalman.html#86a805cd6515872d1132ad0d6eb5dc13" title="Matrix C.">C</a>*Pfull,pom ); 
     292<a name="l00393"></a>00393         (<a class="code" href="classKalman.html#9fb808cc94a4c2652e1fb93be9bb7dcf" title="cache of est.R">_P</a> ) -= pom; <span class="comment">// P = P -PC'iRy*CP;</span> 
     293<a name="l00394"></a>00394         <a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> = phxu-&gt;<a class="code" href="classdiffbifn.html#ad7673e16aa1a046b131b24c731c4632" title="Evaluates  (VS: Do we really need common eval? ).">eval</a> ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a>,u ); <span class="comment">//y prediction</span> 
     294<a name="l00395"></a>00395         ( <a class="code" href="classKalman.html#fe803a81d2d847b0b1db3c6b29c18061" title="cache of est.mu">_mu</a> ) += <a class="code" href="classKalman.html#d422f51467c7a06174af2476d2826132" title="placeholder for Kalman gain">_K</a>* ( y-<a class="code" href="classKalman.html#764bbc95238eda11fc81c5ebd0b1dcfd" title="cache of fy.mu">_yp</a> ); 
     295<a name="l00396"></a>00396  
     296<a name="l00397"></a>00397         <span class="keywordflow">if</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>==<span class="keyword">true</span> ) {<a class="code" href="classBM.html#5623fef6572a08c2b53b8c87b82dc979" title="Logarithm of marginalized data likelihood.">ll</a>+=<a class="code" href="classKalman.html#e580ab06483952bd03f2e651763e184f" title="preditive density on $y_t$">fy</a>.<a class="code" href="classeEF.html#6466e8d4aa9dd64698ed288cbb1afc03" title="Evaluate normalized log-probability.">evalpdflog</a> ( y );} 
     297<a name="l00398"></a>00398 }; 
     298<a name="l00399"></a>00399  
     299<a name="l00400"></a>00400  
     300<a name="l00401"></a>00401 <span class="preprocessor">#endif // KF_H</span> 
     301<a name="l00402"></a>00402 <span class="preprocessor"></span> 
     302<a name="l00403"></a>00403  
    301303</pre></div></div> 
    302 <hr size="1"><address style="text-align: right;"><small>Generated on Wed Oct 15 15:57:08 2008 for mixpp by&nbsp; 
     304<hr size="1"><address style="text-align: right;"><small>Generated on Wed Nov 12 20:46:05 2008 for mixpp by&nbsp; 
    303305<a href="http://www.doxygen.org/index.html"> 
    304306<img src="doxygen.png" alt="doxygen" align="middle" border="0"></a> 1.5.6 </small></address>