| 89 | | <a name="l00063"></a>00063 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) {<a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a>=frg0;} |
| 90 | | <a name="l00064"></a>00064 <span class="keywordtype">void</span> set_statistics ( <span class="keywordtype">int</span> dimx0, <span class="keyword">const</span> <a class="code" href="classldmat.html" title="Matrix stored in LD form, (commonly known as UD).">ldmat</a> V0, <span class="keywordtype">double</span> nu0=-1.0 ) {<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.set_parameters ( dimx0,V0,nu0 );<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>=<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.lognc();<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>=dimx0;} |
| 91 | | <a name="l00066"></a>00066 |
| 92 | | <a name="l00067"></a>00067 <span class="comment">// //! Set parameters given by moments, \c mu (mean of theta), \c R (mean of R) and \c C (variance of theta)</span> |
| 93 | | <a name="l00068"></a>00068 <span class="comment">// void set_parameters ( const vec &mu, const mat &R, const mat &C, double dfm){};</span> |
| 94 | | <a name="l00070"></a>00070 <span class="comment"></span> <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a>* BM0 ); |
| 95 | | <a name="l00071"></a>00071 <span class="comment">// //! Returns sufficient statistics</span> |
| 96 | | <a name="l00072"></a>00072 <span class="comment">// void get_parameters ( mat &V0, double &nu0 ) {V0=est._V().to_mat(); nu0=est._nu();}</span> |
| 97 | | <a name="l00075"></a>00075 <span class="comment"></span> |
| 98 | | <a name="l00077"></a>00077 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( <span class="keyword">const</span> vec &dt, <span class="keyword">const</span> <span class="keywordtype">double</span> w ); |
| 99 | | <a name="l00078"></a><a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3">00078</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ) {<a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( dt,1.0 );}; |
| 100 | | <a name="l00079"></a>00079 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1ARX.html#080a7e531e3aa06694112863b15bc6a4">logpred</a> ( <span class="keyword">const</span> vec &dt ) <span class="keyword">const</span>; |
| 101 | | <a name="l00080"></a><a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca">00080</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca" title="Flatten the posterior according to the given BMEF (of the same type!).">flatten</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* B ) { |
| 102 | | <a name="l00081"></a>00081 <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>* A=<span class="keyword">dynamic_cast<</span><span class="keyword">const </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>*<span class="keyword">></span> ( B ); |
| 103 | | <a name="l00082"></a>00082 <span class="comment">// nu should be equal to B.nu</span> |
| 104 | | <a name="l00083"></a>00083 <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( A-><a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a>/<a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ); |
| 105 | | <a name="l00084"></a>00084 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a> ) {<a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a>=<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a>();} |
| 106 | | <a name="l00085"></a>00085 } |
| 107 | | <a name="l00087"></a>00087 <a class="code" href="classbdm_1_1enorm.html">enorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &rgr ) <span class="keyword">const</span>; |
| 108 | | <a name="l00089"></a><a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15">00089</a> <a class="code" href="classbdm_1_1enorm.html">enorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a>()<span class="keyword"> const </span>{ |
| 109 | | <a name="l00090"></a>00090 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>==<a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>.<a class="code" href="group__math.html#g96dfb21865db4f5bd36fa70f9b0b1163" title="access function">rows</a>()-1,<span class="stringliteral">"Regressor is not only 1"</span> ); |
| 110 | | <a name="l00091"></a>00091 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( vec_1 ( 1.0 ) ); |
| 111 | | <a name="l00092"></a>00092 } |
| 112 | | <a name="l00094"></a>00094 <a class="code" href="classbdm_1_1mlnorm.html">mlnorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#74fe8ae2d88bee8639510fd0eaf73513" title="conditional version of the predictor">predictor</a>() <span class="keyword">const</span>; |
| 113 | | <a name="l00095"></a>00095 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>; |
| 114 | | <a name="l00097"></a>00097 ivec <a class="code" href="classbdm_1_1ARX.html#16b02ae03316751664c22d59d90c1e34" title="Brute force structure estimation.">structure_est</a> ( <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> Eg0 ); |
| 115 | | <a name="l00099"></a>00099 |
| 116 | | <a name="l00102"></a>00102 <span class="keyword">const</span> <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>* _e()<span class="keyword"> const </span>{<span class="keywordflow">return</span> &<a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a> ;}; |
| 117 | | <a name="l00103"></a>00103 <span class="keyword">const</span> egiw& posterior()<span class="keyword"> const </span>{<span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>;} |
| 118 | | <a name="l00105"></a>00105 |
| 119 | | <a name="l00108"></a>00108 <span class="keywordtype">void</span> set_drv ( <span class="keyword">const</span> RV &drv0 ) {<a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a>=drv0;} |
| 120 | | <a name="l00109"></a>00109 RV& get_yrv() { |
| 121 | | <a name="l00110"></a>00110 <span class="comment">//if yrv is not ready create it</span> |
| 122 | | <a name="l00111"></a>00111 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() !=<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) { |
| 123 | | <a name="l00112"></a>00112 <span class="keywordtype">int</span> i=0; |
| 124 | | <a name="l00113"></a>00113 <span class="keywordflow">while</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() <<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) {<a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>.add ( <a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> ( vec_1 ( i ) ) );i++;} |
| 125 | | <a name="l00114"></a>00114 } |
| 126 | | <a name="l00115"></a>00115 <span class="comment">//yrv should be ready by now</span> |
| 127 | | <a name="l00116"></a>00116 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() ==<a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>,<span class="stringliteral">"incompatible drv"</span> ); |
| 128 | | <a name="l00117"></a>00117 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>; |
| 129 | | <a name="l00118"></a>00118 } |
| 130 | | <a name="l00120"></a>00120 |
| 131 | | <a name="l00121"></a>00121 <span class="comment">// TODO dokumentace - aktualizovat</span> |
| 132 | | <a name="l00142"></a>00142 <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#9637412df898048bafaefee9dc7e9f6c">from_setting</a>( <span class="keyword">const</span> Setting &<span class="keyword">set</span> ); |
| 133 | | <a name="l00143"></a>00143 |
| 134 | | <a name="l00144"></a>00144 <span class="comment">// TODO dodelat void to_setting( Setting &set ) const;</span> |
| 135 | | <a name="l00145"></a>00145 }; |
| 136 | | <a name="l00146"></a>00146 |
| 137 | | <a name="l00147"></a>00147 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a>(ARX); |
| 138 | | <a name="l00148"></a>00148 |
| 139 | | <a name="l00149"></a>00149 } |
| 140 | | <a name="l00150"></a>00150 |
| 141 | | <a name="l00151"></a>00151 <span class="preprocessor">#endif // AR_H</span> |
| 142 | | <a name="l00152"></a>00152 <span class="preprocessor"></span> |
| 143 | | <a name="l00153"></a>00153 |
| | 88 | <a name="l00063"></a>00063 <span class="keywordtype">void</span> set_parameters ( <span class="keywordtype">double</span> frg0 ) { |
| | 89 | <a name="l00064"></a>00064 <a class="code" href="classbdm_1_1BMEF.html#1331865e10fb1ccef65bb4c47fa3be64" title="forgetting factor">frg</a> = frg0; |
| | 90 | <a name="l00065"></a>00065 } |
| | 91 | <a name="l00066"></a>00066 <span class="keywordtype">void</span> set_statistics ( <span class="keywordtype">int</span> dimx0, <span class="keyword">const</span> ldmat V0, <span class="keywordtype">double</span> nu0 = -1.0 ) { |
| | 92 | <a name="l00067"></a>00067 <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.set_parameters ( dimx0, V0, nu0 ); |
| | 93 | <a name="l00068"></a>00068 <a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> = <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.lognc(); |
| | 94 | <a name="l00069"></a>00069 <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> = dimx0; |
| | 95 | <a name="l00070"></a>00070 } |
| | 96 | <a name="l00072"></a>00072 |
| | 97 | <a name="l00073"></a>00073 <span class="comment">// //! Set parameters given by moments, \c mu (mean of theta), \c R (mean of R) and \c C (variance of theta)</span> |
| | 98 | <a name="l00074"></a>00074 <span class="comment">// void set_parameters ( const vec &mu, const mat &R, const mat &C, double dfm){};</span> |
| | 99 | <a name="l00076"></a>00076 <span class="comment"></span> <span class="keywordtype">void</span> set_statistics ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html#2def512872ed8a4fc3b702371ec0be55" title="Default constructor (=empty constructor).">BMEF</a>* BM0 ); |
| | 100 | <a name="l00077"></a>00077 <span class="comment">// //! Returns sufficient statistics</span> |
| | 101 | <a name="l00078"></a>00078 <span class="comment">// void get_parameters ( mat &V0, double &nu0 ) {V0=est._V().to_mat(); nu0=est._nu();}</span> |
| | 102 | <a name="l00081"></a>00081 <span class="comment"></span> |
| | 103 | <a name="l00083"></a>00083 <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( <span class="keyword">const</span> vec &dt, <span class="keyword">const</span> <span class="keywordtype">double</span> w ); |
| | 104 | <a name="l00084"></a><a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3">00084</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#8bdf2974052e8ce74eb0d4f3791c58a3" title="Incremental Bayes rule.">bayes</a> ( <span class="keyword">const</span> vec &dt ) { |
| | 105 | <a name="l00085"></a>00085 <a class="code" href="classbdm_1_1ARX.html#17e7fe14654ab3c449846c3f43e66169" title="Weighted Bayes .">bayes</a> ( dt, 1.0 ); |
| | 106 | <a name="l00086"></a>00086 }; |
| | 107 | <a name="l00087"></a>00087 <span class="keywordtype">double</span> <a class="code" href="classbdm_1_1ARX.html#080a7e531e3aa06694112863b15bc6a4">logpred</a> ( <span class="keyword">const</span> vec &dt ) <span class="keyword">const</span>; |
| | 108 | <a name="l00088"></a><a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca">00088</a> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#e86ab499b116b837d3163ec852961eca" title="Flatten the posterior according to the given BMEF (of the same type!).">flatten</a> ( <span class="keyword">const</span> <a class="code" href="classbdm_1_1BMEF.html" title="Estimator for Exponential family.">BMEF</a>* B ) { |
| | 109 | <a name="l00089"></a>00089 <span class="keyword">const</span> <a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>* A = <span class="keyword">dynamic_cast<</span><span class="keyword">const </span><a class="code" href="classbdm_1_1ARX.html" title="Linear Autoregressive model with Gaussian noise.">ARX</a>*<span class="keyword">></span> ( B ); |
| | 110 | <a name="l00090"></a>00090 <span class="comment">// nu should be equal to B.nu</span> |
| | 111 | <a name="l00091"></a>00091 <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#8e610e95401a11baf34f65e16ecd87be" title="Power of the density, used e.g. to flatten the density.">pow</a> ( A-><a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> / <a class="code" href="classbdm_1_1ARX.html#740b0582f180ba13cae91d66e9bdb67f" title="cached value of est.nu">nu</a> ); |
| | 112 | <a name="l00092"></a>00092 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1BM.html#faff0ad12556fe7dc0e2807d4fd938ee" title="If true, the filter will compute likelihood of the data record and store it in ll...">evalll</a> ) { |
| | 113 | <a name="l00093"></a>00093 <a class="code" href="classbdm_1_1BMEF.html#06e7b3ac03e10017d4288c76888e2865" title="cached value of lognc() in the previous step (used in evaluation of ll )">last_lognc</a> = <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>.<a class="code" href="classbdm_1_1egiw.html#41d72ba7b2abc8a9a4209ffa98ed5633" title="logarithm of the normalizing constant, ">lognc</a>(); |
| | 114 | <a name="l00094"></a>00094 } |
| | 115 | <a name="l00095"></a>00095 } |
| | 116 | <a name="l00097"></a>00097 <a class="code" href="classbdm_1_1enorm.html">enorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( <span class="keyword">const</span> vec &rgr ) <span class="keyword">const</span>; |
| | 117 | <a name="l00099"></a><a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15">00099</a> <a class="code" href="classbdm_1_1enorm.html">enorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a>()<span class="keyword"> const </span>{ |
| | 118 | <a name="l00100"></a>00100 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> == <a class="code" href="classbdm_1_1ARX.html#de5b7d83ff5d3f5af2f80068db0abdfd" title="cached value of est.V">V</a>.<a class="code" href="classbdm_1_1sqmat.html#73e639221343dcce76c3305524d67590" title="Reimplementing common functions of mat: rows().">rows</a>() - 1, <span class="stringliteral">"Regressor is not only 1"</span> ); |
| | 119 | <a name="l00101"></a>00101 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#4cdf5e2a7d3480ec31f6247ed4289b15" title="Predictor for empty regressor.">epredictor</a> ( vec_1 ( 1.0 ) ); |
| | 120 | <a name="l00102"></a>00102 } |
| | 121 | <a name="l00104"></a>00104 <a class="code" href="classbdm_1_1mlnorm.html" title="Normal distributed linear function with linear function of mean value;.">mlnorm<ldmat></a>* <a class="code" href="classbdm_1_1ARX.html#74fe8ae2d88bee8639510fd0eaf73513" title="conditional version of the predictor">predictor</a>() <span class="keyword">const</span>; |
| | 122 | <a name="l00105"></a>00105 <a class="code" href="classbdm_1_1mlstudent.html">mlstudent</a>* predictor_student() <span class="keyword">const</span>; |
| | 123 | <a name="l00107"></a>00107 ivec <a class="code" href="classbdm_1_1ARX.html#16b02ae03316751664c22d59d90c1e34" title="Brute force structure estimation.">structure_est</a> ( <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a> Eg0 ); |
| | 124 | <a name="l00109"></a>00109 |
| | 125 | <a name="l00112"></a>00112 <span class="keyword">const</span> <a class="code" href="classbdm_1_1egiw.html" title="Gauss-inverse-Wishart density stored in LD form.">egiw</a>& posterior()<span class="keyword"> const </span>{ |
| | 126 | <a name="l00113"></a>00113 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#11474a627367f81b76830cb8477cf026" title="Posterior estimate of in the form of Normal-inverse Wishart density.">est</a>; |
| | 127 | <a name="l00114"></a>00114 } |
| | 128 | <a name="l00116"></a>00116 |
| | 129 | <a name="l00119"></a>00119 <span class="keywordtype">void</span> set_drv ( <span class="keyword">const</span> RV &drv0 ) { |
| | 130 | <a name="l00120"></a>00120 <a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> = drv0; |
| | 131 | <a name="l00121"></a>00121 } |
| | 132 | <a name="l00122"></a>00122 RV& get_yrv() { |
| | 133 | <a name="l00123"></a>00123 <span class="comment">//if yrv is not ready create it</span> |
| | 134 | <a name="l00124"></a>00124 <span class="keywordflow">if</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() != <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) { |
| | 135 | <a name="l00125"></a>00125 <span class="keywordtype">int</span> i = 0; |
| | 136 | <a name="l00126"></a>00126 <span class="keywordflow">while</span> ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() < <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a> ) { |
| | 137 | <a name="l00127"></a>00127 <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>.add ( <a class="code" href="classbdm_1_1BM.html#c400357e37d27a4834b2b1d9211009ed" title="Random variable of the data (optional).">drv</a> ( vec_1 ( i ) ) ); |
| | 138 | <a name="l00128"></a>00128 i++; |
| | 139 | <a name="l00129"></a>00129 } |
| | 140 | <a name="l00130"></a>00130 } |
| | 141 | <a name="l00131"></a>00131 <span class="comment">//yrv should be ready by now</span> |
| | 142 | <a name="l00132"></a>00132 it_assert_debug ( <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>._dsize() == <a class="code" href="classbdm_1_1ARX.html#8e68db2a218d54b09304cad6c0a897d9" title="size of output variable (needed in regressors)">dimx</a>, <span class="stringliteral">"incompatible drv"</span> ); |
| | 143 | <a name="l00133"></a>00133 <span class="keywordflow">return</span> <a class="code" href="classbdm_1_1ARX.html#363aaa55b2ab3eec602510cdf53e84ef">_yrv</a>; |
| | 144 | <a name="l00134"></a>00134 } |
| | 145 | <a name="l00136"></a>00136 |
| | 146 | <a name="l00137"></a>00137 <span class="comment">// TODO dokumentace - aktualizovat</span> |
| | 147 | <a name="l00158"></a>00158 <span class="comment"></span> <span class="keywordtype">void</span> <a class="code" href="classbdm_1_1ARX.html#9637412df898048bafaefee9dc7e9f6c">from_setting</a> ( <span class="keyword">const</span> Setting &<span class="keyword">set</span> ); |
| | 148 | <a name="l00159"></a>00159 |
| | 149 | <a name="l00160"></a>00160 }; |
| | 150 | <a name="l00161"></a>00161 |
| | 151 | <a name="l00162"></a>00162 <a class="code" href="user__info_8h.html#4f9de2f17e844047726487b99def99c6" title="Macro for registration of class into map of user-infos, registered class is scriptable...">UIREGISTER</a> ( ARX ); |
| | 152 | <a name="l00163"></a>00163 SHAREDPTR ( ARX ); |
| | 153 | <a name="l00164"></a>00164 |
| | 154 | <a name="l00165"></a>00165 } |
| | 155 | <a name="l00166"></a>00166 |
| | 156 | <a name="l00167"></a>00167 <span class="preprocessor">#endif // AR_H</span> |
| | 157 | <a name="l00168"></a>00168 <span class="preprocessor"></span> |
| | 158 | <a name="l00169"></a>00169 |
