Changeset 737 for library/bdm/estim/particles.cpp

Timestamp:

11/25/09 12:14:38 (15 years ago)

Author:

mido

Message:

ASTYLER RUN OVER THE WHOLE LIBRARY, JUPEE

Files:

• library/bdm/estim/particles.cpp (modified) (4 diffs)

library/bdm/estim/particles.cpp

@@ -5 +5 @@
 using std::endl;
 
-void PF::bayes_gensmp(const vec &ut){
-        if (ut.length()>0){
-                vec cond(par->dimensionc());
-                cond.set_subvector(par->dimension(),ut);
-                #pragma parallel for
-                for (int i = 0; i < n; i++ ) {
-                        cond.set_subvector(0,_samples ( i ));
+void PF::bayes_gensmp ( const vec &ut ) {
+        if ( ut.length() > 0 ) {
+                vec cond ( par->dimensionc() );
+                cond.set_subvector ( par->dimension(), ut );
+#pragma parallel for
+                for ( int i = 0; i < n; i++ ) {
+                        cond.set_subvector ( 0, _samples ( i ) );
                         _samples ( i ) = par->samplecond ( cond );
-                        lls(i) = 0;
+                        lls ( i ) = 0;
                 }
-        } else {                
-                #pragma parallel for
-                for (int i = 0; i < n; i++ ) {
+        } else {
+#pragma parallel for
+                for ( int i = 0; i < n; i++ ) {
                         _samples ( i ) = par->samplecond ( _samples ( i ) );
-                        lls(i) = 0;
+                        lls ( i ) = 0;
                 }
         }
 }
 
-void PF::bayes_weights(){
-// 
-        double mlls=max(lls);
+void PF::bayes_weights() {
+//
+        double mlls = max ( lls );
         // compute weights
-        for (int  i = 0; i < n; i++ ) {
+        for ( int  i = 0; i < n; i++ ) {
                 _w ( i ) *= exp ( lls ( i ) - mlls ); // multiply w by likelihood
         }
 
         //renormalize
-        double sw=sum(_w);
-        if (!std::isfinite(sw)) {
-                for (int i=0;i<n;i++){
-                        if (!std::isfinite(_w(i))) {_w(i)=0;}
+        double sw = sum ( _w );
+        if ( !std::isfinite ( sw ) ) {
+                for ( int i = 0; i < n; i++ ) {
+                        if ( !std::isfinite ( _w ( i ) ) ) {
+                                _w ( i ) = 0;
+                        }
                 }
-                sw = sum(_w);
-                if (!std::isfinite(sw) || sw==0.0) {
-                        bdm_error("Particle filter is lost; no particle is good enough.");
+                sw = sum ( _w );
+                if ( !std::isfinite ( sw ) || sw == 0.0 ) {
+                        bdm_error ( "Particle filter is lost; no particle is good enough." );
                 }
         }
@@ -46 +48 @@
 }
 
-void PF::bayes( const vec &yt, const vec &cond ) {
-        const vec &ut=cond; //todo
-        
+void PF::bayes ( const vec &yt, const vec &cond ) {
+        const vec &ut = cond; //todo
+
         int i;
         // generate samples - time step
-        bayes_gensmp(ut);
+        bayes_gensmp ( ut );
         // weight them - data step
         for ( i = 0; i < n; i++ ) {
@@ -59 +61 @@
         bayes_weights();
 
-        if (do_resampling()) {
-                est.resample ( resmethod);
+        if ( do_resampling() ) {
+                est.resample ( resmethod );
         }
 
@@ -73 +75 @@
 // }
 
-void MPF::bayes ( const vec &yt, const vec &cond ) {    
-        // follows PF::bayes in most places!!!  
+void MPF::bayes ( const vec &yt, const vec &cond ) {
+        // follows PF::bayes in most places!!!
         int i;
-        int n=pf->__w().length();
+        int n = pf->__w().length();
         vec &lls = pf->_lls();
-        Array<vec> &samples=pf->__samples();
-        
+        Array<vec> &samples = pf->__samples();
+
         // generate samples - time step
-        pf->bayes_gensmp(vec(0));
+        pf->bayes_gensmp ( vec ( 0 ) );
         // weight them - data step
-        #pragma parallel for
+#pragma parallel for
         for ( i = 0; i < n; i++ ) {
-                vec bm_cond(BMs(i)->dimensionc());
-                this2bm.fill_cond(yt,cond, bm_cond);
-                pf2bm.filldown(samples(i), bm_cond);
-                BMs(i) -> bayes(this2bm.pushdown(yt), bm_cond);
-                lls ( i ) += BMs(i)->_ll();
+                vec bm_cond ( BMs ( i )->dimensionc() );
+                this2bm.fill_cond ( yt, cond, bm_cond );
+                pf2bm.filldown ( samples ( i ), bm_cond );
+                BMs ( i ) -> bayes ( this2bm.pushdown ( yt ), bm_cond );
+                lls ( i ) += BMs ( i )->_ll();
         }
 
         pf->bayes_weights();
-        
+
         ivec ind;
-        if (pf->do_resampling()) {
-                pf->resample ( ind);
-                
-                #pragma omp parallel for
+        if ( pf->do_resampling() ) {
+                pf->resample ( ind );
+
+#pragma omp parallel for
                 for ( i = 0; i < n; i++ ) {
                         if ( ind ( i ) != i ) {//replace the current Bm by a new one