Changeset 267

Timestamp:

02/11/09 14:15:05 (16 years ago)

Author:

smidl

Message:

samplecond modification

Files:

• bdm/estim/libPF.cpp (modified) (1 diff)
• bdm/estim/libPF.h (modified) (1 diff)
• bdm/stat/libBM.h (modified) (3 diffs)
• bdm/stat/libDS.cpp (modified) (2 diffs)
• bdm/stat/libDS.h (modified) (3 diffs)
• pmsm/pmsm_mix.cpp (modified) (1 diff)

bdm/estim/libPF.cpp

@@ -13 +13 @@
         for ( i=0;i<n;i++ ) {
                 //generate new samples from paramater evolution model;
-                _samples ( i ) = par.samplecond ( _samples ( i ), lls ( i ) );
+                _samples ( i ) = par.samplecond ( _samples ( i ));
+                lls(i )= par._e()->evallog(_samples(i));
                 lls ( i ) *= obs.evallogcond ( dt,_samples ( i ) );
 

bdm/estim/libPF.h

@@ -151 +151 @@
         for ( i=0;i<n;i++ ) {   
                 //generate new samples from paramater evolution model;
-                _samples ( i ) = par.samplecond ( _samples ( i ), llsP ( i ) );
+                _samples ( i ) = par.samplecond ( _samples ( i ) );
+                llsP ( i ) = par._e()->evallog(_samples(i));
                 Bms[i]->condition ( _samples ( i ) );
                 Bms[i]->bayes ( dt );

bdm/stat/libBM.h

@@ -234 +234 @@
         public:
 
-                //! Returns a sample from the density conditioned on \c cond, \f$x \sim epdf(rv|cond)\f$. \param cond is numeric value of \c rv \param ll is a return value of log-likelihood of the sample.
-                virtual vec samplecond ( const vec &cond, double &ll ) {
+                //! Returns a sample from the density conditioned on \c cond, \f$x \sim epdf(rv|cond)\f$. \param cond is numeric value of \c rv 
+                virtual vec samplecond ( const vec &cond) {
                         this->condition ( cond );
                         vec temp= ep->sample();
-                        ll=ep->evallog ( temp );return temp;
+                        return temp;
                 };
                 //! Returns \param N samples from the density conditioned on \c cond, \f$x \sim epdf(rv|cond)\f$. \param cond is numeric value of \c rv \param ll is a return value of log-likelihood of the sample.
@@ -298 +298 @@
 
         */
-
-        /*!
-        @brief Class for storing results (and semi-results) of an experiment
-
-        This class abstracts logging of results from implementation. This class replaces direct logging of results (e.g. to files or to global variables) by calling methods of a logger. Specializations of this abstract class for specific storage method are designed.
-        */
-        class logger : public bdmroot {
-        protected:
-                //! RVs of all logged variables.
-                Array<RV> entries;
-                //! Names of logged quantities, e.g. names of algorithm variants
-                Array<string> names;
-        public:
-                //!Default constructor
-                logger ( ) : entries ( 0 ),names ( 0 ) {}
-
-                //! returns an identifier which will be later needed for calling the log() function
-                virtual int add ( const RV &rv, string name="" ) {
-                        int id=entries.length();
-                        names=concat ( names, name ); // diff
-                        entries.set_length ( id+1,true );
-                        entries ( id ) = rv;
-                        return id; // identifier of the last entry
-                }
-
-                //! log this vector
-                virtual void logit ( int id, const vec &v ) =0;
-
-                //! Shifts storage position for another time step.
-                virtual void step() =0;
-
-                //! Finalize storing information
-                virtual void finalize() {};
-
-                //! Initialize the storage
-                virtual void init() {};
-
-                //! for future use
-                virtual ~logger() {};
-        };
-
         class datalink_e2e {
         protected:
@@ -418 +377 @@
                 //! Fill
 
+        };
+
+        /*!
+        @brief Class for storing results (and semi-results) of an experiment
+
+        This class abstracts logging of results from implementation. This class replaces direct logging of results (e.g. to files or to global variables) by calling methods of a logger. Specializations of this abstract class for specific storage method are designed.
+         */
+        class logger : public bdmroot {
+                protected:
+                //! RVs of all logged variables.
+                        Array<RV> entries;
+                //! Names of logged quantities, e.g. names of algorithm variants
+                        Array<string> names;
+                public:
+                //!Default constructor
+                        logger ( ) : entries ( 0 ),names ( 0 ) {}
+
+                //! returns an identifier which will be later needed for calling the log() function
+                        virtual int add ( const RV &rv, string name="" ) {
+                                int id=entries.length();
+                                names=concat ( names, name ); // diff
+                                entries.set_length ( id+1,true );
+                                entries ( id ) = rv;
+                                return id; // identifier of the last entry
+                        }
+
+                //! log this vector
+                        virtual void logit ( int id, const vec &v ) =0;
+
+                //! Shifts storage position for another time step.
+                        virtual void step() =0;
+
+                //! Finalize storing information
+                        virtual void finalize() {};
+
+                //! Initialize the storage
+                        virtual void init() {};
+
+                //! for future use
+                        virtual ~logger() {};
         };
 

bdm/stat/libDS.cpp

@@ -43 +43 @@
 
 void ArxDS::step() {
-        double tmp;
         //shift history
         H.shift_right ( 0, Drv.count() +Urv.count() );
@@ -52 +51 @@
         rgr = rgrlnk.get_val ( H );
         // Eval Y
-        H.set_subvector ( 0, model.samplecond ( rgr,tmp ) );
+        H.set_subvector ( 0, model.samplecond ( rgr ) );
 
 }

bdm/stat/libDS.h

@@ -73 +73 @@
                 int L_theta;
                 int L_R;
-                public:
+        public:
                 void getdata ( vec &dt ) {
                         it_assert_debug ( dt.length() ==Drv.count(),"ArxDS" );
@@ -104 +104 @@
                         mat &A =model._A();
                         mat R =model._R();
-                        if ( opt_L_theta ) {L_theta=L.add ( RV("{theta }", vec_1(A.rows() *A.cols())),"t" );}
-                        if ( opt_L_theta ) {L_R=L.add ( RV("{R }", vec_1(R.rows() *R.cols())),"r" );}
+                        if ( opt_L_theta ) {L_theta=L.add ( RV ( "{theta }", vec_1 ( A.rows() *A.cols() ) ),"t" );}
+                        if ( opt_L_theta ) {L_R=L.add ( RV ( "{R }", vec_1 ( R.rows() *R.cols() ) ),"r" );}
                 }
                 virtual void logit ( logger &L ) {
@@ -126 +126 @@
 
         };
+
+        class stateDS : public DS {
+        protected:
+                //!conditional pdf of the state evolution \f$ f(x_t|x_{t-1}) \f$
+                mpdf* IM;
+                //!conditional pdf of the observations \f$ f(d_t|x_t) \f$
+                mpdf* OM;
+                //! result storage
+                vec dt;
+                //! state storage
+                vec xt;
+                //! input storage
+                vec ut;
+                //! Logger
+                int L_xt;
+        public:
+                void getdata ( vec &dt0 ) {dt0=dt;}
+                void getdata ( vec &dt0, const ivec &indeces ) {dt0=dt ( indeces );}
+
+                stateDS ( mpdf* IM0, mpdf* OM0, RV &Urv0 ) :DS ( OM0->_rv(),Urv0 ),IM ( IM0 ),OM ( OM0 ),
+                                dt ( OM0->_rv().count() ), xt ( IM0->_rv().count() ), ut ( Urv0.count() ) {}
+                ~stateDS() {delete IM; delete OM;}
+                virtual void step() {
+                        double tmp;
+                        xt=IM->samplecond(concat ( xt,ut ));
+                        dt=OM->samplecond(concat ( xt,ut ));
+                };
+                
+                virtual void log_add ( logger &L ) {
+                        DS::log_add ( L );
+                        L_xt=L.add(IM->_rv(),"true");
+                }
+                virtual void logit ( logger &L ) {
+                        DS::logit ( L );
+                        L.logit ( L_xt,xt);
+                }
+
+        };
+
 }; //namespace
 

pmsm/pmsm_mix.cpp

@@ -94 +94 @@
         L.init();
 
-double dum=0.0;
 vec dumvec = vec_1(1.0);
-vec z=  evolQR.samplecond(dumvec,dum) ;
+vec z=  evolQR.samplecond(dumvec) ;
 cout << z << endl;