| 30 | | protected: |
| 31 | | //! internal matrix of data |
| 32 | | mat Data; |
| 33 | | //! active column in the Data matrix |
| 34 | | int time; |
| 35 | | //! vector of rows that are presented in Dt |
| 36 | | ivec rowid; |
| 37 | | //! vector of delays that are presented in Dt |
| 38 | | ivec delays; |
| 39 | | |
| 40 | | public: |
| 41 | | void getdata ( vec &dt ); |
| 42 | | void getdata ( vec &dt, const ivec &indeces ); |
| 43 | | void set_rvs ( RV &drv, RV &urv ); |
| 44 | | |
| 45 | | void write ( vec &ut ) { |
| 46 | | bdm_error ( "MemDS::write is not supported" ); |
| 47 | | } |
| 48 | | |
| 49 | | void write ( vec &ut, ivec &indices ) { |
| 50 | | bdm_error ( "MemDS::write is not supported" ); |
| 51 | | } |
| 52 | | |
| 53 | | void step(); |
| 54 | | //!Default constructor |
| 55 | | MemDS () {}; |
| 56 | | MemDS ( mat &Dat, ivec &rowid0, ivec &delays0 ); |
| 57 | | }; |
| | 30 | protected: |
| | 31 | //! internal matrix of data |
| | 32 | mat Data; |
| | 33 | //! active column in the Data matrix |
| | 34 | int time; |
| | 35 | //! vector of rows that are presented in Dt |
| | 36 | ivec rowid; |
| | 37 | //! vector of delays that are presented in Dt |
| | 38 | ivec delays; |
| | 39 | |
| | 40 | public: |
| | 41 | void getdata ( vec &dt ); |
| | 42 | void getdata ( vec &dt, const ivec &indeces ); |
| | 43 | void set_rvs ( RV &drv, RV &urv ); |
| | 44 | |
| | 45 | void write ( vec &ut ) { |
| | 46 | bdm_error ( "MemDS::write is not supported" ); |
| | 47 | } |
| | 48 | |
| | 49 | void write ( vec &ut, ivec &indices ) { |
| | 50 | bdm_error ( "MemDS::write is not supported" ); |
| | 51 | } |
| | 52 | |
| | 53 | void step(); |
| | 54 | //!Default constructor |
| | 55 | MemDS () {}; |
| | 56 | MemDS ( mat &Dat, ivec &rowid0, ivec &delays0 ); |
| | 57 | }; |
| | 58 | |
| | 59 | /*! \brief Simulate data from a static pdf |
| | 60 | Trivial example of a data source, could be used for tests of some estimation algorithms. For example, simulating data from a mixture model and feeding them to mixture model estimators. |
| | 61 | */ |
| | 62 | |
| | 63 | class EpdfDS: public DS { |
| | 64 | protected: |
| | 65 | //! internal pointer to epdf from which we samplecond |
| | 66 | shared_ptr<epdf> iepdf; |
| | 67 | //! internal storage of data sample |
| | 68 | vec dt; |
| | 69 | public: |
| | 70 | void step() { |
| | 71 | dt=iepdf->sample(); |
| | 72 | } |
| | 73 | void getdata ( vec &dt_out ) { |
| | 74 | dt_out = dt; |
| | 75 | } |
| | 76 | void getdata ( vec &dt_out, const ivec &ids ) { |
| | 77 | dt_out = dt ( ids ); |
| | 78 | } |
| | 79 | const RV& _drv() { |
| | 80 | return iepdf->_rv(); |
| | 81 | } |
| | 82 | |
| | 83 | /*! |
| | 84 | \code |
| | 85 | class = "PdfDS"; |
| | 86 | epdf = {class="epdf_offspring", ...}// list of points |
| | 87 | \endcode |
| | 88 | |
| | 89 | */ |
| | 90 | void from_setting ( const Setting &set ) { |
| | 91 | iepdf=UI::build<epdf> ( set,"epdf",UI::compulsory ); |
| | 92 | dt = zeros ( iepdf->dimension() ); |
| | 93 | } |
| | 94 | }; |
| | 95 | UIREGISTER ( EpdfDS ); |
| | 96 | |
| | 97 | /*! \brief Simulate data from conditional density |
| | 98 | Still having only one density but allowing conditioning on either input or delayed values. |
| | 99 | */ |
| | 100 | class MpdfDS :public DS { |
| | 101 | protected: |
| | 102 | //! internal pointer to epdf from which we samplecond |
| | 103 | shared_ptr<mpdf> impdf; |
| | 104 | //! internal storage of data sample |
| | 105 | vec dt; |
| | 106 | //! input vector |
| | 107 | vec ut; |
| | 108 | //! datalink between dt and ut and regressor |
| | 109 | datalink_2to1_buffered rgrlink; |
| | 110 | //! numeric values of regressor |
| | 111 | vec rgr; |
| | 112 | |
| | 113 | public: |
| | 114 | void step() { |
| | 115 | rgrlink.filldown ( dt,ut,rgr ); |
| | 116 | rgrlink.step(dt,ut);//whist history |
| | 117 | dt=impdf->samplecond ( rgr ); |
| | 118 | } |
| | 119 | void getdata ( vec &dt_out ) { |
| | 120 | dt_out = dt; |
| | 121 | } |
| | 122 | void getdata ( vec &dt_out, const ivec &ids ) { |
| | 123 | dt_out = dt ( ids ); |
| | 124 | } |
| | 125 | const RV& _drv() const { |
| | 126 | return impdf->_rv(); |
| | 127 | } |
| | 128 | void write(const vec &ut0){ut=ut0;} |
| | 129 | |
| | 130 | /*! |
| | 131 | \code |
| | 132 | class = "MpdfDS"; |
| | 133 | mpdf = {class="epdf_offspring", ...}// list of points |
| | 134 | \endcode |
| | 135 | |
| | 136 | */ |
| | 137 | void from_setting ( const Setting &set ) { |
| | 138 | impdf=UI::build<mpdf> ( set,"mpdf",UI::compulsory ); |
| | 139 | |
| | 140 | // get unique rvs form rvc |
| | 141 | RV rgrv0=impdf->_rvc().remove_time(); |
| | 142 | // input is what in not in _rv() |
| | 143 | RV urv=rgrv0.subt(impdf->_rv()); |
| | 144 | set_drv(impdf->_rv(), urv); |
| | 145 | // connect input and output to rvc |
| | 146 | rgrlink.set_connection(impdf->_rvc(), Drv,Urv); |
| | 147 | |
| | 148 | dt = zeros ( impdf->dimension() ); |
| | 149 | rgr = zeros ( impdf->dimensionc() ); |
| | 150 | ut = zeros(urv._dsize()); |
| | 151 | } |
| | 152 | }; |
| | 153 | UIREGISTER ( MpdfDS ); |
| 134 | | protected: |
| 135 | | //! Rv of the regressor |
| 136 | | RV Rrv; |
| 137 | | //! History, ordered as \f$[y_t, u_t, y_{t-1 }, u_{t-1}, \ldots]\f$ |
| 138 | | vec H; |
| 139 | | //! (future) input |
| 140 | | vec U; |
| 141 | | //! temporary variable for regressor |
| 142 | | vec rgr; |
| 143 | | //! data link: H -> rgr |
| 144 | | datalink rgrlnk; |
| 145 | | //! model of Y - linear Gaussian |
| 146 | | mlnorm<chmat> model; |
| 147 | | //! options |
| 148 | | bool opt_L_theta; |
| 149 | | //! loggers |
| 150 | | int L_theta; |
| 151 | | int L_R; |
| 152 | | int dt_size; |
| 153 | | public: |
| 154 | | void getdata ( vec &dt ) { |
| 155 | | dt = H; |
| 156 | | } |
| 157 | | |
| 158 | | void getdata ( vec &dt, const ivec &indices ) { |
| 159 | | dt = H ( indices ); |
| 160 | | } |
| 161 | | |
| 162 | | void write ( vec &ut ) { |
| 163 | | U = ut; |
| 164 | | } |
| 165 | | |
| 166 | | void write ( vec &ut, const ivec &indices ) { |
| 167 | | bdm_assert_debug ( ut.length() == indices.length(), "ArxDS" ); |
| 168 | | set_subvector ( U, indices, ut ); |
| 169 | | } |
| 170 | | |
| 171 | | void step(); |
| 172 | | |
| 173 | | //!Default constructor |
| 174 | | ArxDS ( ) {}; |
| 175 | | //! Set parameters of the internal model, H is maximum time delay |
| 176 | | void set_parameters ( const mat &Th0, const vec mu0, const chmat &sqR0 ) { |
| 177 | | model.set_parameters ( Th0, mu0, sqR0 ); |
| 178 | | }; |
| 179 | | //! Set |
| 180 | | void set_drv ( const RV &yrv, const RV &urv, const RV &rrv ) { |
| 181 | | Rrv = rrv; |
| 182 | | Urv = urv; |
| 183 | | dt_size = yrv._dsize() + urv._dsize(); |
| 184 | | |
| 185 | | RV drv = concat ( yrv, urv ); |
| 186 | | Drv = drv; |
| 187 | | int td = rrv.mint(); |
| 188 | | H.set_size ( drv._dsize() * ( -td + 1 ) ); |
| 189 | | U.set_size ( Urv._dsize() ); |
| 190 | | for ( int i = -1; i >= td; i-- ) { |
| 191 | | drv.t ( -1 ); |
| 192 | | Drv.add ( drv ); //shift u1 |
| 193 | | } |
| 194 | | rgrlnk.set_connection ( rrv, Drv ); |
| 195 | | |
| 196 | | dtsize = Drv._dsize(); |
| 197 | | utsize = Urv._dsize(); |
| 198 | | } |
| 199 | | //! set options from a string |
| 200 | | void set_options ( const string &s ) { |
| 201 | | opt_L_theta = ( s.find ( "L_theta" ) != string::npos ); |
| 202 | | }; |
| 203 | | virtual void log_add ( logger &L ) { |
| 204 | | //DS::log_add ( L ); too long!! |
| 205 | | L_dt = L.add ( Drv ( 0, dt_size ), "" ); |
| 206 | | L_ut = L.add ( Urv, "" ); |
| 207 | | |
| 208 | | mat &A = model._A(); |
| 209 | | mat R = model._R(); |
| 210 | | if ( opt_L_theta ) { |
| 211 | | L_theta = L.add ( RV ( "{th }", vec_1 ( A.rows() * A.cols() ) ), "t" ); |
| 212 | | } |
| 213 | | if ( opt_L_theta ) { |
| 214 | | L_R = L.add ( RV ( "{R }", vec_1 ( R.rows() * R.cols() ) ), "r" ); |
| 215 | | } |
| 216 | | } |
| 217 | | virtual void logit ( logger &L ) { |
| 218 | | //DS::logit ( L ); |
| 219 | | L.logit ( L_dt, H.left ( dt_size ) ); |
| 220 | | L.logit ( L_ut, U ); |
| 221 | | |
| 222 | | mat &A = model._A(); |
| 223 | | mat R = model._R(); |
| 224 | | if ( opt_L_theta ) { |
| 225 | | L.logit ( L_theta, vec ( A._data(), A.rows() *A.cols() ) ); |
| 226 | | }; |
| 227 | | if ( opt_L_theta ) { |
| 228 | | L.logit ( L_R, vec ( R._data(), R.rows() *R.rows() ) ); |
| 229 | | }; |
| 230 | | } |
| 231 | | |
| 232 | | // TODO dokumentace - aktualizovat |
| 233 | | /*! UI for ArxDS using factorized description! |
| 234 | | |
| 235 | | The ArxDS is constructed from a structure with fields: |
| 236 | | \code |
| 237 | | system = { |
| 238 | | type = "ArxDS"; |
| 239 | | // description of y variables |
| 240 | | y = {type="rv"; names=["y", "u"];}; |
| 241 | | // description of u variable |
| 242 | | u = {type="rv"; names=[];} |
| 243 | | // description of regressor |
| 244 | | rgr = {type="rv"; |
| 245 | | names = ["y","y","y","u"]; |
| 246 | | times = [-1, -2, -3, -1]; |
| 247 | | } |
| 248 | | |
| 249 | | // theta |
| 250 | | theta = [0.8, -0.3, 0.4, 1.0, |
| 251 | | 0.0, 0.0, 0.0, 0.0]; |
| 252 | | // offset (optional) |
| 253 | | offset = [0.0, 0.0]; |
| 254 | | //variance |
| 255 | | r = [0.1, 0.0, |
| 256 | | 0.0, 1.0]; |
| 257 | | //options: L_theta = log value of theta, |
| 258 | | opt = "L_theta"; |
| 259 | | }; |
| 260 | | \endcode |
| 261 | | |
| 262 | | Result is ARX data source offering with full history as Drv. |
| 263 | | */ |
| 264 | | void from_setting ( const Setting &set ); |
| 265 | | |
| 266 | | // TODO dodelat void to_setting( Setting &set ) const; |
| | 230 | protected: |
| | 231 | //! Rv of the regressor |
| | 232 | RV Rrv; |
| | 233 | //! History, ordered as \f$[y_t, u_t, y_{t-1 }, u_{t-1}, \ldots]\f$ |
| | 234 | vec H; |
| | 235 | //! (future) input |
| | 236 | vec U; |
| | 237 | //! temporary variable for regressor |
| | 238 | vec rgr; |
| | 239 | //! data link: H -> rgr |
| | 240 | datalink rgrlnk; |
| | 241 | //! model of Y - linear Gaussian |
| | 242 | mlnorm<chmat> model; |
| | 243 | //! options |
| | 244 | bool opt_L_theta; |
| | 245 | //! loggers |
| | 246 | int L_theta; |
| | 247 | int L_R; |
| | 248 | int dt_size; |
| | 249 | public: |
| | 250 | void getdata ( vec &dt ) { |
| | 251 | dt = H; |
| | 252 | } |
| | 253 | |
| | 254 | void getdata ( vec &dt, const ivec &indices ) { |
| | 255 | dt = H ( indices ); |
| | 256 | } |
| | 257 | |
| | 258 | void write ( vec &ut ) { |
| | 259 | U = ut; |
| | 260 | } |
| | 261 | |
| | 262 | void write ( vec &ut, const ivec &indices ) { |
| | 263 | bdm_assert_debug ( ut.length() == indices.length(), "ArxDS" ); |
| | 264 | set_subvector ( U, indices, ut ); |
| | 265 | } |
| | 266 | |
| | 267 | void step(); |
| | 268 | |
| | 269 | //!Default constructor |
| | 270 | ArxDS ( ) {}; |
| | 271 | //! Set parameters of the internal model, H is maximum time delay |
| | 272 | void set_parameters ( const mat &Th0, const vec mu0, const chmat &sqR0 ) { |
| | 273 | model.set_parameters ( Th0, mu0, sqR0 ); |
| | 274 | }; |
| | 275 | //! Set |
| | 276 | void set_drv ( const RV &yrv, const RV &urv, const RV &rrv ) { |
| | 277 | Rrv = rrv; |
| | 278 | Urv = urv; |
| | 279 | dt_size = yrv._dsize() + urv._dsize(); |
| | 280 | |
| | 281 | RV drv = concat ( yrv, urv ); |
| | 282 | Drv = drv; |
| | 283 | int td = rrv.mint(); |
| | 284 | H.set_size ( drv._dsize() * ( -td + 1 ) ); |
| | 285 | U.set_size ( Urv._dsize() ); |
| | 286 | for ( int i = -1; i >= td; i-- ) { |
| | 287 | drv.t ( -1 ); |
| | 288 | Drv.add ( drv ); //shift u1 |
| | 289 | } |
| | 290 | rgrlnk.set_connection ( rrv, Drv ); |
| | 291 | |
| | 292 | dtsize = Drv._dsize(); |
| | 293 | utsize = Urv._dsize(); |
| | 294 | } |
| | 295 | //! set options from a string |
| | 296 | void set_options ( const string &s ) { |
| | 297 | opt_L_theta = ( s.find ( "L_theta" ) != string::npos ); |
| | 298 | }; |
| | 299 | virtual void log_add ( logger &L ) { |
| | 300 | //DS::log_add ( L ); too long!! |
| | 301 | L_dt = L.add ( Drv ( 0, dt_size ), "" ); |
| | 302 | L_ut = L.add ( Urv, "" ); |
| | 303 | |
| | 304 | mat &A = model._A(); |
| | 305 | mat R = model._R(); |
| | 306 | if ( opt_L_theta ) { |
| | 307 | L_theta = L.add ( RV ( "{th }", vec_1 ( A.rows() * A.cols() ) ), "t" ); |
| | 308 | } |
| | 309 | if ( opt_L_theta ) { |
| | 310 | L_R = L.add ( RV ( "{R }", vec_1 ( R.rows() * R.cols() ) ), "r" ); |
| | 311 | } |
| | 312 | } |
| | 313 | virtual void logit ( logger &L ) { |
| | 314 | //DS::logit ( L ); |
| | 315 | L.logit ( L_dt, H.left ( dt_size ) ); |
| | 316 | L.logit ( L_ut, U ); |
| | 317 | |
| | 318 | mat &A = model._A(); |
| | 319 | mat R = model._R(); |
| | 320 | if ( opt_L_theta ) { |
| | 321 | L.logit ( L_theta, vec ( A._data(), A.rows() *A.cols() ) ); |
| | 322 | }; |
| | 323 | if ( opt_L_theta ) { |
| | 324 | L.logit ( L_R, vec ( R._data(), R.rows() *R.rows() ) ); |
| | 325 | }; |
| | 326 | } |
| | 327 | |
| | 328 | // TODO dokumentace - aktualizovat |
| | 329 | /*! UI for ArxDS using factorized description! |
| | 330 | |
| | 331 | The ArxDS is constructed from a structure with fields: |
| | 332 | \code |
| | 333 | system = { |
| | 334 | type = "ArxDS"; |
| | 335 | // description of y variables |
| | 336 | y = {type="rv"; names=["y", "u"];}; |
| | 337 | // description of u variable |
| | 338 | u = {type="rv"; names=[];} |
| | 339 | // description of regressor |
| | 340 | rgr = {type="rv"; |
| | 341 | names = ["y","y","y","u"]; |
| | 342 | times = [-1, -2, -3, -1]; |
| | 343 | } |
| | 344 | |
| | 345 | // theta |
| | 346 | theta = [0.8, -0.3, 0.4, 1.0, |
| | 347 | 0.0, 0.0, 0.0, 0.0]; |
| | 348 | // offset (optional) |
| | 349 | offset = [0.0, 0.0]; |
| | 350 | //variance |
| | 351 | r = [0.1, 0.0, |
| | 352 | 0.0, 1.0]; |
| | 353 | //options: L_theta = log value of theta, |
| | 354 | opt = "L_theta"; |
| | 355 | }; |
| | 356 | \endcode |
| | 357 | |
| | 358 | Result is ARX data source offering with full history as Drv. |
| | 359 | */ |
| | 360 | void from_setting ( const Setting &set ); |
| | 361 | |
| | 362 | // TODO dodelat void to_setting( Setting &set ) const; |
| 273 | | private: |
| 274 | | //!conditional pdf of the state evolution \f$ f(x_t|x_{t-1}) \f$ |
| 275 | | shared_ptr<mpdf> IM; |
| 276 | | |
| 277 | | //!conditional pdf of the observations \f$ f(d_t|x_t) \f$ |
| 278 | | shared_ptr<mpdf> OM; |
| 279 | | |
| 280 | | protected: |
| 281 | | //! result storage |
| 282 | | vec dt; |
| 283 | | //! state storage |
| 284 | | vec xt; |
| 285 | | //! input storage |
| 286 | | vec ut; |
| 287 | | //! Logger |
| 288 | | int L_xt; |
| 289 | | |
| 290 | | public: |
| 291 | | void getdata ( vec &dt0 ) { |
| 292 | | dt0 = dt; |
| 293 | | } |
| 294 | | |
| 295 | | void getdata ( vec &dt0, const ivec &indices ) { |
| 296 | | dt0 = dt ( indices ); |
| 297 | | } |
| 298 | | |
| 299 | | stateDS ( const shared_ptr<mpdf> &IM0, const shared_ptr<mpdf> &OM0, int usize ) : IM ( IM0 ), OM ( OM0 ), |
| 300 | | dt ( OM0->dimension() ), xt ( IM0->dimension() ), |
| 301 | | ut ( usize ), L_xt(0) { } |
| 302 | | |
| 303 | | stateDS() : L_xt(0) { } |
| 304 | | |
| 305 | | virtual void step() { |
| 306 | | xt = IM->samplecond ( concat ( xt, ut ) ); |
| 307 | | dt = OM->samplecond ( concat ( xt, ut ) ); |
| 308 | | } |
| 309 | | |
| 310 | | virtual void log_add ( logger &L ) { |
| 311 | | DS::log_add ( L ); |
| 312 | | L_xt = L.add ( IM->_rv(), "true" ); |
| 313 | | } |
| 314 | | virtual void logit ( logger &L ) { |
| 315 | | DS::logit ( L ); |
| 316 | | L.logit ( L_xt, xt ); |
| 317 | | } |
| 318 | | |
| 319 | | /*! UI for stateDS |
| 320 | | |
| 321 | | The DS is constructed from a structure with fields: |
| 322 | | \code |
| 323 | | system = { |
| 324 | | type = "stateDS"; |
| 325 | | //Internal model |
| 326 | | IM = { type = "mpdf"; //<-- valid offspring! e.g. "mlnorm" |
| 327 | | rv = { //description of x_t |
| 328 | | names=["name1",...]; |
| 329 | | sizes=[2,1]; // optional default=[1,1...]; |
| 330 | | times=[0,0]; // optional default=[0,0...]; |
| 331 | | } |
| 332 | | rvu= { //description of u_t |
| 333 | | //optional default=empty |
| 334 | | } |
| 335 | | |
| 336 | | // remaining fields depending on the chosen type |
| 337 | | }; |
| 338 | | //Observation model |
| 339 | | OM = { type = "mpdf-offspring"; |
| 340 | | rv = {}; //description of d_t |
| 341 | | rvu = {type="internal", path="system.IM.rvu"}; //description of u_t |
| 342 | | |
| 343 | | //remaining fields |
| 344 | | } |
| 345 | | }; |
| 346 | | \endcode |
| 347 | | */ |
| 348 | | void from_setting ( const Setting &set ); |
| 349 | | |
| 350 | | // TODO dodelat void to_setting( Setting &set ) const; |
| | 369 | private: |
| | 370 | //!conditional pdf of the state evolution \f$ f(x_t|x_{t-1}) \f$ |
| | 371 | shared_ptr<mpdf> IM; |
| | 372 | |
| | 373 | //!conditional pdf of the observations \f$ f(d_t|x_t) \f$ |
| | 374 | shared_ptr<mpdf> OM; |
| | 375 | |
| | 376 | protected: |
| | 377 | //! result storage |
| | 378 | vec dt; |
| | 379 | //! state storage |
| | 380 | vec xt; |
| | 381 | //! input storage |
| | 382 | vec ut; |
| | 383 | //! Logger |
| | 384 | int L_xt; |
| | 385 | |
| | 386 | public: |
| | 387 | void getdata ( vec &dt0 ) { |
| | 388 | dt0 = dt; |
| | 389 | } |
| | 390 | |
| | 391 | void getdata ( vec &dt0, const ivec &indices ) { |
| | 392 | dt0 = dt ( indices ); |
| | 393 | } |
| | 394 | |
| | 395 | stateDS ( const shared_ptr<mpdf> &IM0, const shared_ptr<mpdf> &OM0, int usize ) : IM ( IM0 ), OM ( OM0 ), |
| | 396 | dt ( OM0->dimension() ), xt ( IM0->dimension() ), |
| | 397 | ut ( usize ), L_xt ( 0 ) { } |
| | 398 | |
| | 399 | stateDS() : L_xt ( 0 ) { } |
| | 400 | |
| | 401 | virtual void step() { |
| | 402 | xt = IM->samplecond ( concat ( xt, ut ) ); |
| | 403 | dt = OM->samplecond ( concat ( xt, ut ) ); |
| | 404 | } |
| | 405 | |
| | 406 | virtual void log_add ( logger &L ) { |
| | 407 | DS::log_add ( L ); |
| | 408 | L_xt = L.add ( IM->_rv(), "true" ); |
| | 409 | } |
| | 410 | virtual void logit ( logger &L ) { |
| | 411 | DS::logit ( L ); |
| | 412 | L.logit ( L_xt, xt ); |
| | 413 | } |
| | 414 | |
| | 415 | /*! UI for stateDS |
| | 416 | |
| | 417 | The DS is constructed from a structure with fields: |
| | 418 | \code |
| | 419 | system = { |
| | 420 | type = "stateDS"; |
| | 421 | //Internal model |
| | 422 | IM = { type = "mpdf"; //<-- valid offspring! e.g. "mlnorm" |
| | 423 | rv = { //description of x_t |
| | 424 | names=["name1",...]; |
| | 425 | sizes=[2,1]; // optional default=[1,1...]; |
| | 426 | times=[0,0]; // optional default=[0,0...]; |
| | 427 | } |
| | 428 | rvu= { //description of u_t |
| | 429 | //optional default=empty |
| | 430 | } |
| | 431 | |
| | 432 | // remaining fields depending on the chosen type |
| | 433 | }; |
| | 434 | //Observation model |
| | 435 | OM = { type = "mpdf-offspring"; |
| | 436 | rv = {}; //description of d_t |
| | 437 | rvu = {type="internal", path="system.IM.rvu"}; //description of u_t |
| | 438 | |
| | 439 | //remaining fields |
| | 440 | } |
| | 441 | }; |
| | 442 | \endcode |
| | 443 | */ |
| | 444 | void from_setting ( const Setting &set ); |
| | 445 | |
| | 446 | // TODO dodelat void to_setting( Setting &set ) const; |