| 1 | /*! |
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| 2 | \file |
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| 3 | \brief Common DataSources. |
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| 4 | \author Vaclav Smidl. |
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| 5 | |
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| 6 | ----------------------------------- |
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| 7 | BDM++ - C++ library for Bayesian Decision Making under Uncertainty |
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| 8 | |
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| 9 | Using IT++ for numerical operations |
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| 10 | ----------------------------------- |
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| 11 | */ |
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| 12 | |
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| 13 | #ifndef DS_H |
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| 14 | #define DS_H |
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| 15 | |
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| 16 | |
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| 17 | #include "libBM.h" |
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| 18 | #include "libEF.h" |
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| 19 | |
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| 20 | |
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| 21 | namespace bdm { |
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| 22 | /*! |
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| 23 | * \brief Memory storage of off-line data column-wise |
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| 24 | |
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| 25 | The data are stored in an internal matrix \c Data . Each column of Data corresponds to one discrete time observation \f$t\f$. Access to this matrix is via indexes \c rowid and \c delays. |
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| 26 | |
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| 27 | The data can be loaded from a file. |
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| 28 | */ |
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| 29 | class MemDS : public DS { |
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| 30 | //! internal matrix of data |
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| 31 | mat Data; |
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| 32 | //! active column in the Data matrix |
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| 33 | int time; |
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| 34 | //! vector of rows that are presented in Dt |
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| 35 | ivec rowid; |
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| 36 | //! vector of delays that are presented in Dt |
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| 37 | ivec delays; |
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| 38 | |
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| 39 | public: |
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| 40 | void getdata ( vec &dt ); |
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| 41 | void getdata ( vec &dt, const ivec &indeces ); |
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| 42 | void linkrvs ( RV &drv, RV &urv ); |
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| 43 | void write ( vec &ut ) {it_error ( "MemDS::write is not supported" );} |
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| 44 | void write ( vec &ut,ivec &indexes ) {it_error ( "MemDS::write is not supported" );} |
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| 45 | void step(); |
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| 46 | //!Default constructor |
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| 47 | MemDS ( mat &Dat, ivec &rowid, ivec &delays ); |
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| 48 | }; |
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| 49 | |
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| 50 | /*! |
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| 51 | \brief Generator of ARX data |
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| 52 | |
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| 53 | */ |
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| 54 | class ArxDS : public DS { |
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| 55 | //! Rv of the regressor |
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| 56 | RV Rrv; |
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| 57 | //! Rv of the history (full regressor) |
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| 58 | RV Hrv; |
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| 59 | //! Internal storage of results |
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| 60 | vec Y; |
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| 61 | //! History, ordered as \f$[u_t, y_{t-1 }, u_{t-1}, \ldots]\f$ |
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| 62 | vec H; |
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| 63 | //! temporary variable for regressor |
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| 64 | vec rgr; |
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| 65 | //! data link: val = y, cond = u; local = rgr; |
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| 66 | datalink_e2e rgrlnk; |
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| 67 | //! model of Y - linear Gaussian |
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| 68 | mlnorm<chmat> model; |
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| 69 | public: |
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| 70 | void getdata ( vec &dt ){it_assert_debug(dt.length()==Y.length(),"ArxDS"); |
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| 71 | dt=concat(Y,H.left(Urv.count()));}; |
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| 72 | void getdata ( vec &dt, const ivec &indexes ){it_assert_debug(dt.length()==Y.length(),"ArxDS"); dt=Y(indexes);}; |
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| 73 | void write ( vec &ut ){it_assert_debug(ut.length()==Urv.count(),"ArxDS"); H.set_subvector(0,ut);}; |
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| 74 | void write ( vec &ut, const ivec &indexes ){it_assert_debug(ut.length()==Urv.count(),"ArxDS"); set_subvector(H,indexes,ut);}; |
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| 75 | void step(); |
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| 76 | //!Default constructor |
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| 77 | ArxDS ( RV &drv, RV &urv, RV &rrv); |
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| 78 | //! Set parameters of the internal model |
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| 79 | void set_parameters(const mat &Th0, const vec mu0, const chmat &sqR0) |
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| 80 | {model.set_parameters(Th0, mu0, sqR0); }; |
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| 81 | }; |
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| 82 | |
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| 83 | }; //namespace |
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| 84 | |
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| 85 | #endif // DS_H |
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