[2] | 1 | /*! |
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[5] | 2 | \file |
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| 3 | \brief Bayesian Models (bm) that use Bayes rule to learn from observations |
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| 4 | \author Vaclav Smidl. |
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[2] | 5 | |
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[5] | 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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[2] | 13 | #ifndef BM_H |
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| 14 | #define BM_H |
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| 15 | |
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| 16 | #include <itpp/itbase.h> |
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| 17 | //#include <std> |
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| 18 | |
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| 19 | using namespace itpp; |
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| 20 | |
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[5] | 21 | /*! |
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| 22 | * \brief Class representing variables, most often random variables |
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| 23 | |
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| 24 | * More?... |
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| 25 | */ |
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[2] | 26 | class RV { |
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[5] | 27 | int len; |
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| 28 | ivec ids; |
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| 29 | ivec sizes; |
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| 30 | ivec times; |
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| 31 | ivec obs; |
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| 32 | Array<std::string> names; |
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[2] | 33 | |
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[5] | 34 | private: |
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| 35 | void init ( ivec in_ids, Array<std::string> in_names, ivec in_sizes, ivec in_times, ivec in_obs ); |
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[2] | 36 | public: |
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[5] | 37 | //! Full constructor which is called by the others |
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| 38 | RV ( ivec in_ids, Array<std::string> in_names, ivec in_sizes, ivec in_times, ivec in_obs ); |
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| 39 | //! default constructor |
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| 40 | RV ( ivec ids ); |
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| 41 | //! Printing output e.g. for debugging. |
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| 42 | friend std::ostream &operator<< ( std::ostream &os, const RV &rv ); |
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| 43 | |
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| 44 | //! Find indexes of another rv in self |
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| 45 | ivec rvfind(RV rv2); |
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| 46 | //! Add (concat) another variable to the current one |
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| 47 | RV rvadd(RV rv2); |
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| 48 | //! Subtract another variable from the current one |
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| 49 | RV rvsubt(RV rv2); |
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| 50 | //! Select only variables at indeces ind |
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| 51 | RV rvsubselect(ivec ind); |
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| 52 | //! Select only variables at indeces ind |
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| 53 | RV operator()(ivec ind); |
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[2] | 54 | }; |
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| 55 | |
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| 56 | |
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| 57 | |
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| 58 | |
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| 59 | //! Class representing function of variables |
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| 60 | class fnc { |
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[5] | 61 | RV rv; |
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[2] | 62 | }; |
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| 63 | |
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[4] | 64 | //! Bayesian Model of the world, i.e. all uncertainty is modeled by probabilities. |
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[2] | 65 | class BM { |
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| 66 | public: |
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[5] | 67 | //! Incremental Bayes rule |
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| 68 | void bayes ( vec dt ); |
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| 69 | //! Batch Bayes rule (columns of Dt are observations) |
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| 70 | virtual void bayes ( mat Dt ); |
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[2] | 71 | }; |
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| 72 | |
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[4] | 73 | //! Probability density function with numerical statistics, e.g. posterior density. |
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[2] | 74 | class epdf { |
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[5] | 75 | RV rv; |
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[2] | 76 | public: |
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[5] | 77 | //! Returns the required moment of the epdf |
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| 78 | virtual vec moment ( const int order = 1 ); |
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[2] | 79 | }; |
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| 80 | |
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[5] | 81 | //! Conditional probability density, e.g. modeling some dependencies. |
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[2] | 82 | class mpdf { |
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[5] | 83 | //! modeled random variable |
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| 84 | RV rv; |
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| 85 | //! random variable in condition |
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| 86 | RV rvc; |
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[2] | 87 | public: |
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| 88 | |
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[5] | 89 | //! Returns the required moment of the epdf |
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| 90 | virtual fnc moment ( const int order = 1 ); |
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[2] | 91 | }; |
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| 92 | |
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| 93 | #endif // BM_H |
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