BNdistance.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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#ifndef GUM_KL_H
#define GUM_KL_H
 
#include <agrum/BN/IBayesNet.h>
 
namespace gum {

  enum class Complexity : char { Heavy, Difficult, Correct };

  template < GUM_Numeric GUM_SCALAR >
  class BNdistance {
// difficulty is chosen w.r.t the log10DomainSize of the BN
#define GAP_COMPLEXITY_KL_HEAVY_DIFFICULT   double(12.0)
#define GAP_COMPLEXITY_KL_DIFFICULT_CORRECT double(7.0)
 
    public:
    BNdistance(const IBayesNet< GUM_SCALAR >& P, const IBayesNet< GUM_SCALAR >& Q);

    BNdistance(const BNdistance< GUM_SCALAR >& kl);

    virtual ~BNdistance();

    Complexity difficulty() const;


    double klPQ();

    Size errorPQ();

    double klQP();

    Size errorQP();

    double hellinger();

    double bhattacharya();

    double jsd();

    const IBayesNet< GUM_SCALAR >& p() const;

    const IBayesNet< GUM_SCALAR >& q() const;
 
    protected:
    // should be pure virtual but using BNdistance directly is a way to delay the
    // choice between different computation scheme (@see ExactBNdistance)
    virtual void computeKL_();
 
    void process_();
 
    const IBayesNet< GUM_SCALAR >& p_;
    const IBayesNet< GUM_SCALAR >& q_;
 
    GUM_SCALAR klPQ_;
    GUM_SCALAR klQP_;
 
    Size errorPQ_;
    Size errorQP_;
 
    GUM_SCALAR hellinger_;
    GUM_SCALAR bhattacharya_;
    GUM_SCALAR jsd_;
 
    private:
    bool       _checkCompatibility_() const;
    Complexity _difficulty_;
    bool       _done_;
  };
 
 
#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
 
  extern template class BNdistance< double >;
 
#endif
 
}   // namespace gum
 
#include <agrum/BN/algorithms/divergence/BNdistance_tpl.h>
 
#endif   // GUM_KL_H