BNdistance.h

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/***************************************************************************
 *   Copyright (C) 2005 by Christophe GONZALES and Pierre-Henri WUILLEMIN  *
 *   {prenom.nom}_at_lip6.fr                                               *
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 *   This program is distributed in the hope that it will be useful,       *
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         *
 *   GNU General Public License for more details.                          *
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 *   You should have received a copy of the GNU General Public License     *
 *   along with this program; if not, write to the                         *
 *   Free Software Foundation, Inc.,                                       *
 *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
 ***************************************************************************/
#ifndef GUM_KL_H
#define GUM_KL_H

#include <agrum/BN/IBayesNet.h>
#include <agrum/core/sequence.h>

namespace gum {

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

  template < typename 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;
    GUM_SCALAR _hellinger;
    GUM_SCALAR _bhattacharya;
    GUM_SCALAR _jsd;

    Size _errorPQ;
    Size _errorQP;

    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