GibbsBNdistance.h

Go to the documentation of this file.

/***************************************************************************
 *   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.                          *
 *                                                                         *
 *   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_GIBBS_KL2_H
#define GUM_GIBBS_KL2_H

#include <agrum/BN/algorithms/divergence/BNdistance.h>
#include <agrum/BN/inference/tools/gibbsOperator.h>
#include <agrum/core/approximations/approximationScheme.h>

#include <agrum/core/signal/signaler.h>

namespace gum {

  template < typename GUM_SCALAR >
  class GibbsBNdistance
      : public BNdistance< GUM_SCALAR >
      , public ApproximationScheme
      , public GibbsOperator< GUM_SCALAR > {
    public:
    /* no default constructor */

    GibbsBNdistance(const IBayesNet< GUM_SCALAR >& P,
                    const IBayesNet< GUM_SCALAR >& Q);

    explicit GibbsBNdistance(const BNdistance< GUM_SCALAR >& kl);

    ~GibbsBNdistance();

    void setBurnIn(Size b);

    Size burnIn() const;

    protected:
    void _computeKL() final;

    using BNdistance< GUM_SCALAR >::_p;
    using BNdistance< GUM_SCALAR >::_q;
    using BNdistance< GUM_SCALAR >::_hellinger;
    using BNdistance< GUM_SCALAR >::_bhattacharya;
    using BNdistance< GUM_SCALAR >::_jsd;

    using BNdistance< GUM_SCALAR >::_klPQ;
    using BNdistance< GUM_SCALAR >::_klQP;

    using BNdistance< GUM_SCALAR >::_errorPQ;
    using BNdistance< GUM_SCALAR >::_errorQP;
  };


#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
  extern template class GibbsBNdistance< double >;
#endif

}   // namespace gum

#include <agrum/BN/algorithms/divergence/GibbsKL_tpl.h>

#endif