scoreLog2Likelihood.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.                          *
 *                                                                         *
 *   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_LEARNING_SCORE_LOG2_LIKELIHOOD_H
#define GUM_LEARNING_SCORE_LOG2_LIKELIHOOD_H

#include <string>

#include <agrum/agrum.h>
#include <agrum/core/math/math.h>
#include <agrum/learning/scores_and_tests/score.h>
#include <agrum/learning/aprioris/aprioriNoApriori.h>

namespace gum {

  namespace learning {

    template < template < typename > class ALLOC = std::allocator >
    class ScoreLog2Likelihood : public Score< ALLOC > {
      public:
      using allocator_type = ALLOC< NodeId >;

      // ##########################################################################
      // ##########################################################################


      ScoreLog2Likelihood(
         const DBRowGeneratorParser< ALLOC >& parser,
         const Apriori< ALLOC >&              apriori,
         const std::vector< std::pair< std::size_t, std::size_t >,
                            ALLOC< std::pair< std::size_t, std::size_t > > >&
            ranges,
         const Bijection< NodeId, std::size_t, ALLOC< std::size_t > >&
            nodeId2columns =
               Bijection< NodeId, std::size_t, ALLOC< std::size_t > >(),
         const allocator_type& alloc = allocator_type());



      ScoreLog2Likelihood(
         const DBRowGeneratorParser< ALLOC >& parser,
         const Apriori< ALLOC >&              apriori,
         const Bijection< NodeId, std::size_t, ALLOC< std::size_t > >&
            nodeId2columns =
               Bijection< NodeId, std::size_t, ALLOC< std::size_t > >(),
         const allocator_type& alloc = allocator_type());

      ScoreLog2Likelihood(const ScoreLog2Likelihood< ALLOC >& from);

      ScoreLog2Likelihood(const ScoreLog2Likelihood< ALLOC >& from,
                          const allocator_type&               alloc);

      ScoreLog2Likelihood(ScoreLog2Likelihood< ALLOC >&& from);

      ScoreLog2Likelihood(ScoreLog2Likelihood< ALLOC >&& from,
                          const allocator_type&          alloc);

      virtual ScoreLog2Likelihood< ALLOC >* clone() const;

      virtual ScoreLog2Likelihood< ALLOC >*
         clone(const allocator_type& alloc) const;

      virtual ~ScoreLog2Likelihood();



      // ##########################################################################
      // ##########################################################################


      ScoreLog2Likelihood< ALLOC >&
         operator=(const ScoreLog2Likelihood< ALLOC >& from);

      ScoreLog2Likelihood< ALLOC >& operator=(ScoreLog2Likelihood< ALLOC >&& from);



      // ##########################################################################
      // ##########################################################################


      virtual std::string isAprioriCompatible() const final;


      virtual const Apriori< ALLOC >& internalApriori() const final;

      using Score< ALLOC >::score;


      double score(const IdSet< ALLOC >& idset);




      static std::string isAprioriCompatible(const std::string& apriori_type,
                                             double             weight = 1.0f);


      static std::string isAprioriCompatible(const Apriori< ALLOC >& apriori);


      protected:

      virtual double _score(const IdSet< ALLOC >& idset) final;


#ifndef DOXYGEN_SHOULD_SKIP_THIS

      private:
      AprioriNoApriori< ALLOC > __internal_apriori;

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
    };

  } /* namespace learning */

} /* namespace gum */


#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
extern template class gum::learning::ScoreLog2Likelihood<>;
#endif


// always include the template implementation
#include <agrum/learning/scores_and_tests/scoreLog2Likelihood_tpl.h>

#endif /* GUM_LEARNING_SCORE_LOG2_LIKELIHOOD_H */