scoreLog2Likelihood.h

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#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 */