kNML.h

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#ifndef GUM_LEARNING_K_NML_H
#define GUM_LEARNING_K_NML_H

#include <vector>

#include <agrum/core/math/math.h>
#include <agrum/core/math/variableLog2ParamComplexity.h>
#include <agrum/learning/scores_and_tests/independenceTest.h>

namespace gum {

  namespace learning {


    template < template < typename > class ALLOC = std::allocator >
    class KNML : private IndependenceTest< ALLOC > {
      public:
      using allocator_type = ALLOC< NodeId >;

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


      KNML(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());



      KNML(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());

      KNML(const KNML< ALLOC >& from);

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

      KNML(KNML< ALLOC >&& from);

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

      virtual KNML< ALLOC >* clone() const;

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

      virtual ~KNML();



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


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

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



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

      using IndependenceTest< ALLOC >::setMaxNbThreads;

      using IndependenceTest< ALLOC >::nbThreads;

      using IndependenceTest< ALLOC >::setMinNbRowsPerThread;

      using IndependenceTest< ALLOC >::minNbRowsPerThread;


      using IndependenceTest< ALLOC >::setRanges;

      using IndependenceTest< ALLOC >::clearRanges;

      using IndependenceTest< ALLOC >::ranges;

      using IndependenceTest< ALLOC >::score;

      virtual void clear();

      virtual void clearCache();

      virtual void useCache(const bool on_off);


      using IndependenceTest< ALLOC >::nodeId2Columns;

      using IndependenceTest< ALLOC >::database;

      using IndependenceTest< ALLOC >::getAllocator;



      protected:

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


#ifndef DOXYGEN_SHOULD_SKIP_THIS

      private:
      VariableLog2ParamComplexity< ALLOC > __param_complexity;

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
    };

  } /* namespace learning */

} /* namespace gum */


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

#endif /* GUM_LEARNING_K_NML_H */