correctedMutualInformation.h

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#ifndef GUM_LEARNING_CORRECTED_MUTUAL_INFORMATION_H
#define GUM_LEARNING_CORRECTED_MUTUAL_INFORMATION_H

#include <agrum/config.h>
#include <agrum/core/math/math.h>
#include <vector>

#include <agrum/learning/scores_and_tests/kNML.h>
#include <agrum/learning/scores_and_tests/scoreLog2Likelihood.h>
#include <agrum/learning/scores_and_tests/scoreMDL.h>

namespace gum {

  namespace learning {

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

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


      CorrectedMutualInformation(
         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());


      CorrectedMutualInformation(
         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());

      CorrectedMutualInformation(const CorrectedMutualInformation< ALLOC >& from);

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

      CorrectedMutualInformation(CorrectedMutualInformation< ALLOC >&& from);

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

      virtual CorrectedMutualInformation< ALLOC >* clone() const;

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

      virtual ~CorrectedMutualInformation();



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


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

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



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

      virtual void clear();


      virtual void clearCache();


      virtual void useCache(bool on_off);

      void useICache(bool on_off);

      void clearICache();

      void useHCache(bool on_off);

      void clearHCache();

      void useKCache(bool on_off);

      void clearKCache();

      void useCnrCache(bool on_off);

      void clearCnrCache();



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

      double score(NodeId var1, NodeId var2);

      double score(NodeId                                        var1,
                   NodeId                                        var2,
                   const std::vector< NodeId, ALLOC< NodeId > >& conditioning_ids);

      double score(NodeId var1, NodeId var2, NodeId var3);

      double score(NodeId                                        var1,
                   NodeId                                        var2,
                   NodeId                                        var3,
                   const std::vector< NodeId, ALLOC< NodeId > >& conditioning_ids);



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

      void useMDL();

      void useNML();

      void useNoCorr();

      virtual void setMaxNbThreads(std::size_t nb) const;

      virtual std::size_t nbThreads() const;

      virtual void setMinNbRowsPerThread(const std::size_t nb) const;

      virtual std::size_t minNbRowsPerThread() const;


      template < template < typename > class XALLOC >
      void setRanges(
         const std::vector< std::pair< std::size_t, std::size_t >,
                            XALLOC< std::pair< std::size_t, std::size_t > > >&
            new_ranges);

      void clearRanges();

      const std::vector< std::pair< std::size_t, std::size_t >,
                         ALLOC< std::pair< std::size_t, std::size_t > > >&
         ranges() const;


      allocator_type getAllocator() const;



      enum class KModeTypes { MDL, NML, NoCorr };


#ifndef DOXYGEN_SHOULD_SKIP_THIS

      private:
      /* Note that the log2-likelihood is equal to N times the entropy H */
      ScoreLog2Likelihood< ALLOC > __NH;

      KNML< ALLOC > __k_NML;

      ScoreMDL< ALLOC > __score_MDL;

      KModeTypes __kmode{KModeTypes::MDL};



      bool __use_ICache{true};


      bool __use_HCache{true};


      bool __use_KCache{true};


      bool __use_CnrCache{true};


      ScoringCache< ALLOC > __ICache;

      ScoringCache< ALLOC > __KCache;


      const std::vector< NodeId, ALLOC< NodeId > > __empty_conditioning_set;

      const double __threshold{1e-10};


      double __NI_score(NodeId                                        var_x,
                        NodeId                                        var_y,
                        const std::vector< NodeId, ALLOC< NodeId > >& vars_z);

      double __NI_score(NodeId                                        var_x,
                        NodeId                                        var_y,
                        NodeId                                        var_z,
                        const std::vector< NodeId, ALLOC< NodeId > >& vars_ui);

      double __K_score(NodeId                                        var_x,
                       NodeId                                        var_y,
                       const std::vector< NodeId, ALLOC< NodeId > >& vars_z);

      double __K_score(NodeId                                        var_x,
                       NodeId                                        var_y,
                       NodeId                                        var_z,
                       const std::vector< NodeId, ALLOC< NodeId > >& vars_ui);

#endif /* DOXYGEN_SHOULD_SKIP_THIS */
    };

  } /* namespace learning */

} /* namespace gum */


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


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

#endif /* GUM_LEARNING_CORRECTED_MUTUAL_INFORMATION_H */