correctedMutualInformation_inl.h

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/****************************************************************************
 *   This file is part of the aGrUM/pyAgrum library.                        *
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 *   Copyright (c) 2005-2026 by                                             *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
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 *   SPDX-FileCopyrightText: Copyright 2005-2026                            *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
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#pragma once
 

#include <agrum/BN/learning/correctedMutualInformation.h>   // to ease IDE parser
#ifndef DOXYGEN_SHOULD_SKIP_THIS
 
namespace gum {
 
  namespace learning {

    INLINE void CorrectedMutualInformation::useCache(bool on_off) {
      useICache(on_off);
      useHCache(on_off);
      useKCache(on_off);
      useCnrCache(on_off);
    }

    INLINE void CorrectedMutualInformation::useICache(bool on_off) {
      if (!on_off) _ICache_.clear();
      _use_ICache_ = on_off;
    }

    INLINE void CorrectedMutualInformation::useHCache(bool on_off) {
      if (!on_off) _NH_.clearCache();
      _use_HCache_ = on_off;
      _NH_.useCache(on_off);
    }

    INLINE void CorrectedMutualInformation::useKCache(bool on_off) {
      if (!on_off) _KCache_.clear();
      _use_KCache_ = on_off;
    }

    INLINE void CorrectedMutualInformation::useCnrCache(bool on_off) {
      if (!on_off) _k_NML_.clearCache();
      _use_CnrCache_ = on_off;
      _k_NML_.useCache(on_off);
    }

    INLINE void CorrectedMutualInformation::clear() {
      _NH_.clear();
      _k_NML_.clear();
      _score_MDL_.clear();
      clearCache();
    }

    INLINE void CorrectedMutualInformation::clearCache() {
      _NH_.clearCache();
      _k_NML_.clearCache();
      _ICache_.clear();
      _KCache_.clear();
    }

    INLINE void CorrectedMutualInformation::clearICache() { _ICache_.clear(); }

    INLINE void CorrectedMutualInformation::clearHCache() { _NH_.clearCache(); }

    INLINE void CorrectedMutualInformation::clearKCache() { _KCache_.clear(); }

    INLINE void CorrectedMutualInformation::clearCnrCache() { _k_NML_.clearCache(); }

    INLINE void CorrectedMutualInformation::setNumberOfThreads(Size nb) {
      _NH_.setNumberOfThreads(nb);
      _k_NML_.setNumberOfThreads(nb);
      _score_MDL_.setNumberOfThreads(nb);
    }

    INLINE Size CorrectedMutualInformation::getNumberOfThreads() const {
      return _NH_.getNumberOfThreads();
    }

    INLINE bool CorrectedMutualInformation::isGumNumberOfThreadsOverriden() const {
      return _NH_.isGumNumberOfThreadsOverriden();
    }

    INLINE void CorrectedMutualInformation::setMinNbRowsPerThread(const std::size_t nb) const {
      _NH_.setMinNbRowsPerThread(nb);
      _k_NML_.setMinNbRowsPerThread(nb);
      _score_MDL_.setMinNbRowsPerThread(nb);
    }

    INLINE std::size_t CorrectedMutualInformation::minNbRowsPerThread() const {
      return _NH_.minNbRowsPerThread();
    }

    INLINE const std::vector< std::pair< std::size_t, std::size_t > >&
                 CorrectedMutualInformation::ranges() const {
      return _NH_.ranges();
    }

    INLINE void CorrectedMutualInformation::useMDL() {
      clearCache();
      _kmode_ = KModeTypes::MDL;
    }

    INLINE void CorrectedMutualInformation::useNML() {
      clearCache();
      _kmode_ = KModeTypes::NML;
    }

    INLINE void CorrectedMutualInformation::useNoCorr() {
      clearCache();
      _kmode_ = KModeTypes::NoCorr;
    }

    INLINE double CorrectedMutualInformation::score(NodeId var1, NodeId var2) {
      return score(var1, var2, _empty_conditioning_set_);
    }

    INLINE double CorrectedMutualInformation::score(NodeId                       var1,
                                                    NodeId                       var2,
                                                    const std::vector< NodeId >& conditioning_ids) {
      return _NI_score_(var1, var2, conditioning_ids) - _K_score_(var1, var2, conditioning_ids);
    }

    INLINE double CorrectedMutualInformation::score(NodeId var1, NodeId var2, NodeId var3) {
      return score(var1, var2, var3, _empty_conditioning_set_);
    }

    INLINE double CorrectedMutualInformation::score(NodeId                       var1,
                                                    NodeId                       var2,
                                                    NodeId                       var3,
                                                    const std::vector< NodeId >& conditioning_ids) {
      return _NI_score_(var1, var2, var3, conditioning_ids)
           + _K_score_(var1, var2, var3, conditioning_ids);
    }

    INLINE double CorrectedMutualInformation::_NI_score_(NodeId                       var_x,
                                                         NodeId                       var_y,
                                                         NodeId                       var_z,
                                                         const std::vector< NodeId >& ui_ids) {
      // conditional 3-point mutual information formula:
      // I(x;y;z|{ui}) = I(x;y|{ui}) - I(x;y|z,{ui})
      std::vector< NodeId > uiz_ids = ui_ids;
      uiz_ids.push_back(var_z);
      return _NI_score_(var_x, var_y, ui_ids) - _NI_score_(var_x, var_y, uiz_ids);
    }

    INLINE double CorrectedMutualInformation::_K_score_(NodeId                       var1,
                                                        NodeId                       var2,
                                                        NodeId                       var3,
                                                        const std::vector< NodeId >& ui_ids) {
      // k(x;y;z|ui) = k(x;y|ui,z) - k(x;y|ui)
      std::vector< NodeId > uiz_ids = ui_ids;
      uiz_ids.push_back(var3);
      return _K_score_(var1, var2, uiz_ids) - _K_score_(var1, var2, ui_ids);
    }
 
 
  } /* namespace learning */
 
} /* namespace gum */
 
#endif /* DOXYGEN_SHOULD_SKIP_THIS */