ConstraintBasedLearning.h

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#ifndef GUM_CONSTRAINT_BASED_LEARNING_H
#define GUM_CONSTRAINT_BASED_LEARNING_H
 
#include <limits>
#include <sstream>
#include <string>
#include <vector>
 
#include <agrum/config.h>
 
#include <agrum/base/core/approximations/approximationScheme.h>
#include <agrum/base/graphs/algorithms/MeekRules.h>
 
#define GUM_SL_EMIT(x, y, action, explain)                                                \
  {                                                                                       \
    std::ostringstream action_stream;                                                     \
    action_stream << action;                                                              \
    std::ostringstream explain_stream;                                                    \
    explain_stream << explain;                                                            \
    GUM_EMIT4(onStructuralModification, x, y, action_stream.str(), explain_stream.str()); \
  }
 
namespace gum {
 
  namespace learning {
 
    using ThreePoints = std::tuple< NodeId, NodeId, NodeId >;

    class ConstraintBasedLearning: public ApproximationScheme {
      public:
      // ##########################################################################
      // ##########################################################################
 
      ConstraintBasedLearning();
      explicit ConstraintBasedLearning(int maxLog);
      ConstraintBasedLearning(const ConstraintBasedLearning&);
      ConstraintBasedLearning(ConstraintBasedLearning&&);
      ~ConstraintBasedLearning() override;

 
      ConstraintBasedLearning& operator=(const ConstraintBasedLearning&);
      ConstraintBasedLearning& operator=(ConstraintBasedLearning&&);
 
      // ##########################################################################
      // ##########################################################################
 
      void setForbiddenGraph(const gum::DiGraph& forbidGraph);
      void setMandatoryGraph(const gum::DAG& mandaGraph);
      void setMaxIndegree(gum::Size n);
      void addConstraints(const HashTable< std::pair< NodeId, NodeId >, char >& constraints);
      const std::vector< Arc > latentVariables() const;

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

      PDAG learnPDAG(MixedGraph graph);

      DAG learnDAG(MixedGraph graph);

      template < GUM_Numeric GUM_SCALAR = double, typename PARAM_ESTIMATOR >
      BayesNet< GUM_SCALAR > learnBN(PARAM_ESTIMATOR& estimator, MixedGraph graph);

 
      Signaler< gum::NodeId, gum::NodeId, std::string, std::string > onStructuralModification;
 
      protected:
      // ##########################################################################
      // ##########################################################################
 
      virtual MixedGraph learnSkeleton(MixedGraph graph) = 0;
 
      virtual MixedGraph learnMixedStructure(MixedGraph graph) = 0;

 
      // ##########################################################################
      // ##########################################################################
 
      static bool _existsDirectedPath_(const MixedGraph& graph, NodeId n1, NodeId n2);
      static bool _existsNonTrivialDirectedPath_(const MixedGraph& graph, NodeId n1, NodeId n2);
      void        orientDoubleHeadedArcs_(MixedGraph& mg);
      std::vector< ThreePoints > unshieldedTriples_(const MixedGraph& graph);
 
      void applyStructuralConstraints_(MixedGraph& graph);

      MixedGraph initGraph_(const MixedGraph& template_graph);
 
      gum::MeekRules meekRules_;

 
      // ##########################################################################
      // ##########################################################################
 
      bool isForbiddenArc_(NodeId x, NodeId y) const;
      bool isForbiddenEdge_(NodeId x, NodeId y) const;
      bool isMaxIndegree_(const MixedGraph& graph, NodeId x);
      bool isArcValid_(const MixedGraph& graph, NodeId x, NodeId y);

 
      // ##########################################################################
      // ##########################################################################
 
      gum::DiGraph                                   _forbiddenGraph_;
      gum::DAG                                       _mandatoryGraph_;
      HashTable< std::pair< NodeId, NodeId >, char > _initialMarks_;
      std::vector< Arc >                             _latentCouples_;
      int                                            _maxLog_{100};
      const std::vector< NodeId >                    _emptySet_;
 
      private:
      gum::Size _maxIndegree_{std::numeric_limits< gum::Size >::max()};
    };
 
  } /* namespace learning */
 
} /* namespace gum */
 
#include <agrum/BN/learning/ConstraintBasedLearning_tpl.h>
 
#endif /* GUM_CONSTRAINT_BASED_LEARNING_H */