BNDatabaseGenerator.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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#ifndef GUM_BN_DATABASE_GENERATOR_H
#define GUM_BN_DATABASE_GENERATOR_H
 
#include <filesystem>
#include <fstream>
 
#include <agrum/base/core/progressNotification.h>
#include <agrum/base/database/databaseTable.h>
#include <agrum/BN/BayesNet.h>
 
#include <string_view>
 
namespace gum {
 
  namespace learning {
    template < GUM_Numeric GUM_SCALAR >
    class BNDatabaseGenerator: public ProgressNotifier {
      public:
      enum class DiscretizedLabelMode : char { INTERVAL, MEDIAN, RANDOM };
 
      // #######################################################################
      // #######################################################################

      explicit BNDatabaseGenerator(const BayesNet< GUM_SCALAR >& bn);

      ~BNDatabaseGenerator();

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

      double drawSamples(Size nbSamples);

      double drawSamples(Size nbSamples, const gum::Instantiation& evs, int timeout = 300);

      void setDiscretizedLabelModeRandom();

      void setDiscretizedLabelModeMedian();

      void setDiscretizedLabelModeInterval();

      void toCSV(std::string_view csvFileURL,
                 bool             useLabels     = true,
                 bool             append        = false,
                 std::string      csvSeparator  = ",",
                 bool             checkOnAppend = false) const;

      DatabaseTable toDatabaseTable(bool useLabels = true) const;

      std::vector< std::vector< Idx > > database() const;
 
      Size samplesNbRows() const;
      Size samplesNbCols() const;
 
      Idx         samplesAt(Idx row, Idx col) const;
      std::string samplesLabelAt(Idx row, Idx col) const;

      void setVarOrder(const std::vector< Idx >& varOrder);

      void setVarOrder(const std::vector< std::string >& varOrder);

      void setVarOrderFromCSV(std::string_view csvFileURL, std::string_view csvSeparator = ",");

      void setTopologicalVarOrder();

      void setAntiTopologicalVarOrder();

      void setRandomVarOrder();

      std::vector< Idx > varOrder() const;

      std::vector< std::string > varOrderNames() const;

      double log2likelihood() const;

      const BayesNet< GUM_SCALAR >& bn(void);

 
      private:
      DiscretizedLabelMode _discretizedLabelMode_;
      const BayesNet< GUM_SCALAR >& _bn_;

      Bijection< std::string, NodeId > _names2ids_;

      Size _nbVars_;

      std::vector< std::vector< Idx > > _database_;

      std::vector< Idx > _varOrder_;

      bool _drawnSamples_ = false;

      double _log2likelihood_ = 0;

      std::string _label_(const std::vector< Idx >& row, const DiscreteVariable& v, Idx i) const;

      std::vector< Idx > _varOrderFromCSV_(std::string_view csvFileURL,
                                           std::string_view csvSeparator = ",") const;

      std::vector< Idx > _varOrderFromCSV_(std::ifstream&   csvFile,
                                           std::string_view csvSeparator = ",") const;
 
      // forbidden copies / moves
      BNDatabaseGenerator(const BNDatabaseGenerator&)            = delete;
      BNDatabaseGenerator(BNDatabaseGenerator&&)                 = delete;
      BNDatabaseGenerator& operator=(const BNDatabaseGenerator&) = delete;
      BNDatabaseGenerator& operator=(BNDatabaseGenerator&&)      = delete;
    };
 
 
#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
    extern template class BNDatabaseGenerator< double >;
#endif
 
  } /* namespace learning */
} /* namespace gum */
 
#include <agrum/BN/database/BNDatabaseGenerator_tpl.h>
#endif /* BN_DATABASE_GENERTOR */