BNDatabaseGenerator.h

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#ifndef GUM_BN_DATABASE_GENERATOR
#define GUM_BN_DATABASE_GENERATOR

#include <agrum/BN/BayesNet.h>
#include <agrum/core/progressNotification.h>
#include <agrum/learning/database/databaseTable.h>
#include <fstream>

namespace gum {

  namespace learning {
    template < typename GUM_SCALAR >
    class BNDatabaseGenerator : public ProgressNotifier {
      public:
      // #######################################################################
      // #######################################################################

      BNDatabaseGenerator(const BayesNet< GUM_SCALAR >& bn);

      ~BNDatabaseGenerator();


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


      double drawSamples(Size nbSamples);   // drawSamples

      void toCSV(const std::string& 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;

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

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

      void setVarOrderFromCSV(const std::string& csvFileURL,
                              const std::string& csvSeparator = ",");

      void setTopologicalVarOrder();

      void setAntiTopologicalVarOrder();

      void setRandomVarOrder();

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

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

      double log2likelihood() const;


      private:
      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::vector< Idx >
         __varOrderFromCSV(const std::string& csvFileURL,
                           const std::string& csvSeparator = ",") const;

      std::vector< Idx >
         __varOrderFromCSV(std::ifstream&     csvFile,
                           const std::string& 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/learning/database/BNDatabaseGenerator_tpl.h>
#endif /* BN_DATABASE_GENERTOR */