DBRowGeneratorWithBN.h

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/***************************************************************************
 *   Copyright (C) 2005 by Christophe GONZALES and Pierre-Henri WUILLEMIN  *
 *   {prenom.nom}_at_lip6.fr                                               *
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *                                                                         *
 *   This program is distributed in the hope that it will be useful,       *
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of        *
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the         *
 *   GNU General Public License for more details.                          *
 *                                                                         *
 *   You should have received a copy of the GNU General Public License     *
 *   along with this program; if not, write to the                         *
 *   Free Software Foundation, Inc.,                                       *
 *   59 Temple Place - Suite 330, Boston, MA  02111-1307, USA.             *
 ***************************************************************************/
#ifndef GUM_LEARNING_DBROW_GENERATOR_WITH_BN_H
#define GUM_LEARNING_DBROW_GENERATOR_WITH_BN_H

#include <vector>

#include <agrum/agrum.h>
#include <agrum/core/bijection.h>
#include <agrum/BN/BayesNet.h>
#include <agrum/BN/inference/variableElimination.h>
#include <agrum/learning/database/DBRowGenerator.h>

namespace gum {

  namespace learning {

    template < typename GUM_SCALAR = double,
               template < typename > class ALLOC = std::allocator >
    class DBRowGeneratorWithBN : public DBRowGenerator< ALLOC > {
      public:
      using allocator_type = ALLOC< DBTranslatedValue >;

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


      DBRowGeneratorWithBN(
         const std::vector< DBTranslatedValueType, ALLOC< DBTranslatedValueType > >
                                       column_types,
         const BayesNet< GUM_SCALAR >& bn,
         const DBRowGeneratorGoal      goal,
         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());

      DBRowGeneratorWithBN(const DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >& from);

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

      DBRowGeneratorWithBN(DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >&& from);

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

      ~DBRowGeneratorWithBN();



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


      virtual void setBayesNet(const BayesNet< GUM_SCALAR >& new_bn);

      const BayesNet< GUM_SCALAR >& getBayesNet() const;

      allocator_type getAllocator() const;



      protected:
      const BayesNet< GUM_SCALAR >* _bn;

      Bijection< NodeId, std::size_t, ALLOC< std::size_t > > _nodeId2columns;


      DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >&
         operator=(const DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >& from);

      DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >&
         operator=(DBRowGeneratorWithBN< GUM_SCALAR, ALLOC >&& from);
    };

  } /* namespace learning */

} /* namespace gum */


// always include the template implementation
#include <agrum/learning/database/DBRowGeneratorWithBN_tpl.h>

#endif /* GUM_LEARNING_DBROW_GENERATOR_WITH_BN_H */