paramEstimatorML.h

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#ifndef GUM_LEARNING_PARAM_ESTIMATOR_ML_H
#define GUM_LEARNING_PARAM_ESTIMATOR_ML_H

#include <sstream>

#include <agrum/agrum.h>
#include <agrum/learning/paramUtils/paramEstimator.h>

namespace gum {

  namespace learning {

    template < template < typename > class ALLOC = std::allocator >
    class ParamEstimatorML : public ParamEstimator< ALLOC > {
      public:
      using allocator_type = ALLOC< NodeId >;

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


      ParamEstimatorML(
         const DBRowGeneratorParser< ALLOC >& parser,
         const Apriori< ALLOC >&              external_apriori,
         const Apriori< ALLOC >&              score_internal__apriori,
         const std::vector< std::pair< std::size_t, std::size_t >,
                            ALLOC< std::pair< std::size_t, std::size_t > > >&
            ranges,
         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());


      ParamEstimatorML(
         const DBRowGeneratorParser< ALLOC >& parser,
         const Apriori< ALLOC >&              external_apriori,
         const Apriori< ALLOC >&              score_internal__apriori,
         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());

      ParamEstimatorML(const ParamEstimatorML< ALLOC >& from);

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

      ParamEstimatorML(ParamEstimatorML< ALLOC >&& from);

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

      virtual ParamEstimatorML< ALLOC >* clone() const;

      virtual ParamEstimatorML< ALLOC >* clone(const allocator_type& alloc) const;

      virtual ~ParamEstimatorML();



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


      ParamEstimatorML< ALLOC >& operator=(const ParamEstimatorML< ALLOC >& from);

      ParamEstimatorML< ALLOC >& operator=(ParamEstimatorML< ALLOC >&& from);



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

      using ParamEstimator< ALLOC >::parameters;


      virtual std::vector< double, ALLOC< double > > parameters(
         const NodeId                                  target_node,
         const std::vector< NodeId, ALLOC< NodeId > >& conditioning_nodes);

    };

  } /* namespace learning */

} /* namespace gum */

#include <agrum/learning/paramUtils/paramEstimatorML_tpl.h>

#endif /* GUM_LEARNING_PARAM_ESTIMATOR_ML_H */