DAG2BNLearner.cpp

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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#include <agrum/BN/learning/paramUtils/DAG2BNLearner.h>
 
#ifndef DOXYGEN_SHOULD_SKIP_THIS

#  ifdef GUM_NO_INLINE
#    include <agrum/BN/learning/paramUtils/DAG2BNLearner_inl.h>
#  endif /* GUM_NO_INLINE */
 
namespace gum {
 
  namespace learning {

    DAG2BNLearner::DAG2BNLearner() : EMApproximationScheme() { GUM_CONSTRUCTOR(DAG2BNLearner); }

    DAG2BNLearner::DAG2BNLearner(const DAG2BNLearner& from) :
        EMApproximationScheme(from), noiseEM_(from.noiseEM_),
        max_nb_dec_likelihood_iter_(from.max_nb_dec_likelihood_iter_) {
      GUM_CONS_CPY(DAG2BNLearner);
    }

    DAG2BNLearner::DAG2BNLearner(DAG2BNLearner&& from) :
        EMApproximationScheme(std::move(from)), noiseEM_(from.noiseEM_),
        max_nb_dec_likelihood_iter_(from.max_nb_dec_likelihood_iter_) {
      GUM_CONS_MOV(DAG2BNLearner);
    }

    DAG2BNLearner* DAG2BNLearner::clone() const { return new DAG2BNLearner(*this); }

    DAG2BNLearner::~DAG2BNLearner() { GUM_DESTRUCTOR(DAG2BNLearner); }

    DAG2BNLearner& DAG2BNLearner::operator=(const DAG2BNLearner& from) {
      EMApproximationScheme::operator=(from);
      noiseEM_ = from.noiseEM_;
      return *this;
    }

    DAG2BNLearner& DAG2BNLearner::operator=(DAG2BNLearner&& from) {
      EMApproximationScheme::operator=(std::move(from));
      noiseEM_ = from.noiseEM_;
      return *this;
    }
 
 
  } /* namespace learning */
 
} /* namespace gum */
 
#endif /* DOXYGEN_SHOULD_SKIP_THIS */