paramEstimatorML_inl.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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#pragma once
 

#ifndef DOXYGEN_SHOULD_SKIP_THIS
 
namespace gum {
 
  namespace learning {

    INLINE ParamEstimatorML::ParamEstimatorML(
        const DBRowGeneratorParser&                                 parser,
        const Prior&                                                external_prior,
        const Prior&                                                score_internal_prior,
        const std::vector< std::pair< std::size_t, std::size_t > >& ranges,
        const Bijection< NodeId, std::size_t >&                     nodeId2columns) :
        ParamEstimator(parser, external_prior, score_internal_prior, ranges, nodeId2columns) {
      GUM_CONSTRUCTOR(ParamEstimatorML);
    }

    INLINE
    ParamEstimatorML::ParamEstimatorML(const DBRowGeneratorParser&             parser,
                                       const Prior&                            external_prior,
                                       const Prior&                            score_internal_prior,
                                       const Bijection< NodeId, std::size_t >& nodeId2columns) :
        ParamEstimator(parser, external_prior, score_internal_prior, nodeId2columns) {
      GUM_CONSTRUCTOR(ParamEstimatorML);
    }

    INLINE ParamEstimatorML::ParamEstimatorML(const ParamEstimatorML& from) : ParamEstimator(from) {
      GUM_CONS_CPY(ParamEstimatorML);
    }

    INLINE ParamEstimatorML::ParamEstimatorML(ParamEstimatorML&& from) :
        ParamEstimator(std::move(from)) {
      GUM_CONS_MOV(ParamEstimatorML);
    }

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

    INLINE std::vector< double >
           ParamEstimatorML::parameters(const NodeId                 target_node,
                                     const std::vector< NodeId >& conditioning_nodes) {
      return _parametersAndLogLikelihood_(target_node, conditioning_nodes, false).first;
    }

    INLINE std::pair< std::vector< double >, double > ParamEstimatorML::parametersAndLogLikelihood(
        const NodeId                 target_node,
        const std::vector< NodeId >& conditioning_nodes) {
      return _parametersAndLogLikelihood_(target_node, conditioning_nodes, true);
    }
 
  } /* namespace learning */
 
} /* namespace gum */
 
#endif /* DOXYGEN_SHOULD_SKIP_THIS */