smoothingPrior_inl.h

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 *       - Christophe GONZALES(_at_AMU)                                     *
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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
    SmoothingPrior::SmoothingPrior(const DatabaseTable&                    database,
                                   const Bijection< NodeId, std::size_t >& nodeId2columns) :
        Prior(database, nodeId2columns) {
      GUM_CONSTRUCTOR(SmoothingPrior);
    }

    INLINE SmoothingPrior::SmoothingPrior(const SmoothingPrior& from) : Prior(from) {
      GUM_CONS_CPY(SmoothingPrior);
    }

    INLINE SmoothingPrior::SmoothingPrior(SmoothingPrior&& from) noexcept : Prior(std::move(from)) {
      GUM_CONS_MOV(SmoothingPrior);
    }

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

    INLINE SmoothingPrior::~SmoothingPrior() { GUM_DESTRUCTOR(SmoothingPrior); }

    INLINE SmoothingPrior& SmoothingPrior::operator=(const SmoothingPrior& from) {
      Prior::operator=(from);
      return *this;
    }

    INLINE SmoothingPrior& SmoothingPrior::operator=(SmoothingPrior&& from) {
      Prior::operator=(std::move(from));
      return *this;
    }

    INLINE PriorType SmoothingPrior::getType() const { return PriorType::SmoothingPriorType; }

    INLINE bool SmoothingPrior::isInformative() const { return this->weight_ != 0.0; }

    INLINE void SmoothingPrior::addJointPseudoCount(const IdCondSet&       idset,
                                                    std::vector< double >& counts) {
      // if the idset is empty or the weight is zero, the prior is also empty
      if (idset.empty() || (this->weight_ == 0.0)) return;
 
      // otherwise, add the weight to all the cells in the counting vector
      for (auto& count: counts)
        count += this->weight_;
    }
 
  } /* namespace learning */
 
} /* namespace gum */
 
#endif /* DOXYGEN_SHOULD_SKIP_THIS */