aGrUM 3.2.0
a C++ library for (probabilistic) graphical models
scoreLog2Likelihood_inl.h
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40
41#pragma once
42
43
49
50#include <agrum/BN/learning/scores/scoreLog2Likelihood.h> // to ease IDE parser
51#ifndef DOXYGEN_SHOULD_SKIP_THIS
52
53# include <sstream>
54
56
57namespace gum {
58
59 namespace learning {
60
61 // Constructors and destructor are defined out-of-line in
62 // scoreLog2Likelihood.cpp on purpose -- see the comment there.
63
66 return new ScoreLog2Likelihood(*this);
67 }
68
70 INLINE std::string ScoreLog2Likelihood::isPriorCompatible(const Prior& prior) {
71 return isPriorCompatible(prior.getType(), prior.weight());
72 }
73
75 INLINE std::string ScoreLog2Likelihood::isPriorCompatible() const {
76 return isPriorCompatible(*(this->prior_));
77 }
78
80 INLINE const Prior& ScoreLog2Likelihood::internalPrior() const { return _internal_prior_; }
81
83 INLINE double ScoreLog2Likelihood::score(const IdCondSet& idset) { return score_(idset); }
84
85
86 } /* namespace learning */
87
88} /* namespace gum */
89
90#endif /* DOXYGEN_SHOULD_SKIP_THIS */
A class for storing a pair of sets of NodeIds, the second one corresponding to a conditional set.
Definition idCondSet.h:214
the base class for all a priori
Definition prior.h:84
the class for computing Log2-likelihood scores
std::string isPriorCompatible() const final
indicates whether the prior is compatible (meaningful) with the score
double score_(const IdCondSet &idset) final
returns the score for a given IdCondSet
ScoreLog2Likelihood(const DBRowGeneratorParser &parser, const Prior &prior, const std::vector< std::pair< std::size_t, std::size_t > > &ranges, const Bijection< NodeId, std::size_t > &nodeId2columns=Bijection< NodeId, std::size_t >())
default constructor
double score(const IdCondSet &idset)
returns the score for a given IdCondSet
const Prior & internalPrior() const final
returns the internal prior of the score
ScoreLog2Likelihood * clone() const override
virtual copy constructor
Prior * prior_
the expert knowledge a priorwe add to the score
Definition score.h:238
include the inlined functions if necessary
Definition CSVParser.h:55
gum is the global namespace for all aGrUM entities
Definition agrum.h:46
the class for computing Log2-likelihood scores