aGrUM 3.2.0
a C++ library for (probabilistic) graphical models
scorefNML_inl.h
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40
41#pragma once
42
43
49
50#include <agrum/BN/learning/scores/scorefNML.h> // to ease IDE parser
51#ifndef DOXYGEN_SHOULD_SKIP_THIS
52
54
55namespace gum {
56
57 namespace learning {
58
59 // Constructors and destructor are defined out-of-line in scorefNML.cpp
60 // on purpose -- see the comment there.
61
63 INLINE ScorefNML* ScorefNML::clone() const { return new ScorefNML(*this); }
64
66 INLINE std::string ScorefNML::isPriorCompatible(const Prior& prior) {
67 return isPriorCompatible(prior.getType(), prior.weight());
68 }
69
71 INLINE std::string ScorefNML::isPriorCompatible() const {
72 return isPriorCompatible(*(this->prior_));
73 }
74
76 INLINE const Prior& ScorefNML::internalPrior() const { return _internal_prior_; }
77
78
79 } /* namespace learning */
80
81} /* namespace gum */
82
83#endif /* DOXYGEN_SHOULD_SKIP_THIS */
the base class for all a priori
Definition prior.h:84
Prior * prior_
the expert knowledge a priorwe add to the score
Definition score.h:238
the class for computing fNML scores
Definition scorefNML.h:72
ScorefNML * clone() const override
virtual copy constructor
std::string isPriorCompatible() const final
indicates whether the prior is compatible (meaningful) with the score
const Prior & internalPrior() const final
returns the internal prior of the score
ScorefNML(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
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 fNML scores