aGrUM 2.3.2
a C++ library for (probabilistic) graphical models
BIFWriter.h
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41
51
52#ifndef GUM_BIF_WRITER_H
53#define GUM_BIF_WRITER_H
54
55#include <fstream>
56#include <iostream>
57#include <sstream>
58#include <string>
59
60#include <agrum/agrum.h>
61
63
64namespace gum {
65
78 template < typename GUM_SCALAR >
79 class BIFWriter final: public BNWriter< GUM_SCALAR > {
80 public:
81 // ==========================================================================
83 // ==========================================================================
85
90
94 ~BIFWriter() override;
95
96 BIFWriter(const BIFWriter&) = default;
97 BIFWriter(BIFWriter&&) noexcept = default;
98 BIFWriter& operator=(const BIFWriter&) = default;
99 BIFWriter& operator=(BIFWriter&&) noexcept = default;
100
102
103 protected:
111 void _doWrite(std::ostream& output, const IBayesNet< GUM_SCALAR >& bn) final;
112
121 void _doWrite(const std::string& filePath, const IBayesNet< GUM_SCALAR >& bn) final;
122
128 void _syntacticalCheck(const IBayesNet< GUM_SCALAR >& bn) final;
129
130 private:
131 // Returns the header of the BIF file.
132 std::string _header_(const IBayesNet< GUM_SCALAR >& bn);
133
134 // Returns a bloc defining a variable in the BIF format.
136
137 // Returns a bloc defining a variable's CPT in the BIF format.
138 std::string _variableCPT_(const Tensor< GUM_SCALAR >& cpt);
139
140 // Returns the modalities labels of the variables in varsSeq
141 std::string _variablesLabels_(const Sequence< const DiscreteVariable* >& varsSeq,
142 const Instantiation& inst);
143 };
144
145
146#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
147 extern template class BIFWriter< double >;
148#endif
149
150} /* namespace gum */
151
153#endif // GUM_BIF_WRITER_H
Definition of abstract classes for file output manipulation of Bayesian networks.
std::string _variablesLabels_(const Sequence< const DiscreteVariable * > &varsSeq, const Instantiation &inst)
BIFWriter()
Default constructor.
BIFWriter(BIFWriter &&) noexcept=default
Default constructor.
std::string _variableCPT_(const Tensor< GUM_SCALAR > &cpt)
std::string _variableBloc_(const DiscreteVariable &var)
BIFWriter(const BIFWriter &)=default
Default constructor.
void _syntacticalCheck(const IBayesNet< GUM_SCALAR > &bn) final
Check whether the BN is syntactically correct for BIF format.
~BIFWriter() override
Destructor.
void _doWrite(std::ostream &output, const IBayesNet< GUM_SCALAR > &bn) final
Writes a Bayesian network in the output stream using the BIF format.
std::string _header_(const IBayesNet< GUM_SCALAR > &bn)
BNWriter()
Default constructor.
Base class for discrete random variable.
Class representing the minimal interface for Bayesian network with no numerical data.
Definition IBayesNet.h:75
Class for assigning/browsing values to tuples of discrete variables.
The generic class for storing (ordered) sequences of objects.
Definition sequence.h:972
aGrUM's Tensor is a multi-dimensional array with tensor operators.
Definition tensor.h:85
gum is the global namespace for all aGrUM entities
Definition agrum.h:46
STL namespace.