52#ifndef GUM_NET_WRITER_H
53#define GUM_NET_WRITER_H
75 template <
typename GUM_SCALAR >
134#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
Definition of abstract classes for file output manipulation of Bayesian networks.
BNWriter()
Default constructor.
Base class for discrete random variable.
Class representing the minimal interface for Bayesian network with no numerical data.
static std::string _header_(const IBayesNet< GUM_SCALAR > &bn)
NetWriter(const NetWriter &)=default
Default constructor.
NetWriter()
Default constructor.
std::string _variableCPT_(const Tensor< GUM_SCALAR > &cpt)
void _doWrite(std::ostream &output, const IBayesNet< GUM_SCALAR > &bn) final
Writes a Bayesian network in the output stream using the BN format.
~NetWriter() override
Destructor.
std::string _variableBloc_(const DiscreteVariable &var)
NetWriter(NetWriter &&) noexcept=default
Default constructor.
aGrUM's Tensor is a multi-dimensional array with tensor operators.
gum is the global namespace for all aGrUM entities