32 # define MCBG MCBayesNetGenerator 34 # define MCBG MCBayesNetGenerator< GUM_SCALAR, ICPTGenerator, ICPTDisturber > 39 template <
typename GUM_SCALAR,
53 MCBG(nbrNodes, maxArcs, maxModality, iteration, p, q) {
56 "maxParents must be at least equal to 1 to have a connexe graph");
62 template <
typename GUM_SCALAR,
74 MCBG(bayesNet, iteration, p, q) {
80 template <
typename GUM_SCALAR,
91 template <
typename GUM_SCALAR,
101 return MCBG::__checkConditions();
104 template <
typename GUM_SCALAR,
108 class ICPTDisturber >
114 template <
typename GUM_SCALAR,
118 class ICPTDisturber >
124 "maxParents must be at least equal to 1 to have a connexe graph");
Class representing a Bayesian Network.
<agrum/BN/generator/SimpleMCayesNetGenerator.h>
Idx q() const
Return a constant reference to the probabilité imposed on the Markov Chain BayesNetGenerator.
void setMaxParents(Size maxParents)
Modifies the value of the number of maximum parents imposed on the BayesNetGenerator.
gum is the global namespace for all aGrUM entities
BayesNet< GUM_SCALAR > _bayesNet
bool __checkConditions() final
function to holding the the specification wanted for the Bayesian markov.
~MaxParentsMCBayesNetGenerator() final
Destructor.
MaxParentsMCBayesNetGenerator(Size nbrNodes, Size maxArcs, Size maxModality=2, Size maxParents=1, Idx iteration=5000, Idx p=30, Idx q=40)
Constructor.
Size maxParents() const
Return a constant reference to the number of maximum parents imposed on the Markov Chain BayesNetGene...
Size Idx
Type for indexes.
Size iteration() const
Return a constant reference to the number of iteration imposed on the Markov Chain BayesNetGenerator...
std::size_t Size
In aGrUM, hashed values are unsigned long int.
Class for generating bayesian networks using MC algorithm cf.
Idx p() const
Return a constant reference to the probabilité p imposed on the Markov Chain BayesNetGenerator.
#define GUM_ERROR(type, msg)