50#ifndef GUM_BAYES_NET_INFERENCE_H
51#define GUM_BAYES_NET_INFERENCE_H
82 template <
typename GUM_SCALAR >
83 class JointTargetedInference;
88 template <
typename GUM_SCALAR >
89 class MarginalTargetedInference;
94 template <
typename GUM_SCALAR >
95 class EvidenceInference;
160 template <
typename GUM_SCALAR >
Implementation of the non pure virtual methods of class BayesNetInference.
Class representing the minimal interface for Bayesian network with no numerical data.
friend JointTargetedInference< GUM_SCALAR >
allow JointInference to access the single targets and inference states
void _setBayesNetDuringConstruction_(const IBayesNet< GUM_SCALAR > *bn)
assigns a BN during the inference engine construction
BayesNetInference(const IBayesNet< GUM_SCALAR > *bn)
default constructor
friend MarginalTargetedInference< GUM_SCALAR >
allow JointInference to access the single targets and inference states
friend EvidenceInference< GUM_SCALAR >
allow JointInference to access the single targets and inference states
virtual const IBayesNet< GUM_SCALAR > & BN() const final
Returns a constant reference over the IBayesNet referenced by this class.
BayesNetInference()
default constructor with a null BN (useful for virtual inheritance)
virtual ~BayesNetInference()
destructor
virtual void setBN(const IBayesNet< GUM_SCALAR > *bn)
assigns a new BN to the inference engine
GraphicalModelInference(const GraphicalModel *model)
default constructor
Class representing the minimal interface for Bayesian network with no numerical data.
This file contains abstract class definitions for graphical models inference classes.
gum is the global namespace for all aGrUM entities
FindBarrenNodesType
type of algorithm to determine barren nodes