aGrUM  0.13.2
loopySamplingInference_tpl.h
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31 
32 #define DEFAULT_VIRTUAL_LBP_SIZE 5000
33 
34 namespace gum {
35 
36 
37  template < typename GUM_SCALAR, template < typename > class APPROX >
39  const IBayesNet< GUM_SCALAR >* BN) :
40  APPROX< GUM_SCALAR >(BN),
41  _virtualLBPSize(DEFAULT_VIRTUAL_LBP_SIZE) {
42  GUM_CONSTRUCTOR(LoopySamplingInference);
43  }
44 
45 
46  template < typename GUM_SCALAR, template < typename > class APPROX >
48  GUM_DESTRUCTOR(LoopySamplingInference);
49  }
50 
51 
52  template < typename GUM_SCALAR, template < typename > class APPROX >
54  LoopyBeliefPropagation< GUM_SCALAR > lbp(&this->BN());
55  for (const auto x : this->hardEvidence()) {
56  lbp.addEvidence(x.first, x.second);
57  }
58  lbp.makeInference();
59 
60  if (!this->isSetEstimator) {
61  this->_setEstimatorFromLBP(&lbp, _virtualLBPSize);
62  }
63 
64  this->_loopApproxInference();
65  }
66 } // namespace gum
#define DEFAULT_VIRTUAL_LBP_SIZE
Class representing the minimal interface for Bayesian Network.
Definition: IBayesNet.h:59
gum is the global namespace for all aGrUM entities
Definition: agrum.h:25
virtual void makeInference() final
perform the heavy computations needed to compute the targets&#39; posteriors
virtual ~LoopySamplingInference()
destructor
virtual void addEvidence(NodeId id, const Idx val) final
adds a new hard evidence on node id
<agrum/BN/inference/loopyBeliefPropagation.h>
virtual void _makeInference()
makes the inference by generating samples w.r.t the mother class&#39; sampling method after initalizing e...
LoopySamplingInference(const IBayesNet< GUM_SCALAR > *bn)
Default constructor.
This file implements a Hybrid sampling class using LoopyBeliefPropagation and an approximate Inferenc...
<agrum/BN/inference/loopySamplingInference.h>