aGrUM  0.14.2
weightedSampling.h
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28 #ifndef GUM_WEIGHTED_INFERENCE_H
29 #define GUM_WEIGHTED_INFERENCE_H
30 
32 
33 namespace gum {
34 
47  template < typename GUM_SCALAR >
48  class WeightedSampling : public SamplingInference< GUM_SCALAR > {
49  public:
53  explicit WeightedSampling(const IBayesNet< GUM_SCALAR >* bn);
54 
58  ~WeightedSampling() override;
59 
60  protected:
62  Instantiation _burnIn() override;
63 
65 
76  Instantiation _draw(GUM_SCALAR* w, Instantiation prev) override;
77  };
78 
79 
80 #ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
81  extern template class WeightedSampling< double >;
82 #endif
83 } // namespace gum
84 
86 
87 #endif
WeightedSampling(const IBayesNet< GUM_SCALAR > *bn)
Default constructor.
~WeightedSampling() override
Destructor.
Implementation of Weighted Sampling for inference in Bayesian Networks.
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
This file contains general methods for simulation-oriented approximate inference. ...
Class for assigning/browsing values to tuples of discrete variables.
Definition: instantiation.h:80
Instantiation _draw(GUM_SCALAR *w, Instantiation prev) override
draws a sample according to Weighted sampling
Instantiation _burnIn() override
draws a defined number of samples without updating the estimators