estimator.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
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#ifndef GUM_ESTIMATOR_H
#define GUM_ESTIMATOR_H
 
#include <vector>
 
#include <agrum/BN/inference/loopyBeliefPropagation.h>
 
namespace gum {
 
  template < typename GUM_SCALAR >
  class Estimator {
    public:

    Estimator();

    explicit Estimator(const IBayesNet< GUM_SCALAR >* bn);
 
    /* Destructor */
    ~Estimator();


    void setFromBN(const IBayesNet< GUM_SCALAR >* bn, const NodeSet& hardEvidence);

    void setFromLBP(LoopyBeliefPropagation< GUM_SCALAR >* lbp,
                    const NodeSet&                        hardEvidence,
                    GUM_SCALAR                            virtualLBPSize);


    GUM_SCALAR confidence();


    void update(Instantiation I, GUM_SCALAR w);


    const Tensor< GUM_SCALAR >& posterior(const DiscreteVariable& var);


    void clear();
 
    private:
    HashTable< std::string, std::vector< GUM_SCALAR > > estimator_;

    GUM_SCALAR wtotal_;

    Size ntotal_;

    const IBayesNet< GUM_SCALAR >* bn_;


    GUM_SCALAR EV(std::string name, Idx val);


    GUM_SCALAR variance(std::string name, Idx val);   // variance corrigée
 
    private:

    HashTable< std::string, Tensor< GUM_SCALAR >* > _target_posteriors_;
  };
 
#ifndef GUM_NO_EXTERN_TEMPLATE_CLASS
  extern template class Estimator< double >;
#endif
 
}   // namespace gum
 
#include <agrum/BN/inference/tools/estimator_tpl.h>
#endif