exactBNdistance_tpl.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
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#pragma once
 

 
#include <agrum/BN/algorithms/divergence/BNdistance.h>
#include <agrum/BN/algorithms/divergence/exactBNdistance.h>
#include <agrum/BN/IBayesNet.h>
 
#include <agrum/base/core/math/math_utils.h>
 
namespace gum {
  template < typename GUM_SCALAR >
  ExactBNdistance< GUM_SCALAR >::ExactBNdistance(const IBayesNet< GUM_SCALAR >& P,
                                                 const IBayesNet< GUM_SCALAR >& Q) :
      BNdistance< GUM_SCALAR >(P, Q) {
    GUM_CONSTRUCTOR(ExactBNdistance);
  }
 
  template < typename GUM_SCALAR >
  ExactBNdistance< GUM_SCALAR >::ExactBNdistance(const BNdistance< GUM_SCALAR >& kl) :
      BNdistance< GUM_SCALAR >(kl) {
    GUM_CONSTRUCTOR(ExactBNdistance);
  }
 
  template < typename GUM_SCALAR >
  ExactBNdistance< GUM_SCALAR >::~ExactBNdistance() {
    GUM_DESTRUCTOR(ExactBNdistance);
  }
 
  template < typename GUM_SCALAR >
  void ExactBNdistance< GUM_SCALAR >::computeKL_() {
    klPQ_ = klQP_ = hellinger_ = bhattacharya_ = jsd_ = (GUM_SCALAR)0.0;
    errorPQ_ = errorQP_ = 0;
 
    auto Ip = p_.completeInstantiation();
    auto Iq = q_.completeInstantiation();
 
    // map between p_ variables and q_ variables (using name of vars)
    HashTable< const DiscreteVariable*, const DiscreteVariable* > map;
 
    for (Idx ite = 0; ite < Ip.nbrDim(); ++ite) {
      map.insert(&Ip.variable(ite), &q_.variableFromName(Ip.variable(ite).name()));
    }
    GUM_SCALAR pp, pq, pmid, lpp, lpq, lpmid;
    for (Ip.setFirst(); !Ip.end(); ++Ip) {
      Iq.setValsFrom(map, Ip);
      pp    = p_.jointProbability(Ip);
      pq    = q_.jointProbability(Iq);
      pmid  = (pp + pq) / 2.0;
      lpmid = GUM_LOG2_OR_0(pmid);
      lpp   = GUM_LOG2_OR_0(pp);
      lpq   = GUM_LOG2_OR_0(pq);
 
 
      hellinger_ += std::pow(std::sqrt(pp) - std::sqrt(pq), 2);
      bhattacharya_ += std::sqrt(pp * pq);
 
      if (pp != (GUM_SCALAR)0.0) {
        if (pq != (GUM_SCALAR)0.0) {
          klPQ_ -= pp * (lpq - lpp);   // log2(pq / pp);
        } else {
          errorPQ_++;
        }
      }
 
      if (pq != (GUM_SCALAR)0.0) {
        if (pp != (GUM_SCALAR)0.0) {
          klQP_ -= pq * (lpp - lpq);   // log2(pp / pq);
        } else {
          errorQP_++;
        }
      }
      if (pmid != (GUM_SCALAR)0.0) {
        jsd_ += pp * lpp + pq * lpq
              - (pp + pq) * lpmid;   // pp* log2(pp / pmid) + pq * log2(pq / pmid);
      }
    }
    jsd_ /= 2.0;
    hellinger_    = std::sqrt(hellinger_);
    bhattacharya_ = -std::log(bhattacharya_);
  }
 
}   // namespace gum