IBayesNetGenerator_tpl.h

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 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
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 *   SPDX-FileCopyrightText: Copyright 2005-2025                            *
 *       - Pierre-Henri WUILLEMIN(_at_LIP6)                                 *
 *       - Christophe GONZALES(_at_AMU)                                     *
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#pragma once
 

#include <agrum/base/variables/rangeVariable.h>
#include <agrum/BN/generator/IBayesNetGenerator.h>
 
namespace gum {
 
  // Default constructor.
  // Use the SimpleCPTGenerator for generating the BNs CPT.
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::IBayesNetGenerator(Size nbrNodes,
                                                                             Size maxArcs,
                                                                             Size maxModality) :
      dag_() {
    GUM_CONSTRUCTOR(IBayesNetGenerator);
    nbrNodes_ = nbrNodes;
 
    if (maxArcs < nbrNodes - 1 || maxArcs > (nbrNodes * (nbrNodes - 1)) / 2)
      GUM_ERROR(OperationNotAllowed, " maxArcs value not possible ")
 
    if (maxModality < 2) GUM_ERROR(OperationNotAllowed, " maxModality must be at least equal to 2 ")
 
    maxArcs_     = maxArcs;
    maxModality_ = maxModality;
  }
 
  // Destructor.
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::~IBayesNetGenerator() {
    GUM_DESTRUCTOR(IBayesNetGenerator);
    //    delete cptGenerator_;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  void IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::fillCPT(BayesNet< GUM_SCALAR >& bn) const {
    for (auto node: bn.nodes())
      this->generateCPT(bn.cpt(node).pos(bn.variable(node)), bn.cpt(node));
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE Size IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::maxModality() const {
    return maxModality_;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE Size IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::nbrNodes() const {
    return nbrNodes_;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE Size IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::maxArcs() const {
    return maxArcs_;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE void IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setMaxModality(Size maxModality) {
    if (maxModality < 2)
      GUM_ERROR(OperationNotAllowed, " maxModality must be at least equal to two ")
 
    maxModality_ = maxModality;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE void IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setNbrNodes(Size nbrNodes) {
    if ((maxArcs_ < nbrNodes - 1) || (maxArcs_ > (nbrNodes * (nbrNodes - 1)) / 2))
      GUM_ERROR(OperationNotAllowed, " nbrNodes value not possible ")
 
    nbrNodes_ = nbrNodes;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE void IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::setMaxArcs(Size maxArcs) {
    if (maxArcs < nbrNodes_ - 1 || maxArcs > (nbrNodes_ * (nbrNodes_ - 1)) / 2)
      GUM_ERROR(OperationNotAllowed, " maxArcs value not possible ")
 
    maxArcs_ = maxArcs;
  }
 
  template < typename GUM_SCALAR, template < typename > class ICPTGenerator >
  INLINE void IBayesNetGenerator< GUM_SCALAR, ICPTGenerator >::fromDAG(BayesNet< GUM_SCALAR >& bn) {
    bn.clear();
 
    const auto  width = (this->dag_.size() >= 100) ? 3 : 2;
    int         n     = 0;
    const auto& topo  = this->dag_.topologicalOrder();
    for (const auto node: topo) {
      std::stringstream strBuff;
      strBuff << "X" << std::setfill('0') << std::setw(width) << n++;
      bn.add(RangeVariable(strBuff.str(), "", 0, long(1 + randomValue(this->maxModality_ - 1))),
             node);
    }
    bn.beginTopologyTransformation();
    for (auto arc: this->dag_.arcs()) {
      bn.addArc(arc.tail(), arc.head());
    }
    bn.endTopologyTransformation();
  }
 
 
} /* namespace gum */