influenceDiagramGenerator_tpl.h

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

#include <agrum/ID/generator/influenceDiagramGenerator.h>
 
#include <agrum/base/core/utils_random.h>
 
namespace gum {
  // Default constructor.
  // Use the SimpleCPTGenerator for generating the IDs CPT.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagramGenerator< GUM_SCALAR >::InfluenceDiagramGenerator() {
    GUM_CONSTRUCTOR(InfluenceDiagramGenerator)
    _cptGenerator_ = new SimpleCPTGenerator< GUM_SCALAR >();
    _utGenerator_  = new SimpleUTGenerator();
  }
 
  // Use this constructor if you want to use a different policy for generating
  // CPT than the default one.
  // The cptGenerator will be erased when the destructor is called.
  // @param cptGenerator The policy used to generate CPT.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagramGenerator< GUM_SCALAR >::InfluenceDiagramGenerator(
      ICPTGenerator< GUM_SCALAR >* cptGenerator) {
    GUM_CONSTRUCTOR(InfluenceDiagramGenerator)
    _cptGenerator_ = cptGenerator;
    _utGenerator_  = new SimpleUTGenerator();
  }
 
  // Use this constructor if you want to use a different policy for generating
  // UT than the default one.
  // The utGenerator will be erased when the destructor is called.
  // @param utGenerator The policy used to generate UT.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagramGenerator< GUM_SCALAR >::InfluenceDiagramGenerator(UTGenerator* utGenerator) {
    GUM_CONSTRUCTOR(InfluenceDiagramGenerator)
    _cptGenerator_ = new SimpleCPTGenerator< GUM_SCALAR >();
    _utGenerator_  = utGenerator;
  }
 
  // Use this constructor if you want to use a different policy for generating
  // both CPT & UT than the defaults ones.
  // The cptGenerator and utGenerator will be erased when the destructor is
  // called.
  // @param cptGenerator The policy used to generate CPT.
  // @param utGenerator The policy used to generate UT.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagramGenerator< GUM_SCALAR >::InfluenceDiagramGenerator(
      ICPTGenerator< GUM_SCALAR >* cptGenerator,
      UTGenerator*                 utGenerator) {
    GUM_CONSTRUCTOR(InfluenceDiagramGenerator)
    _cptGenerator_ = cptGenerator;
    _utGenerator_  = utGenerator;
  }
 
  // Destructor.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagramGenerator< GUM_SCALAR >::~InfluenceDiagramGenerator() {
    GUM_DESTRUCTOR(InfluenceDiagramGenerator)
    delete _cptGenerator_;
    delete _utGenerator_;
  }
 
  // Generates an influence diagram using floats.
  // @param nbrNodes The number of nodes in the generated ID.
  // @param arcdensity The probability of adding an arc between two nodes.
  // @param chanceNodeDensity The proportion of chance node
  // @param utilityNodeDensity The proportion of utility node
  // @param max_modality Each DRV has from 2 to max_modality modalities
  // @return A IDs randomly generated.
  template < GUM_Numeric GUM_SCALAR >
  InfluenceDiagram< GUM_SCALAR >*
      InfluenceDiagramGenerator< GUM_SCALAR >::generateID(Size       nbrNodes,
                                                          GUM_SCALAR arcDensity,
                                                          GUM_SCALAR chanceNodeDensity,
                                                          GUM_SCALAR utilityNodeDensity,
                                                          Size       max_modality) {
    auto influenceDiagram = new InfluenceDiagram< GUM_SCALAR >();
    // First we add nodes
    HashTable< Size, NodeId > map;
    Size                      nb_mod;
 
    for (Idx i = 0; i < nbrNodes; ++i) {
      const auto varName = std::format("{}", i);
      nb_mod             = (max_modality == 2) ? 2 : 2 + randomValue(max_modality - 1);
 
      GUM_SCALAR cnd = chanceNodeDensity;
      GUM_SCALAR und = utilityNodeDensity;
 
      auto d = (GUM_SCALAR)randomProba();
 
      if (d < cnd)
        map.insert(i, influenceDiagram->addChanceNode(RangeVariable(varName, "", 0, nb_mod - 1)));
      else if (d < (cnd + und))
        map.insert(i, influenceDiagram->addUtilityNode(RangeVariable(varName, "", 0, 0)));
      else
        map.insert(i, influenceDiagram->addDecisionNode(RangeVariable(varName, "", 0, nb_mod - 1)));
    }
 
    // We add arcs
    GUM_SCALAR p = arcDensity;
 
    for (Size i = 0; i < nbrNodes; ++i)
      if (!influenceDiagram->isUtilityNode(map[i]))
        for (Size j = i + 1; j < nbrNodes; ++j)
          if (((GUM_SCALAR)randomProba()) < p) { influenceDiagram->addArc(map[i], map[j]); }
 
    // And fill the CPTs and UTs
    for (Size i = 0; i < nbrNodes; ++i)
      if (influenceDiagram->isChanceNode(map[i]))
        _cptGenerator_->generateCPT(
            influenceDiagram->cpt(map[i]).pos(influenceDiagram->variable(map[i])),
            influenceDiagram->cpt(map[i]));
      else if (influenceDiagram->isUtilityNode(map[i]))
        _utGenerator_->generateUT(
            influenceDiagram->utility(map[i]).pos(influenceDiagram->variable(map[i])),
            influenceDiagram->utility(map[i]));
 
    _checkTemporalOrder_(influenceDiagram);
 
    return influenceDiagram;
  }
 
  template < GUM_Numeric GUM_SCALAR >
  void InfluenceDiagramGenerator< GUM_SCALAR >::_checkTemporalOrder_(
      InfluenceDiagram< GUM_SCALAR >* infdiag) {
    if (!infdiag->decisionOrderExists()) {
      Sequence< NodeId > order = infdiag->topologicalOrder();
 
      auto orderIter = order.begin();
 
      while ((orderIter != order.end()) && (!infdiag->isDecisionNode(*orderIter)))
        ++orderIter;
 
      if (orderIter == order.end()) return;
 
      NodeId parentDecision = (*orderIter);
 
      ++orderIter;
 
      for (; orderIter != order.end(); ++orderIter)
        if (infdiag->isDecisionNode(*orderIter)) {
          infdiag->addArc(parentDecision, (*orderIter));
          parentDecision = (*orderIter);
        }
    }
  }
} /* namespace gum */