Generic ObjectiveVector types
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5 changed files with 40 additions and 8 deletions
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@ -80,7 +80,7 @@ public:
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bestCurrentParetoSet.push_back(arch[i].objectiveVector());
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}
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AtomType hypervolume= metric(bestCurrentParetoSet,OptimSet );
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double hypervolume= metric(bestCurrentParetoSet,OptimSet );
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if (hypervolume==0) {
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eo::log << eo::logging << "STOP in moeoHypContinue: Best ParetoSet has been reached "
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@ -43,9 +43,9 @@ class moeoDualRealObjectiveVector : public moeoScalarObjectiveVector<ObjectiveVe
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public:
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moeoDualRealObjectiveVector(double value=0.0)
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moeoDualRealObjectiveVector(double value=0.0, bool feasible = false)
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: moeoScalarObjectiveVector<ObjectiveVectorTraits, eoMinimizingDualFitness >
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( T(value, false) ) {}
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( T(value, feasible) ) {}
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bool is_feasible() const
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{
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@ -113,4 +113,36 @@ class moeoDualRealObjectiveVector : public moeoScalarObjectiveVector<ObjectiveVe
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};
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/**
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* Output for a moeoDualRealObjectiveVector object
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* @param _os output stream
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* @param _objectiveVector the objective vector to write
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*/
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template < class ObjectiveVectorTraits >
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std::ostream & operator<<(std::ostream & _os, const moeoDualRealObjectiveVector < ObjectiveVectorTraits > & _objectiveVector)
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{
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for (unsigned int i=0; i<_objectiveVector.size()-1; i++)
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_os << _objectiveVector[i] << " ";
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_os << _objectiveVector[_objectiveVector.size()-1];
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return _os;
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}
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/**
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* Input for a moeoDualRealObjectiveVector object
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* @param _is input stream
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* @param _objectiveVector the objective vector to read
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*/
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template < class ObjectiveVectorTraits >
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std::istream & operator>>(std::istream & _is, moeoDualRealObjectiveVector < ObjectiveVectorTraits > & _objectiveVector)
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{
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_objectiveVector = moeoDualRealObjectiveVector < ObjectiveVectorTraits > ();
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for (unsigned int i=0; i<_objectiveVector.size(); i++)
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{
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_is >> _objectiveVector[i];
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}
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return _is;
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}
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#endif /*_DUALREALOBJECTIVEVECTOR_H_*/
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@ -56,7 +56,7 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
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* @param _normalize allow to normalize data (default true)
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* @param _rho coefficient to determine the reference point.
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*/
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moeoHyperVolumeDifferenceMetric(bool _normalize=true, double _rho=1.1): normalize(_normalize), rho(_rho), ref_point(NULL){
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moeoHyperVolumeDifferenceMetric(bool _normalize=true, double _rho=1.1): normalize(_normalize), rho(_rho), ref_point(/*NULL*/){
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bounds.resize(ObjectiveVector::Traits::nObjectives());
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// initialize bounds in case someone does not want to use them
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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@ -70,7 +70,7 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
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* @param _normalize allow to normalize data (default true)
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* @param _ref_point the reference point
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*/
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moeoHyperVolumeDifferenceMetric(bool _normalize=true, ObjectiveVector& _ref_point=NULL): normalize(_normalize), rho(0.0), ref_point(_ref_point){
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moeoHyperVolumeDifferenceMetric(bool _normalize/*=true*/, ObjectiveVector& _ref_point/*=NULL*/): normalize(_normalize), rho(0.0), ref_point(_ref_point){
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bounds.resize(ObjectiveVector::Traits::nObjectives());
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// initialize bounds in case someone does not want to use them
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for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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@ -149,7 +149,7 @@ class moeoHyperVolumeDifferenceMetric : public moeoVectorVsVectorBinaryMetric <
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}
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#endif
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double min, max;
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typename ObjectiveVector::Type min, max;
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unsigned int nbObj=ObjectiveVector::Traits::nObjectives();
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bounds.resize(nbObj);
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for (unsigned int i=0; i<nbObj; i++){
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@ -152,7 +152,7 @@ class moeoHyperVolumeMetric : public moeoVectorUnaryMetric < ObjectiveVector , d
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if(_set.size() < 1)
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throw("Error in moeoHyperVolumeUnaryMetric::setup -> argument1: vector<ObjectiveVector> size must be greater than 0");
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else{
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double min, max;
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typename ObjectiveVector::Type min, max;
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unsigned int nbObj=ObjectiveVector::Traits::nObjectives();
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bounds.resize(nbObj);
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for (unsigned int i=0; i<nbObj; i++){
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@ -109,7 +109,7 @@ public:
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* @param _set2 the second vector of objective vectors
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*/
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void setup(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2){
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double min, max;
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typename ObjectiveVector::Type min, max;
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unsigned int nbObj=ObjectiveVector::Traits::nObjectives();
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bounds.resize(nbObj);
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for (unsigned int i=0; i<nbObj; i++){
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