metrics modification
git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@180 331e1502-861f-0410-8da2-ba01fb791d7f
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4 changed files with 78 additions and 70 deletions
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@ -2,7 +2,7 @@
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//-----------------------------------------------------------------------------
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// moeoBinaryMetricSavingUpdater.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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@ -20,18 +20,18 @@
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#include <metric/moeoMetric.h>
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/**
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* This class allows to save the progression of a binary metric comparing the fitness values of the current population (or archive)
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* with the fitness values of the population (or archive) of the generation (n-1) into a file
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* This class allows to save the progression of a binary metric comparing the objective vectors of the current population (or archive)
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* with the objective vectors of the population (or archive) of the generation (n-1) into a file
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*/
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template <class EOT>
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template < class MOEOT >
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class moeoBinaryMetricSavingUpdater : public eoUpdater
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{
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public:
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/**
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* The fitness type of a solution
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* The objective vector type of a solution
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*/
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typedef typename EOT::ObjectiveVector ObjectiveVector;
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Ctor
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@ -39,7 +39,7 @@ public:
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* @param _pop the main population
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* @param _filename the target filename
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*/
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moeoBinaryMetricSavingUpdater (moeoPopVsPopBinaryMetric<EOT,double> & _metric, const eoPop<EOT> & _pop, std::string _filename) :
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moeoBinaryMetricSavingUpdater (moeoVectorVsVectorBinaryMetric < ObjectiveVector, double > & _metric, const eoPop < MOEOT > & _pop, std::string _filename) :
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metric(_metric), pop(_pop), filename(_filename), counter(1)
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{}
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@ -53,17 +53,15 @@ public:
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}
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else {
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// creation of the two Pareto sets
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/*
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std::vector<ObjectiveVector> from;
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std::vector<ObjectiveVector> to;
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std::vector < ObjectiveVector > from;
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std::vector < ObjectiveVector > to;
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for (unsigned i=0; i<pop.size(); i++)
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from.push_back(pop[i].objectiveVector());
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for (unsigned i=0 ; i<oldPop.size(); i++)
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to.push_back(oldPop[i].objectiveVector());
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*/
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// writing the result into the file
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std::ofstream f (filename.c_str(), std::ios::app);
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f << counter++ << ' ' << metric(pop,oldPop) << std::endl;
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f << counter++ << ' ' << metric(from,to) << std::endl;
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f.close();
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}
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oldPop = pop;
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@ -73,11 +71,11 @@ public:
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private:
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/** binary metric comparing two Pareto sets */
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moeoPopVsPopBinaryMetric<EOT,double> & metric;
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moeoVectorVsVectorBinaryMetric < ObjectiveVector, double > & metric;
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/** main population */
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const eoPop<EOT> & pop;
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const eoPop < MOEOT > & pop;
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/** (n-1) population */
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eoPop<EOT> oldPop;
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eoPop< MOEOT > oldPop;
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/** target filename */
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std::string filename;
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/** is it the first generation ? */
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@ -2,7 +2,7 @@
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//-----------------------------------------------------------------------------
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// moeoContributionMetric.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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@ -17,37 +17,24 @@
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/**
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* The contribution metric evaluates the proportion of non-dominated solutions given by a Pareto set relatively to another Pareto set
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*
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* (Meunier, Talbi, Reininger: 'A multiobjective genetic algorithm for radio network optimization', in Proc. of the 2000 Congress on Evolutionary Computation, IEEE Press, pp. 317-324)
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*/
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template < class MOEOT >
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class moeoContributionMetric : public moeoPopVsPopBinaryMetric < MOEOT, double >
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template < class ObjectiveVector >
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class moeoContributionMetric : public moeoVectorVsVectorBinaryMetric < ObjectiveVector, double >
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{
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public:
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/** the objective vector type of a solution */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Returns the contribution of the Pareto set '_set1' relatively to the Pareto set '_set2'
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* @param _set1 the first Pareto set
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* @param _set2 the second Pareto set
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*/
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double operator()(const eoPop < MOEOT > & _pop1, const eoPop < MOEOT > & _pop2) {
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/************/
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std::vector<ObjectiveVector> set1;
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std::vector<ObjectiveVector> set2;
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for (unsigned i=0; i<_pop1.size(); i++)
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set1.push_back(_pop1[i].objectiveVector());
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for (unsigned i=0 ; i<_pop2.size(); i++)
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set2.push_back(_pop2[i].objectiveVector());
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/****************/
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unsigned c = card_C(set1, set2);
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unsigned w1 = card_W(set1, set2);
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unsigned n1 = card_N(set1, set2);
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unsigned w2 = card_W(set2, set1);
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unsigned n2 = card_N(set2, set1);
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double operator()(const std::vector < ObjectiveVector > & _set1, const std::vector < ObjectiveVector > & _set2) {
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unsigned c = card_C(_set1, _set2);
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unsigned w1 = card_W(_set1, _set2);
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unsigned n1 = card_N(_set1, _set2);
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unsigned w2 = card_W(_set2, _set1);
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unsigned n2 = card_N(_set2, _set1);
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return (double) (c / 2.0 + w1 + n1) / (c + w1 + n1 + w2 + n2);
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}
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@ -2,7 +2,7 @@
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//-----------------------------------------------------------------------------
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// moeoEntropyMetric.h
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2006
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// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
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/*
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This library...
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@ -16,18 +16,14 @@
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#include <metric/moeoMetric.h>
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/**
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* The entropy gives an idea of the diversity of a Pareto set relatively to another Pareto set
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*
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* The entropy gives an idea of the diversity of a Pareto set relatively to another
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* (Basseur, Seynhaeve, Talbi: 'Design of Multi-objective Evolutionary Algorithms: Application to the Flow-shop Scheduling Problem', in Proc. of the 2002 Congress on Evolutionary Computation, IEEE Press, pp. 1155-1156)
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*/
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template < class MOEOT >
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class moeoEntropyMetric : public moeoVectorVsVectorBinaryMetric < MOEOT, double >
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template < class ObjectiveVector >
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class moeoEntropyMetric : public moeoVectorVsVectorBinaryMetric < ObjectiveVector, double >
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{
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public:
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/** the objective vector type of a solution */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Returns the entropy of the Pareto set '_set1' relatively to the Pareto set '_set2'
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* @param _set1 the first Pareto set
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@ -72,10 +68,17 @@ public:
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private:
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/** vector of min values */
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std::vector<double> vect_min_val;
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/** vector of max values */
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std::vector<double> vect_max_val;
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void removeDominated(std::vector< ObjectiveVector > & _f) {
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/**
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* Removes the dominated individuals contained in _f
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* @param _f a Pareto set
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*/
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void removeDominated(std::vector < ObjectiveVector > & _f) {
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for (unsigned i=0 ; i<_f.size(); i++) {
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bool dom = false;
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for (unsigned j=0; j<_f.size(); j++)
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}
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}
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/**
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* Prenormalization
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* @param _f a Pareto set
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*/
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void prenormalize (const std::vector< ObjectiveVector > & _f) {
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vect_min_val.clear();
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vect_max_val.clear();
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}
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}
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/**
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* Normalization
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* @param _f a Pareto set
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*/
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void normalize (std::vector< ObjectiveVector > & _f) {
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for (unsigned i=0 ; i<ObjectiveVector::nObjectives(); i++)
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for (unsigned j=0; j<_f.size(); j++)
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_f[j][i] = (_f[j][i] - vect_min_val[i]) / (vect_max_val[i] - vect_min_val[i]);
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}
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/**
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* Computation of the union of _f1 and _f2 in _f
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* @param _f1 the first Pareto set
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* @param _f2 the second Pareto set
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* @param _f the final Pareto set
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*/
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void computeUnion(const std::vector< ObjectiveVector > & _f1, const std::vector< ObjectiveVector > & _f2, std::vector< ObjectiveVector > & _f) {
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_f = _f1 ;
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for (unsigned i=0; i<_f2.size(); i++) {
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}
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}
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/**
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* How many in niche
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*/
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unsigned howManyInNicheOf (const std::vector< ObjectiveVector > & _f, const ObjectiveVector & _s, unsigned _size) {
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unsigned n=0;
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for (unsigned i=0 ; i<_f.size(); i++) {
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return n;
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}
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/**
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* Euclidian distance
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*/
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double euclidianDistance (const ObjectiveVector & _set1, const ObjectiveVector & _to, unsigned _deg = 2) {
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double dist=0;
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for (unsigned i=0; i<_set1.size(); i++)
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#include <eoFunctor.h>
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/**
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* Base class for performance metrics (also called quality indicators)
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* Base class for performance metrics (also known as quality indicators).
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*/
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class moeoMetric : public eoFunctorBase
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{};
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/**
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* Base class for unary metrics
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* Base class for unary metrics.
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*/
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template < class A, class R >
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class moeoUnaryMetric : public eoUF < A, R >, public moeoMetric
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@ -31,7 +31,7 @@ class moeoUnaryMetric : public eoUF < A, R >, public moeoMetric
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/**
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* Base class for binary metrics
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* Base class for binary metrics.
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*/
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template < class A1, class A2, class R >
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class moeoBinaryMetric : public eoBF < A1, A2, R >, public moeoMetric
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@ -39,47 +39,42 @@ class moeoBinaryMetric : public eoBF < A1, A2, R >, public moeoMetric
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/**
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* Base class for unary metrics dedicated to the performance evaluation of a single solution's Pareto fitness
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* Base class for unary metrics dedicated to the performance evaluation of a single solution's objective vector.
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*/
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template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
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//class moeoSolutionUnaryMetric : public moeoUnaryMetric < const ObjVector &, R >
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class moeoSolutionUnaryMetric : public moeoUnaryMetric < const MOEOT &, R >
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template < class ObjectiveVector, class R >
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class moeoSolutionUnaryMetric : public moeoUnaryMetric < const ObjectiveVector &, R >
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{};
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/**
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* Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of Pareto fitnesses)
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* Base class for unary metrics dedicated to the performance evaluation of a Pareto set (a vector of objective vectors)
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*/
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template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
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//class moeoVectorUnaryMetric : public moeoUnaryMetric < const std::vector < ObjVector > &, R >
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class moeoPopUnaryMetric : public moeoUnaryMetric < const eoPop < MOEOT > &, R >
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template < class ObjectiveVector, class R >
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class moeoVectorUnaryMetric : public moeoUnaryMetric < const std::vector < ObjectiveVector > &, R >
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{};
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/**
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* Base class for binary metrics dedicated to the performance comparison between two solutions's Pareto fitnesses
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* Base class for binary metrics dedicated to the performance comparison between two solutions's objective vectors.
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*/
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template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
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//class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const ObjVector &, const ObjVector &, R >
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class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const MOEOT &, const MOEOT &, R >
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template < class ObjectiveVector, class R >
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class moeoSolutionVsSolutionBinaryMetric : public moeoBinaryMetric < const ObjectiveVector &, const ObjectiveVector &, R >
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{};
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/**
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* Base class for binary metrics dedicated to the performance comparison between a Pareto set (a vector of Pareto fitnesses) and a single solution's Pareto fitness
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* Base class for binary metrics dedicated to the performance comparison between a Pareto set (a vector of objective vectors) and a single solution's objective vector.
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*/
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template < class MOEOT, class R>//, class ObjVector = typename MOEOT::ObjectiveVector >
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//class moeoVectorVsSolutionBinaryMetric : public moeoBinaryMetric < const std::vector < ObjVector > &, const ObjVector &, R >
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class moeoPopVsSolutionBinaryMetric : public moeoBinaryMetric < const eoPop < MOEOT > &, const MOEOT &, R >
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template < class ObjectiveVector, class R >
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class moeoVectorVsSolutionBinaryMetric : public moeoBinaryMetric < const std::vector < ObjectiveVector > &, const ObjectiveVector &, R >
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{};
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/**
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* Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of Pareto fitnesses)
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* Base class for binary metrics dedicated to the performance comparison between two Pareto sets (two vectors of objective vectors)
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*/
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template < class MOEOT, class R >//, class ObjVector = typename MOEOT::ObjectiveVector >
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//class moeoVectorVsVectorBinaryMetric : public moeoBinaryMetric < const std::vector < ObjVector > &, const std::vector < ObjVector > &, R >
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class moeoPopVsPopBinaryMetric : public moeoBinaryMetric < const eoPop < MOEOT > &, const eoPop < MOEOT > &, R >
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template < class ObjectiveVector, class R >
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class moeoVectorVsVectorBinaryMetric : public moeoBinaryMetric < const std::vector < ObjectiveVector > &, const std::vector < ObjectiveVector > &, R >
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{};
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