add distance
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branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
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branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoDistance.h
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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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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEODISTANCE_H_
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#define MOEODISTANCE_H_
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#include <math.h>
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#include <eoFunctor.h>
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#include <utils/eoRealBounds.h>
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/**
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* The base class for distance computation.
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*/
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template < class MOEOT , class Type >
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class moeoDistance : public eoBF < const MOEOT &, const MOEOT &, const Type >
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{
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public:
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/**
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* Nothing to do
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* @param _pop the population
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*/
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virtual void setup(const eoPop < MOEOT > & _pop)
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{}
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/**
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* Nothing to do
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* @param _min lower bound
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* @param _max upper bound
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* @param _obj the objective index
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*/
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virtual void setup(double _min, double _max, unsigned _obj)
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{}
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/**
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* Nothing to do
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* @param _realInterval the eoRealInterval object
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* @param _obj the objective index
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*/
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virtual void setup(eoRealInterval _realInterval, unsigned _obj)
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{}
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};
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/**
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* The base class for double distance computation with normalized objective values (i.e. between 0 and 1).
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*/
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template < class MOEOT , class Type = double >
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class moeoNormalizedDistance : public moeoDistance < MOEOT , Type >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Default ctr
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*/
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moeoNormalizedDistance()
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{
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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 i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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bounds[i] = eoRealInterval(0,1);
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}
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}
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/**
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* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
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*/
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static double tiny()
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{
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return 1e-6;
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}
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/**
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* Sets the lower and the upper bounds for every objective using extremes values for solutions contained in the population _pop
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* @param _pop the population
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*/
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virtual void setup(const eoPop < MOEOT > & _pop)
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{
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double min, max;
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for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
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{
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min = _pop[0].objectiveVector()[i];
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max = _pop[0].objectiveVector()[i];
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for (unsigned j=1; j<_pop.size(); j++)
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{
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min = std::min(min, _pop[j].objectiveVector()[i]);
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max = std::max(max, _pop[j].objectiveVector()[i]);
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}
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// setting of the bounds for the objective i
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setup(min, max, i);
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}
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}
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/**
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* Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
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* @param _min lower bound
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* @param _max upper bound
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* @param _obj the objective index
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*/
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virtual void setup(double _min, double _max, unsigned _obj)
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{
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if (_min == _max)
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{
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_min -= tiny();
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_max += tiny();
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}
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bounds[_obj] = eoRealInterval(_min, _max);
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}
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/**
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* Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
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* @param _realInterval the eoRealInterval object
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* @param _obj the objective index
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*/
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virtual void setup(eoRealInterval _realInterval, unsigned _obj)
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{
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bounds[_obj] = _realInterval;
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}
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protected:
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/** the bounds for every objective (bounds[i] = bounds for the objective i) */
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std::vector < eoRealInterval > bounds;
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};
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/**
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* A class allowing to compute an euclidian distance between two solutions in the objective space with normalized objective values (i.e. between 0 and 1).
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* A distance value then lies between 0 and sqrt(nObjectives).
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*/
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template < class MOEOT >
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class moeoEuclideanDistance : public moeoNormalizedDistance < MOEOT >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Returns the euclidian distance between _moeo1 and _moeo2 in the objective space
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* @param _moeo1 the first solution
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* @param _moeo2 the second solution
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*/
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const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
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{
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double result = 0.0;
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double tmp1, tmp2;
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for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
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{
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tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
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tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
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result += (tmp1-tmp2) * (tmp1-tmp2);
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}
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return sqrt(result);
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}
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private:
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/** the bounds for every objective */
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using moeoNormalizedDistance < MOEOT > :: bounds;
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};
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/**
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* A class allowing to compute the Manhattan distance between two solutions in the objective space normalized objective values (i.e. between 0 and 1).
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* A distance value then lies between 0 and nObjectives.
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*/
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template < class MOEOT >
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class moeoManhattanDistance : public moeoNormalizedDistance < MOEOT >
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{
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public:
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/** the objective vector type of the solutions */
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typedef typename MOEOT::ObjectiveVector ObjectiveVector;
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/**
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* Returns the Manhattan distance between _moeo1 and _moeo2 in the objective space
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* @param _moeo1 the first solution
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* @param _moeo2 the second solution
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*/
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const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
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{
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double result = 0.0;
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double tmp1, tmp2;
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for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
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{
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tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
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tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
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result += fabs(tmp1-tmp2);
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}
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return result;
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}
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private:
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/** the bounds for every objective */
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using moeoNormalizedDistance < MOEOT > :: bounds;
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};
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#endif /*MOEODISTANCE_H_*/
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@ -0,0 +1,75 @@
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// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// moeoDistanceMatrix.h
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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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Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
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*/
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//-----------------------------------------------------------------------------
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#ifndef MOEODISTANCEMATRIX_H_
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#define MOEODISTANCEMATRIX_H_
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#include <eoFunctor.h>
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#include <distance/moeoDistance.h>
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/**
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* A matrix to compute distances between every pair of individuals contained in a population.
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*/
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template < class MOEOT , class Type >
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class moeoDistanceMatrix : public eoUF < const eoPop < MOEOT > &, void > , public std::vector< std::vector < Type > >
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{
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public:
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using std::vector< std::vector < Type > > :: size;
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using std::vector< std::vector < Type > > :: operator[];
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/**
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* Ctor
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* @param _size size for every dimension of the matrix
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* @param _distance the distance to use
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*/
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moeoDistanceMatrix (unsigned _size, moeoDistance < MOEOT , Type > & _distance) : distance(_distance)
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{
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this->resize(_size);
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for(unsigned i=0; i<_size; i++)
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{
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this->operator[](i).resize(_size);
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}
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}
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/**
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* Sets the distance between every pair of individuals contained in the population _pop
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* @param _pop the population
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*/
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void operator()(const eoPop < MOEOT > & _pop)
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{
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// 1 - setup the bounds (if necessary)
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distance.setup(_pop);
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// 2 - compute distances
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this->operator[](0).operator[](0) = Type();
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for (unsigned i=0; i<size(); i++)
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{
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this->operator[](i).operator[](i) = Type();
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for (unsigned j=0; j<i; j++)
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{
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this->operator[](i).operator[](j) = distance(_pop[i], _pop[j]);
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this->operator[](j).operator[](i) = this->operator[](i).operator[](j);
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}
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}
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}
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private:
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/** the distance to use */
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moeoDistance < MOEOT , Type > & distance;
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};
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#endif /*MOEODISTANCEMATRIX_H_*/
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