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add distance

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@374 331e1502-861f-0410-8da2-ba01fb791d7f
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liefooga 2007-06-26 12:10:04 +00:00
commit 792849c8bd
5 changed files with 243 additions and 187 deletions
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193
branches/paradiseo-moeo-1.0/src/distance/moeoDistance.h
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@ -13,9 +13,7 @@
#ifndef MOEODISTANCE_H_ #ifndef MOEODISTANCE_H_
#define MOEODISTANCE_H_ #define MOEODISTANCE_H_
#include <math.h>
#include <eoFunctor.h> #include <eoFunctor.h>
#include <utils/eoRealBounds.h>
/** /**
* The base class for distance computation. * The base class for distance computation.
@ -25,203 +23,32 @@ class moeoDistance : public eoBF < const MOEOT &, const MOEOT &, const Type >
{ {
public: public:
/** /**
* Nothing to do * Nothing to do
* @param _pop the population * @param _pop the population
*/ */
virtual void setup(const eoPop < MOEOT > & _pop) virtual void setup(const eoPop < MOEOT > & _pop)
{} {}
/** /**
* Nothing to do * Nothing to do
* @param _min lower bound * @param _min lower bound
* @param _max upper bound * @param _max upper bound
* @param _obj the objective index * @param _obj the objective index
*/ */
virtual void setup(double _min, double _max, unsigned _obj) virtual void setup(double _min, double _max, unsigned int _obj)
{} {}
/** /**
* Nothing to do * Nothing to do
* @param _realInterval the eoRealInterval object * @param _realInterval the eoRealInterval object
* @param _obj the objective index * @param _obj the objective index
*/ */
virtual void setup(eoRealInterval _realInterval, unsigned _obj) virtual void setup(eoRealInterval _realInterval, unsigned int _obj)
{} {}
}; };
/**
* The base class for double distance computation with normalized objective values (i.e. between 0 and 1).
*/
template < class MOEOT , class Type = double >
class moeoNormalizedDistance : public moeoDistance < MOEOT , Type >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctr
*/
moeoNormalizedDistance()
{
bounds.resize(ObjectiveVector::Traits::nObjectives());
// initialize bounds in case someone does not want to use them
for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
bounds[i] = eoRealInterval(0,1);
}
}
/**
* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
*/
static double tiny()
{
return 1e-6;
}
/**
* Sets the lower and the upper bounds for every objective using extremes values for solutions contained in the population _pop
* @param _pop the population
*/
virtual void setup(const eoPop < MOEOT > & _pop)
{
double min, max;
for (unsigned i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
min = _pop[0].objectiveVector()[i];
max = _pop[0].objectiveVector()[i];
for (unsigned j=1; j<_pop.size(); j++)
{
min = std::min(min, _pop[j].objectiveVector()[i]);
max = std::max(max, _pop[j].objectiveVector()[i]);
}
// setting of the bounds for the objective i
setup(min, max, i);
}
}
/**
* Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
* @param _min lower bound
* @param _max upper bound
* @param _obj the objective index
*/
virtual void setup(double _min, double _max, unsigned _obj)
{
if (_min == _max)
{
_min -= tiny();
_max += tiny();
}
bounds[_obj] = eoRealInterval(_min, _max);
}
/**
* Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
* @param _realInterval the eoRealInterval object
* @param _obj the objective index
*/
virtual void setup(eoRealInterval _realInterval, unsigned _obj)
{
bounds[_obj] = _realInterval;
}
protected:
/** the bounds for every objective (bounds[i] = bounds for the objective i) */
std::vector < eoRealInterval > bounds;
};
/**
* 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).
* A distance value then lies between 0 and sqrt(nObjectives).
*/
template < class MOEOT >
class moeoEuclideanDistance : public moeoNormalizedDistance < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the euclidian distance between _moeo1 and _moeo2 in the objective space
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
double result = 0.0;
double tmp1, tmp2;
for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
{
tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
result += (tmp1-tmp2) * (tmp1-tmp2);
}
return sqrt(result);
}
private:
/** the bounds for every objective */
using moeoNormalizedDistance < MOEOT > :: bounds;
};
/**
* A class allowing to compute the Manhattan distance between two solutions in the objective space normalized objective values (i.e. between 0 and 1).
* A distance value then lies between 0 and nObjectives.
*/
template < class MOEOT >
class moeoManhattanDistance : public moeoNormalizedDistance < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the Manhattan distance between _moeo1 and _moeo2 in the objective space
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
double result = 0.0;
double tmp1, tmp2;
for (unsigned i=0; i<ObjectiveVector::nObjectives(); i++)
{
tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
result += fabs(tmp1-tmp2);
}
return result;
}
private:
/** the bounds for every objective */
using moeoNormalizedDistance < MOEOT > :: bounds;
};
#endif /*MOEODISTANCE_H_*/ #endif /*MOEODISTANCE_H_*/

9
branches/paradiseo-moeo-1.0/src/distance/moeoDistanceMatrix.h
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@ -13,6 +13,7 @@
#ifndef MOEODISTANCEMATRIX_H_ #ifndef MOEODISTANCEMATRIX_H_
#define MOEODISTANCEMATRIX_H_ #define MOEODISTANCEMATRIX_H_
#include <vector>
#include <eoFunctor.h> #include <eoFunctor.h>
#include <distance/moeoDistance.h> #include <distance/moeoDistance.h>
@ -33,10 +34,10 @@ public:
* @param _size size for every dimension of the matrix * @param _size size for every dimension of the matrix
* @param _distance the distance to use * @param _distance the distance to use
*/ */
moeoDistanceMatrix (unsigned _size, moeoDistance < MOEOT , Type > & _distance) : distance(_distance) moeoDistanceMatrix (unsigned int _size, moeoDistance < MOEOT , Type > & _distance) : distance(_distance)
{ {
this->resize(_size); this->resize(_size);
for (unsigned i=0; i<_size; i++) for (unsigned int i=0; i<_size; i++)
{ {
this->operator[](i).resize(_size); this->operator[](i).resize(_size);
} }
@ -53,10 +54,10 @@ public:
distance.setup(_pop); distance.setup(_pop);
// 2 - compute distances // 2 - compute distances
this->operator[](0).operator[](0) = Type(); this->operator[](0).operator[](0) = Type();
for (unsigned i=0; i<size(); i++) for (unsigned int i=0; i<size(); i++)
{ {
this->operator[](i).operator[](i) = Type(); this->operator[](i).operator[](i) = Type();
for (unsigned j=0; j<i; j++) for (unsigned int j=0; j<i; j++)
{ {
this->operator[](i).operator[](j) = distance(_pop[i], _pop[j]); this->operator[](i).operator[](j) = distance(_pop[i], _pop[j]);
this->operator[](j).operator[](i) = this->operator[](i).operator[](j); this->operator[](j).operator[](i) = this->operator[](i).operator[](j);

58
branches/paradiseo-moeo-1.0/src/distance/moeoEuclideanDistance.h Normal file
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@ -0,0 +1,58 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoEuclideanDistance.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOEUCLIDEANDISTANCE_H_
#define MOEOEUCLIDEANDISTANCE_H_
#include <math.h>
#include <distance/moeoNormalizedDistance.h>
/**
* 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).
* A distance value then lies between 0 and sqrt(nObjectives).
*/
template < class MOEOT >
class moeoEuclideanDistance : public moeoNormalizedDistance < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the euclidian distance between _moeo1 and _moeo2 in the objective space
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
double result = 0.0;
double tmp1, tmp2;
for (unsigned int i=0; i<ObjectiveVector::nObjectives(); i++)
{
tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
result += (tmp1-tmp2) * (tmp1-tmp2);
}
return sqrt(result);
}
private:
/** the bounds for every objective */
using moeoNormalizedDistance < MOEOT > :: bounds;
};
#endif /*MOEOEUCLIDEANDISTANCE_H_*/

58
branches/paradiseo-moeo-1.0/src/distance/moeoManhattanDistance.h Normal file
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@ -0,0 +1,58 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoManhattanDistance.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEOMANHATTANDISTANCE_H_
#define MOEOMANHATTANDISTANCE_H_
#include <math.h>
#include <distance/moeoNormalizedDistance.h>
/**
* A class allowing to compute the Manhattan distance between two solutions in the objective space normalized objective values (i.e. between 0 and 1).
* A distance value then lies between 0 and nObjectives.
*/
template < class MOEOT >
class moeoManhattanDistance : public moeoNormalizedDistance < MOEOT >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Returns the Manhattan distance between _moeo1 and _moeo2 in the objective space
* @param _moeo1 the first solution
* @param _moeo2 the second solution
*/
const double operator()(const MOEOT & _moeo1, const MOEOT & _moeo2)
{
double result = 0.0;
double tmp1, tmp2;
for (unsigned int i=0; i<ObjectiveVector::nObjectives(); i++)
{
tmp1 = (_moeo1.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
tmp2 = (_moeo2.objectiveVector()[i] - bounds[i].minimum()) / bounds[i].range();
result += fabs(tmp1-tmp2);
}
return result;
}
private:
/** the bounds for every objective */
using moeoNormalizedDistance < MOEOT > :: bounds;
};
#endif /*MOEOMANHATTANDISTANCE_H_*/

112
branches/paradiseo-moeo-1.0/src/distance/moeoNormalizedDistance.h Normal file
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@ -0,0 +1,112 @@
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
//-----------------------------------------------------------------------------
// moeoNormalizedDistance.h
// (c) OPAC Team (LIFL), Dolphin Project (INRIA), 2007
/*
This library...
Contact: paradiseo-help@lists.gforge.inria.fr, http://paradiseo.gforge.inria.fr
*/
//-----------------------------------------------------------------------------
#ifndef MOEONORMALIZEDDISTANCE_H_
#define MOEONORMALIZEDDISTANCE_H_
#include <vector>
#include <utils/eoRealBounds.h>
#include <distance/moeoDistance.h>
/**
* The base class for double distance computation with normalized objective values (i.e. between 0 and 1).
*/
template < class MOEOT , class Type = double >
class moeoNormalizedDistance : public moeoDistance < MOEOT , Type >
{
public:
/** the objective vector type of the solutions */
typedef typename MOEOT::ObjectiveVector ObjectiveVector;
/**
* Default ctr
*/
moeoNormalizedDistance()
{
bounds.resize(ObjectiveVector::Traits::nObjectives());
// initialize bounds in case someone does not want to use them
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
bounds[i] = eoRealInterval(0,1);
}
}
/**
* Returns a very small value that can be used to avoid extreme cases (where the min bound == the max bound)
*/
static double tiny()
{
return 1e-6;
}
/**
* Sets the lower and the upper bounds for every objective using extremes values for solutions contained in the population _pop
* @param _pop the population
*/
virtual void setup(const eoPop < MOEOT > & _pop)
{
double min, max;
for (unsigned int i=0; i<ObjectiveVector::Traits::nObjectives(); i++)
{
min = _pop[0].objectiveVector()[i];
max = _pop[0].objectiveVector()[i];
for (unsigned int j=1; j<_pop.size(); j++)
{
min = std::min(min, _pop[j].objectiveVector()[i]);
max = std::max(max, _pop[j].objectiveVector()[i]);
}
// setting of the bounds for the objective i
setup(min, max, i);
}
}
/**
* Sets the lower bound (_min) and the upper bound (_max) for the objective _obj
* @param _min lower bound
* @param _max upper bound
* @param _obj the objective index
*/
virtual void setup(double _min, double _max, unsigned int _obj)
{
if (_min == _max)
{
_min -= tiny();
_max += tiny();
}
bounds[_obj] = eoRealInterval(_min, _max);
}
/**
* Sets the lower bound and the upper bound for the objective _obj using a eoRealInterval object
* @param _realInterval the eoRealInterval object
* @param _obj the objective index
*/
virtual void setup(eoRealInterval _realInterval, unsigned int _obj)
{
bounds[_obj] = _realInterval;
}
protected:
/** the bounds for every objective (bounds[i] = bounds for the objective i) */
std::vector < eoRealInterval > bounds;
};
#endif /*MOEONORMALIZEDDISTANCE_H_*/