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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1813 331e1502-861f-0410-8da2-ba01fb791d7f
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jhumeau 2010-05-17 14:56:42 +00:00
commit 3d8057ac4d
88 changed files with 2726 additions and 2720 deletions
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trunk/paradiseo-mo/src/sampling/moMHRndFitnessCloudSampling.h
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@ -44,8 +44,8 @@
#include <sampling/moFitnessCloudSampling.h>
/**
* To compute an estimation of the fitness cloud,
* i.e. the scatter plot of solution fitness versus neighbor fitness:
* To compute an estimation of the fitness cloud,
* i.e. the scatter plot of solution fitness versus neighbor fitness:
*
* Here solution are sampled with Metropolis-Hasting method
*
@ -53,59 +53,59 @@
* and the fitness of one random neighbor
*
* The values are collected during the Metropolis-Hasting walk
*
*
*/
template <class Neighbor>
class moMHRndFitnessCloudSampling : public moFitnessCloudSampling<Neighbor>
{
public:
typedef typename Neighbor::EOT EOT ;
using moSampling<Neighbor>::localSearch;
using moSampling<Neighbor>::checkpoint;
using moSampling<Neighbor>::monitorVec;
using moSampling<Neighbor>::continuator;
using moFitnessCloudSampling<Neighbor>::fitnessStat;
typedef typename Neighbor::EOT EOT ;
/**
* Default Constructor
* @param _init initialisation method of the solution
* @param _neighborhood neighborhood to get one random neighbor (supposed to be random neighborhood)
* @param _fullEval Fitness function, full evaluation function
* @param _eval neighbor evaluation, incremental evaluation function
* @param _nbStep Number of step of the MH sampling
*/
moMHRndFitnessCloudSampling(eoInit<EOT> & _init,
moNeighborhood<Neighbor> & _neighborhood,
eoEvalFunc<EOT>& _fullEval,
moEval<Neighbor>& _eval,
unsigned int _nbStep) :
moFitnessCloudSampling<Neighbor>(_init, _neighborhood, _fullEval, _eval, _nbStep),
neighborFitnessStat(_neighborhood, _eval)
{
// delete the dummy local search
delete localSearch;
// Metropolis-Hasting sampling
localSearch = new moMetropolisHasting<Neighbor>(_neighborhood, _fullEval, _eval, _nbStep);
using moSampling<Neighbor>::localSearch;
using moSampling<Neighbor>::checkpoint;
using moSampling<Neighbor>::monitorVec;
using moSampling<Neighbor>::continuator;
using moFitnessCloudSampling<Neighbor>::fitnessStat;
// delete the checkpoint with the wrong continuator
delete checkpoint;
/**
* Default Constructor
* @param _init initialisation method of the solution
* @param _neighborhood neighborhood to get one random neighbor (supposed to be random neighborhood)
* @param _fullEval Fitness function, full evaluation function
* @param _eval neighbor evaluation, incremental evaluation function
* @param _nbStep Number of step of the MH sampling
*/
moMHRndFitnessCloudSampling(eoInit<EOT> & _init,
moNeighborhood<Neighbor> & _neighborhood,
eoEvalFunc<EOT>& _fullEval,
moEval<Neighbor>& _eval,
unsigned int _nbStep) :
moFitnessCloudSampling<Neighbor>(_init, _neighborhood, _fullEval, _eval, _nbStep),
neighborFitnessStat(_neighborhood, _eval)
{
// delete the dummy local search
delete localSearch;
// set the continuator
continuator = localSearch->getContinuator();
// Metropolis-Hasting sampling
localSearch = new moMetropolisHasting<Neighbor>(_neighborhood, _fullEval, _eval, _nbStep);
// re-construction of the checkpoint
checkpoint = new moCheckpoint<Neighbor>(*continuator);
checkpoint->add(fitnessStat);
checkpoint->add(*monitorVec[0]);
// delete the checkpoint with the wrong continuator
delete checkpoint;
// one random neighbor
add(neighborFitnessStat);
}
// set the continuator
continuator = localSearch->getContinuator();
// re-construction of the checkpoint
checkpoint = new moCheckpoint<Neighbor>(*continuator);
checkpoint->add(fitnessStat);
checkpoint->add(*monitorVec[0]);
// one random neighbor
add(neighborFitnessStat);
}
protected:
moNeighborFitnessStat< Neighbor > neighborFitnessStat;
moNeighborFitnessStat< Neighbor > neighborFitnessStat;
};