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Ajout de la random neutral walk sampling, on tient le bon bout ;)

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1797 331e1502-861f-0410-8da2-ba01fb791d7f
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verel 2010-05-07 09:05:31 +00:00
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88
trunk/paradiseo-mo/src/continuator/moAverageFitnessNeighborStat.h Normal file
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@ -0,0 +1,88 @@
/*
<moAverageFitnessNeighborStat.h>
Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
Sébastien Verel, Arnaud Liefooghe, Jérémie Humeau
This software is governed by the CeCILL license under French law and
abiding by the rules of distribution of free software. You can use,
modify and/ or redistribute the software under the terms of the CeCILL
license as circulated by CEA, CNRS and INRIA at the following URL
"http://www.cecill.info".
As a counterpart to the access to the source code and rights to copy,
modify and redistribute granted by the license, users are provided only
with a limited warranty and the software's author, the holder of the
economic rights, and the successive licensors have only limited liability.
In this respect, the user's attention is drawn to the risks associated
with loading, using, modifying and/or developing or reproducing the
software by the user in light of its specific status of free software,
that may mean that it is complicated to manipulate, and that also
therefore means that it is reserved for developers and experienced
professionals having in-depth computer knowledge. Users are therefore
encouraged to load and test the software's suitability as regards their
requirements in conditions enabling the security of their systems and/or
data to be ensured and, more generally, to use and operate it in the
same conditions as regards security.
The fact that you are presently reading this means that you have had
knowledge of the CeCILL license and that you accept its terms.
ParadisEO WebSite : http://paradiseo.gforge.inria.fr
Contact: paradiseo-help@lists.gforge.inria.fr
*/
#ifndef moAverageFitnessNeighborStat_h
#define moAverageFitnessNeighborStat_h
#include <continuator/moStat.h>
#include <continuator/moNeighborhoodStat.h>
/**
* From moNeighborhoodStat, to compute the average and the standard deviation of fitness in the neighborhood
*/
template< class Neighbor >
class moAverageFitnessNeighborStat : public moStat<typename Neighbor::EOT, double >
{
public :
typedef typename Neighbor::EOT EOT ;
typedef typename EOT::Fitness Fitness ;
using moStat< EOT, double >::value;
/**
* Default Constructor
* @param _nhStat a neighborhoodStat
*/
moAverageFitnessNeighborStat(moNeighborhoodStat<Neighbor> & _nhStat):
moStat<EOT, double >(0.0, "average"), nhStat(_nhStat) {}
/**
* Set the average and the standard deviation of fitness in the neighborhood
* @param _sol the first solution
*/
virtual void init(EOT & _sol) {
value() = nhStat.getMean();
}
/**
* Set the average and the standard deviation of fitness in the neighborhood
* @param _sol the corresponding solution
*/
virtual void operator()(EOT & _sol) {
value() = nhStat.getMean();
}
/**
* @return the class name
*/
virtual std::string className(void) const {
return "moAverageFitnessNeighborStat";
}
private:
/** moNeighborhoodStat */
moNeighborhoodStat<Neighbor> & nhStat;
};
#endif

88
trunk/paradiseo-mo/src/continuator/moStdFitnessNeighborStat.h Normal file
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/*
<moStdFitnessNeighborStat.h>
Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
Sébastien Verel, Arnaud Liefooghe, Jérémie Humeau
This software is governed by the CeCILL license under French law and
abiding by the rules of distribution of free software. You can use,
modify and/ or redistribute the software under the terms of the CeCILL
license as circulated by CEA, CNRS and INRIA at the following URL
"http://www.cecill.info".
As a counterpart to the access to the source code and rights to copy,
modify and redistribute granted by the license, users are provided only
with a limited warranty and the software's author, the holder of the
economic rights, and the successive licensors have only limited liability.
In this respect, the user's attention is drawn to the risks associated
with loading, using, modifying and/or developing or reproducing the
software by the user in light of its specific status of free software,
that may mean that it is complicated to manipulate, and that also
therefore means that it is reserved for developers and experienced
professionals having in-depth computer knowledge. Users are therefore
encouraged to load and test the software's suitability as regards their
requirements in conditions enabling the security of their systems and/or
data to be ensured and, more generally, to use and operate it in the
same conditions as regards security.
The fact that you are presently reading this means that you have had
knowledge of the CeCILL license and that you accept its terms.
ParadisEO WebSite : http://paradiseo.gforge.inria.fr
Contact: paradiseo-help@lists.gforge.inria.fr
*/
#ifndef moStdFitnessNeighborStat_h
#define moStdFitnessNeighborStat_h
#include <continuator/moStat.h>
#include <continuator/moNeighborhoodStat.h>
/**
* From moNeighborhoodStat, to compute the average and the standard deviation of fitness in the neighborhood
*/
template< class Neighbor >
class moStdFitnessNeighborStat : public moStat<typename Neighbor::EOT, double >
{
public :
typedef typename Neighbor::EOT EOT ;
typedef typename EOT::Fitness Fitness ;
using moStat< EOT, double >::value;
/**
* Default Constructor
* @param _nhStat a neighborhoodStat
*/
moStdFitnessNeighborStat(moNeighborhoodStat<Neighbor> & _nhStat):
moStat<EOT, double >(0.0, "stdev"), nhStat(_nhStat) {}
/**
* Set the average and the standard deviation of fitness in the neighborhood
* @param _sol the first solution
*/
virtual void init(EOT & _sol) {
value() = nhStat.getSD();
}
/**
* Set the average and the standard deviation of fitness in the neighborhood
* @param _sol the corresponding solution
*/
virtual void operator()(EOT & _sol) {
value() = nhStat.getSD();
}
/**
* @return the class name
*/
virtual std::string className(void) const {
return "moStdFitnessNeighborStat";
}
private:
/** moNeighborhoodStat */
moNeighborhoodStat<Neighbor> & nhStat;
};
#endif

5
trunk/paradiseo-mo/src/mo.h
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@ -45,6 +45,7 @@
#include <algo/moRandomBestHC.h>
#include <algo/moNeutralHC.h>
#include <algo/moRandomWalk.h>
#include <algo/moRandomNeutralWalk.h>
#include <algo/moTS.h>
#include <algo/moILS.h>
@ -67,6 +68,8 @@
#include <continuator/moNeighborhoodStat.h>
#include <continuator/moNeutralDegreeNeighborStat.h>
#include <continuator/moSecondMomentNeighborStat.h>
#include <continuator/moAverageFitnessNeighborStat.h>
#include <continuator/moStdFitnessNeighborStat.h>
#include <continuator/moSizeNeighborStat.h>
#include <continuator/moCounterStat.h>
#include <continuator/moCounterMinusOneStat.h>
@ -133,6 +136,7 @@
#include <perturb/moRestartPerturb.h>
#include <perturb/moNeighborhoodPerturb.h>
#include <perturb/moLocalSearchInit.h>
#include <perturb/moSolInit.h>
#include <acceptCrit/moAcceptanceCriterion.h>
#include <acceptCrit/moAlwaysAcceptCrit.h>
@ -152,6 +156,7 @@
#include <sampling/moRndBestFitnessCloudSampling.h>
#include <sampling/moMHRndFitnessCloudSampling.h>
#include <sampling/moMHBestFitnessCloudSampling.h>
#include <sampling/moNeutralWalkSampling.h>
#include <problems/bitString/moBitNeighbor.h>
#include <problems/eval/moOneMaxIncrEval.h>

60
trunk/paradiseo-mo/src/perturb/moSolInit.h Normal file
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@ -0,0 +1,60 @@
/*
<moSolInit.h>
Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
Sebastien Verel, Arnaud Liefooghe, Jeremie Humeau
This software is governed by the CeCILL license under French law and
abiding by the rules of distribution of free software. You can ue,
modify and/ or redistribute the software under the terms of the CeCILL
license as circulated by CEA, CNRS and INRIA at the following URL
"http://www.cecill.info".
In this respect, the user's attention is drawn to the risks associated
with loading, using, modifying and/or developing or reproducing the
software by the user in light of its specific status of free software,
that may mean that it is complicated to manipulate, and that also
therefore means that it is reserved for developers and experienced
professionals having in-depth computer knowledge. Users are therefore
encouraged to load and test the software's suitability as regards their
requirements in conditions enabling the security of their systems and/or
data to be ensured and, more generally, to use and operate it in the
same conditions as regards security.
The fact that you are presently reading this means that you have had
knowledge of the CeCILL license and that you accept its terms.
ParadisEO WebSite : http://paradiseo.gforge.inria.fr
Contact: paradiseo-help@lists.gforge.inria.fr
*/
#ifndef _moSolInit_h
#define _moSolInit_h
#include <eoInit.h>
/**
* Initialization of the solution with the external solution
*/
template< class EOT >
class moSolInit : public eoInit<EOT> {
public:
/**
* Default Constructor
* @param _extSol external solution of the intiialization
*/
moSolInit(EOT & _extSol) : extSol(_extSol) {
}
/**
* Initialization on the externatl solution
* @param _solution to initialize
*/
void operator()(EOT& _solution){
_solution = extSol;
}
private:
EOT& extSol;
};
#endif

2
trunk/paradiseo-mo/src/sampling/moMHRndFitnessCloudSampling.h
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@ -52,7 +52,7 @@
* Sample the fitness of solutions from Metropolis-Hasting sampling
* and the fitness of one random neighbor
*
* The values are collected during the random search
* The values are collected during the Metropolis-Hasting walk
*
*/
template <class Neighbor>

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trunk/paradiseo-mo/src/sampling/moNeutralWalkSampling.h Normal file
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@ -0,0 +1,148 @@
/*
<moNeutralWalkSampling.h>
Copyright (C) DOLPHIN Project-Team, INRIA Lille - Nord Europe, 2006-2010
Sebastien Verel, Arnaud Liefooghe, Jeremie Humeau
This software is governed by the CeCILL license under French law and
abiding by the rules of distribution of free software. You can use,
modify and/ or redistribute the software under the terms of the CeCILL
license as circulated by CEA, CNRS and INRIA at the following URL
"http://www.cecill.info".
As a counterpart to the access to the source code and rights to copy,
modify and redistribute granted by the license, users are provided only
with a limited warranty and the software's author, the holder of the
economic rights, and the successive licensors have only limited liability.
In this respect, the user's attention is drawn to the risks associated
with loading, using, modifying and/or developing or reproducing the
software by the user in light of its specific status of free software,
that may mean that it is complicated to manipulate, and that also
therefore means that it is reserved for developers and experienced
professionals having in-depth computer knowledge. Users are therefore
encouraged to load and test the software's suitability as regards their
requirements in conditions enabling the security of their systems and/or
data to be ensured and, more generally, to use and operate it in the
same conditions as regards security.
The fact that you are presently reading this means that you have had
knowledge of the CeCILL license and that you accept its terms.
ParadisEO WebSite : http://paradiseo.gforge.inria.fr
Contact: paradiseo-help@lists.gforge.inria.fr
*/
#ifndef moNeutralWalkSampling_h
#define moNeutralWalkSampling_h
#include <eoInit.h>
#include <eval/moEval.h>
#include <eoEvalFunc.h>
#include <algo/moRandomNeutralWalk.h>
#include <sampling/moSampling.h>
#include <perturb/moSolInit.h>
#include <continuator/moSolutionStat.h>
#include <utils/eoDistance.h>
#include <continuator/moDistanceStat.h>
#include <continuator/moNeighborhoodStat.h>
#include <continuator/moMaxNeighborStat.h>
#include <continuator/moMinNeighborStat.h>
#include <continuator/moAverageFitnessNeighborStat.h>
#include <continuator/moStdFitnessNeighborStat.h>
#include <continuator/moSizeNeighborStat.h>
#include <continuator/moNbInfNeighborStat.h>
#include <continuator/moNbSupNeighborStat.h>
#include <continuator/moNeutralDegreeNeighborStat.h>
/**
* To explore the evolvability of solutions in a neutral networks:
* Perform a random neutral walk based on the neighborhood,
* The measures of evolvability of solutions are collected during the random neutral walk
* The distribution and autocorrelation can be computed from the serie of values
*
* Informations collected:
* - the current solution of the walk
* - the distance from the starting solution
* - the minimal fitness in the neighborhood
* - the average fitness
* - the standard deviation of the fitness
* - the maximal fitness
* - the size of the neighborhood
* - the number of neighbors with lower fitness
* - the number of neighbors with equal fitness (neutral degree)
* - the number of neighbors with higher fitness
*/
template <class Neighbor>
class moNeutralWalkSampling : public moSampling<Neighbor>
{
public:
typedef typename Neighbor::EOT EOT ;
using moSampling<Neighbor>::localSearch;
/**
* Default Constructor
* @param _initSol the first the solution of the walk
* @param _neighborhood neighborhood giving neighbor in random order
* @param _fullEval Fitness function, full evaluation function
* @param _eval neighbor evaluation, incremental evaluation function
* @param _distance the distance to measure the distance from the initial solution
* @param _nbStep Number of steps of the random walk
*/
moNeutralWalkSampling(EOT & _initSol,
moNeighborhood<Neighbor> & _neighborhood,
eoEvalFunc<EOT>& _fullEval,
moEval<Neighbor>& _eval,
eoDistance<EOT> & _distance,
unsigned int _nbStep) :
moSampling<Neighbor>(init, * new moRandomNeutralWalk<Neighbor>(_neighborhood, _fullEval, _eval, _nbStep), solutionStat),
init(_initSol),
distStat(_distance, _initSol),
neighborhoodStat(_neighborhood, _eval),
minStat(neighborhoodStat),
averageStat(neighborhoodStat),
stdStat(neighborhoodStat),
maxStat(neighborhoodStat),
nbSupStat(neighborhoodStat),
nbInfStat(neighborhoodStat),
sizeStat(neighborhoodStat),
ndStat(neighborhoodStat)
{
add(neighborhoodStat, false);
add(distStat);
add(minStat);
add(averageStat);
add(stdStat);
add(maxStat);
add(sizeStat);
add(nbInfStat);
add(ndStat);
add(nbSupStat);
}
/**
* default destructor
*/
~moNeutralWalkSampling() {
// delete the pointer on the local search which has been constructed in the constructor
delete localSearch;
}
protected:
moSolInit<EOT> init;
moSolutionStat<EOT> solutionStat;
moDistanceStat<EOT> distStat;
moNeighborhoodStat< Neighbor > neighborhoodStat;
moMinNeighborStat< Neighbor > minStat;
moAverageFitnessNeighborStat< Neighbor > averageStat;
moStdFitnessNeighborStat< Neighbor > stdStat;
moMaxNeighborStat< Neighbor > maxStat;
moNbSupNeighborStat< Neighbor > nbSupStat;
moNbInfNeighborStat< Neighbor > nbInfStat;
moSizeNeighborStat< Neighbor > sizeStat;
moNeutralDegreeNeighborStat< Neighbor > ndStat;
};
#endif

2
trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt
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@ -16,6 +16,7 @@ ADD_EXECUTABLE(adaptiveWalks adaptiveWalks.cpp)
ADD_EXECUTABLE(fdc fdc.cpp)
ADD_EXECUTABLE(neutralDegree neutralDegree.cpp)
ADD_EXECUTABLE(fitnessCloud fitnessCloud.cpp)
ADD_EXECUTABLE(neutralWalk neutralWalk.cpp)
TARGET_LINK_LIBRARIES(testRandomWalk eoutils ga eo)
TARGET_LINK_LIBRARIES(testMetropolisHasting eoutils ga eo)
@ -27,3 +28,4 @@ TARGET_LINK_LIBRARIES(adaptiveWalks eoutils ga eo)
TARGET_LINK_LIBRARIES(fdc eoutils ga eo)
TARGET_LINK_LIBRARIES(neutralDegree eoutils ga eo)
TARGET_LINK_LIBRARIES(fitnessCloud eoutils ga eo)
TARGET_LINK_LIBRARIES(neutralWalk eoutils ga eo)

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trunk/paradiseo-mo/tutorial/Lesson6/neutralWalk.cpp Normal file
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@ -0,0 +1,222 @@
//-----------------------------------------------------------------------------
/** neutralWalk.cpp
*
* SV - 07/05/10
*
*/
//-----------------------------------------------------------------------------
// standard includes
#define HAVE_SSTREAM
#include <stdexcept> // runtime_error
#include <iostream> // cout
#include <sstream> // ostrstream, istrstream
#include <fstream>
#include <string.h>
// the general include for eo
#include <eo>
// declaration of the namespace
using namespace std;
//-----------------------------------------------------------------------------
// representation of solutions, and neighbors
#include <ga/eoBit.h> // bit string : see also EO tutorial lesson 1: FirstBitGA.cpp
#include <problems/bitString/moBitNeighbor.h> // neighbor of bit string
//-----------------------------------------------------------------------------
// fitness function, and evaluation of neighbors
#include <eval/royalRoadEval.h>
#include <problems/eval/moRoyalRoadIncrEval.h>
//-----------------------------------------------------------------------------
// neighborhood description
#include <neighborhood/moRndWithoutReplNeighborhood.h> // visit one random neighbor possibly the same one several times
//-----------------------------------------------------------------------------
// the sampling class
#include <utils/eoDistance.h>
#include <sampling/moNeutralWalkSampling.h>
// Declaration of types
//-----------------------------------------------------------------------------
// Indi is the typedef of the solution type like in paradisEO-eo
typedef eoBit<unsigned int> Indi; // bit string with unsigned fitness type
// Neighbor is the typedef of the neighbor type,
// Neighbor = How to compute the neighbor from the solution + information on it (i.e. fitness)
// all classes from paradisEO-mo use this template type
typedef moBitNeighbor<unsigned int> Neighbor ; // bit string neighbor with unsigned fitness type
void main_function(int argc, char **argv)
{
/* =========================================================
*
* Parameters
*
* ========================================================= */
// more information on the input parameters: see EO tutorial lesson 3
// but don't care at first it just read the parameters of the bit string size and the random seed.
// First define a parser from the command-line arguments
eoParser parser(argc, argv);
// For each parameter, define Parameter, read it through the parser,
// and assign the value to the variable
// random seed parameter
eoValueParam<uint32_t> seedParam(time(0), "seed", "Random number seed", 'S');
parser.processParam( seedParam );
unsigned seed = seedParam.value();
// length of the bit string
eoValueParam<unsigned int> vecSizeParam(20, "vecSize", "Genotype size", 'V');
parser.processParam( vecSizeParam, "Representation" );
unsigned vecSize = vecSizeParam.value();
// size of the block
eoValueParam<unsigned int> blockSizeParam(4, "blockSize", "Block size of the Royal Road", 'k');
parser.processParam( blockSizeParam, "Representation" );
unsigned blockSize = blockSizeParam.value();
// the number of steps of the random walk
eoValueParam<unsigned int> stepParam(100, "nbStep", "Number of steps of the random walk", 'n');
parser.processParam( stepParam, "Representation" );
unsigned nbStep = stepParam.value();
// the name of the output file
string str_out = "out.dat"; // default value
eoValueParam<string> outParam(str_out.c_str(), "out", "Output file of the sampling", 'o');
parser.processParam(outParam, "Persistence" );
// the name of the "status" file where all actual parameter values will be saved
string str_status = parser.ProgramName() + ".status"; // default value
eoValueParam<string> statusParam(str_status.c_str(), "status", "Status file");
parser.processParam( statusParam, "Persistence" );
// do the following AFTER ALL PARAMETERS HAVE BEEN PROCESSED
// i.e. in case you need parameters somewhere else, postpone these
if (parser.userNeedsHelp()) {
parser.printHelp(cout);
exit(1);
}
if (statusParam.value() != "") {
ofstream os(statusParam.value().c_str());
os << parser;// and you can use that file as parameter file
}
/* =========================================================
*
* Random seed
*
* ========================================================= */
// reproducible random seed: if you don't change SEED above,
// you'll aways get the same result, NOT a random run
// more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
rng.reseed(seed);
/* =========================================================
*
* Eval fitness function (full evaluation)
*
* ========================================================= */
// the fitness function is the royal function (oneMax is a Royal Road with block of 1)
RoyalRoadEval<Indi> fullEval(blockSize);
/* =========================================================
*
* evaluation of a neighbor solution
*
* ========================================================= */
// Incremental evaluation of the neighbor: fitness is modified by +1 , 0 or -1
moRoyalRoadIncrEval<Neighbor> neighborEval(fullEval);
/* =========================================================
*
* the neighborhood of a solution
*
* ========================================================= */
// Exploration of the neighborhood in random order
// at each step one bit is randomly generated
moRndWithoutReplNeighborhood<Neighbor> neighborhood(vecSize);
/* =========================================================
*
* The sampling of the search space
*
* ========================================================= */
// Initial Solution of the random neutral walk
Indi initialSol(vecSize, false);
// Hamming distance
eoHammingDistance<Indi> distance;
// sampling object :
// - random initialization
// - neighborhood to compute the next step
// - fitness function
// - neighbor evaluation
// - number of steps of the walk
moNeutralWalkSampling<Neighbor> sampling(initialSol, neighborhood, fullEval, neighborEval, distance, nbStep);
/* =========================================================
*
* execute the sampling
*
* ========================================================= */
// nearly 2 blocks are complete
for(unsigned i = 0; i < blockSize - 1; i++) {
initialSol[i] = true;
initialSol[blockSize + i] = true;
initialSol[2 * blockSize + i] = true;
}
// first block is complete
initialSol[blockSize - 1] = true;
fullEval(initialSol);
std::cout << "Initial Solution: " << initialSol << std::endl;
// the sampling
sampling();
/* =========================================================
*
* export the sampling
*
* ========================================================= */
// to export the statistics into file
sampling.fileExport(str_out);
// to get the values of statistics
// so, you can compute some statistics in c++ from the data
const std::vector<Indi> & solutions = sampling.getSolutions(0);
std::cout << "First values:" << std::endl;
std::cout << "Solution " << solutions[0] << std::endl;
std::cout << "Last values:" << std::endl;
std::cout << "Solution " << solutions[solutions.size() - 1] << std::endl;
}
// A main that catches the exceptions
int main(int argc, char **argv)
{
try {
main_function(argc, argv);
}
catch (exception& e) {
cout << "Exception: " << e.what() << '\n';
}
return 1;
}