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Ajout de la random search, et du DOS sampling

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git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1778 331e1502-861f-0410-8da2-ba01fb791d7f
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verel 2010-05-04 17:11:05 +00:00
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82
trunk/paradiseo-mo/src/algo/moRandomSearch.h Normal file
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/*
<moRandomSearch.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 _moRandomSearch_h
#define _moRandomSearch_h
#include <algo/moLocalSearch.h>
#include <explorer/moRandomSearchExplorer.h>
#include <continuator/moTrueContinuator.h>
#include <eoInit.h>
#include <eoEvalFunc.h>
/********************************************************
* Random Search:
* Pure random search local search
*
* At each iteration,
* one random solution is selected and replace the current solution
* the algorithm stops when the number of solution is reached
********************************************************/
template<class Neighbor>
class moRandomSearch: public moLocalSearch<Neighbor>
{
public:
typedef typename Neighbor::EOT EOT;
/**
* Simple constructor for a random search
* @param _init the solution initializer, to explore at random the search space
* @param _fullEval the full evaluation function
* @param _nbSolMax number of solutions
*/
moRandomSearch(eoInit<EOT> & _init, eoEvalFunc<EOT>& _fullEval, unsigned _nbSolMax):
moLocalSearch<Neighbor>(explorer, trueCont, _fullEval),
explorer(_init, _fullEval, _nbSolMax)
{}
/**
* Simple constructor for a random search
* @param _init the solution initializer, to explore at random the search space
* @param _fullEval the full evaluation function
* @param _nbSolMax number of solutions
*/
moRandomSearch(eoInit<EOT> & _init, eoEvalFunc<EOT>& _fullEval, unsigned _nbSolMax, moContinuator<Neighbor>& _cont):
moLocalSearch<Neighbor>(explorer, _cont, _fullEval),
explorer(_init, _fullEval, _nbSolMax)
{}
private:
// always true continuator
moTrueContinuator<Neighbor> trueCont;
// the explorer of the random walk
moRandomSearchExplorer<Neighbor> explorer;
};
#endif

147
trunk/paradiseo-mo/src/explorer/moRandomSearchExplorer.h Normal file
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/*
<moRandomSearchExplorer.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 _moRandomSearchexplorer_h
#define _moRandomSearchexplorer_h
#include <explorer/moNeighborhoodExplorer.h>
#include <neighborhood/moNeighborhood.h>
#include <eoEvalFunc.h>
#include <eoInit.h>
/**
* Explorer for a pure random search:
* the solution is initialized at each step
*/
template< class Neighbor >
class moRandomSearchExplorer : public moNeighborhoodExplorer<Neighbor>
{
public:
typedef typename Neighbor::EOT EOT ;
typedef moNeighborhood<Neighbor> Neighborhood ;
using moNeighborhoodExplorer<Neighbor>::neighborhood;
using moNeighborhoodExplorer<Neighbor>::eval;
/**
* Constructor
* @param _init the solution initializer, to explore at random the search space
* @param _eval the evaluation function
* @param _nbStep maximum number of step to do
*/
moRandomSearchExplorer(eoInit<EOT>& _init, eoEvalFunc<EOT>& _fulleval, unsigned _nbStep) : moNeighborhoodExplorer<Neighbor>(), init(_init), fulleval(_fulleval), nbStep(_nbStep) {
// number of step done
step = 0;
}
/**
* Destructor
*/
~moRandomSearchExplorer() {
}
/**
* initialization of the number of step to be done
*/
virtual void initParam(EOT & solution) {
step = 0;
};
/**
* increase the number of step
*/
virtual void updateParam(EOT & solution) {
step++;
};
/**
* terminate: NOTHING TO DO
*/
virtual void terminate(EOT & solution) {};
/**
* Explore the neighborhood with only one random solution
* we supposed that the first neighbor is uniformly selected in the neighborhood
* @param _solution
*/
virtual void operator()(EOT & _solution) {
//init the first neighbor
init(_solution);
//eval the _solution moved with the neighbor and stock the result in the neighbor
fulleval(_solution);
};
/**
* continue if it is remainds some steps to do
* @param _solution the solution
* @return true there is some steps to do
*/
virtual bool isContinue(EOT & _solution) {
return (step < nbStep) ;
};
/**
* move the solution with the best neighbor
* @param _solution the solution to move
*/
virtual void move(EOT & _solution) {
// the solution is already move. So nothing to do !
};
/**
* accept test : always accept
* @param _solution the solution
* @return true if the best neighbor ameliorate the fitness
*/
virtual bool accept(EOT & _solution) {
return true;
};
private:
// initialization method to explore at random the search space
eoInit<EOT> & init;
// the full eval function
eoEvalFunc<EOT> & fulleval;
// current number of step
unsigned int step;
// maximum number of steps to do
unsigned int nbStep;
};
#endif

3
trunk/paradiseo-mo/src/mo.h
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@ -36,6 +36,7 @@
#define _newmo_h
#include <algo/moLocalSearch.h>
#include <algo/moRandomSearch.h>
#include <algo/moSA.h>
#include <algo/moSimpleHC.h>
#include <algo/moFirstImprHC.h>
@ -85,6 +86,7 @@
#include <explorer/moNeutralHCexplorer.h>
#include <explorer/moMetropolisHastingExplorer.h>
#include <explorer/moNeighborhoodExplorer.h>
#include <explorer/moRandomSearchExplorer.h>
#include <explorer/moRandomNeutralWalkExplorer.h>
#include <explorer/moRandomWalkExplorer.h>
#include <explorer/moSimpleHCexplorer.h>
@ -132,6 +134,7 @@
#include <coolingSchedule/moSimpleCoolingSchedule.h>
#include <sampling/moSampling.h>
#include <sampling/moDensityOfStatesSampling.h>
#include <sampling/moAutocorrelationSampling.h>
#include <problems/bitString/moBitNeighbor.h>

87
trunk/paradiseo-mo/src/sampling/moDensityOfStatesSampling.h Normal file
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/*
<moDensityOfStatesSampling.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 moDensityOfStatesSampling_h
#define moDensityOfStatesSampling_h
#include <eoInit.h>
#include <eval/moEval.h>
#include <eoEvalFunc.h>
#include <algo/moRandomSearch.h>
#include <continuator/moFitnessStat.h>
#include <sampling/moSampling.h>
/**
* To compute the autocorrelation function:
* Perform a random walk based on the neighborhood,
* The fitness values of solutions are collected during the random walk
* The autocorrelation can be computed from the serie of fitness values
*
*/
template <class Neighbor>
class moDensityOfStatesSampling : public moSampling<Neighbor>
{
public:
typedef typename Neighbor::EOT EOT ;
using moSampling<Neighbor>::localSearch;
/**
* Default Constructor
* @param _init initialisation method of the solution
* @param _neighborhood neighborhood giving neighbor in random order
* @param _nbStep Number of steps of the random walk
*/
moDensityOfStatesSampling(eoInit<EOT> & _init,
eoEvalFunc<EOT>& _fullEval,
unsigned int _nbSol) :
moSampling<Neighbor>(_init, * new moRandomSearch<Neighbor>(_init, _fullEval, _nbSol), fitnessStat)
{
}
/**
* default destructor
*/
~moDensityOfStatesSampling() {
// delete the pointer on the local search which has been constructed in the constructor
delete &localSearch;
}
protected:
moFitnessStat<EOT> fitnessStat;
};
#endif

4
trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt
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@ -10,10 +10,12 @@ ADD_EXECUTABLE(testRandomWalk testRandomWalk.cpp)
ADD_EXECUTABLE(testMetropolisHasting testMetropolisHasting.cpp)
ADD_EXECUTABLE(testRandomNeutralWalk testRandomNeutralWalk.cpp)
ADD_EXECUTABLE(sampling sampling.cpp)
ADD_EXECUTABLE(densityOfStates densityOfStates.cpp)
ADD_EXECUTABLE(autocorrelation autocorrelation.cpp)
TARGET_LINK_LIBRARIES(testRandomWalk eoutils ga eo)
TARGET_LINK_LIBRARIES(testMetropolisHasting eoutils ga eo)
TARGET_LINK_LIBRARIES(testRandomNeutralWalk eoutils ga eo)
TARGET_LINK_LIBRARIES(autocorrelation eoutils ga eo)
TARGET_LINK_LIBRARIES(sampling eoutils ga eo)
TARGET_LINK_LIBRARIES(densityOfStates eoutils ga eo)
TARGET_LINK_LIBRARIES(autocorrelation eoutils ga eo)

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trunk/paradiseo-mo/tutorial/Lesson6/densityOfStates.cpp Normal file
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//-----------------------------------------------------------------------------
/** densityOfStates.cpp
*
* SV - 03/05/10
*
*/
//-----------------------------------------------------------------------------
// 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/oneMaxEval.h>
//-----------------------------------------------------------------------------
// the sampling class
#include <sampling/moDensityOfStatesSampling.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();
// the number of steps of the random walk
eoValueParam<unsigned int> solParam(100, "nbSol", "Number of random solution", 'n');
parser.processParam( solParam, "Representation" );
unsigned nbSol = solParam.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);
/* =========================================================
*
* Initialization of the solution
*
* ========================================================= */
// a Indi random initializer: each bit is random
// more information: see EO tutorial lesson 1 (FirstBitGA.cpp)
eoUniformGenerator<bool> uGen;
eoInitFixedLength<Indi> random(vecSize, uGen);
/* =========================================================
*
* Eval fitness function (full evaluation)
*
* ========================================================= */
// the fitness function is just the number of 1 in the bit string
oneMaxEval<Indi> fullEval;
/* =========================================================
*
* The sampling of the search space
*
* ========================================================= */
// sampling object :
// - random initialization
// - local search to sample the search space
// - one statistic to compute
moDensityOfStatesSampling<Neighbor> sampling(random, fullEval, nbSol);
/* =========================================================
*
* execute 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<double> & fitnessValues = sampling.getVector(0);
std::cout << "First values:" << std::endl;
std::cout << "Fitness " << fitnessValues[0] << std::endl;
std::cout << "Last values:" << std::endl;
std::cout << "Fitness " << fitnessValues[fitnessValues.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;
}