diff --git a/trunk/paradiseo-mo/src/continuator/moNeighborFitnessStat.h b/trunk/paradiseo-mo/src/continuator/moNeighborFitnessStat.h new file mode 100644 index 000000000..9d515299d --- /dev/null +++ b/trunk/paradiseo-mo/src/continuator/moNeighborFitnessStat.h @@ -0,0 +1,113 @@ +/* + + 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 moNeighborFitnessStat_h +#define moNeighborFitnessStat_h + +#include +#include +#include + +/** + * Compute the fitness of one random neighbor + */ +template< class Neighbor > +class moNeighborFitnessStat : public moStat +{ +public : + typedef typename Neighbor::EOT EOT ; + typedef moNeighborhood Neighborhood ; + typedef typename EOT::Fitness Fitness ; + + using moStat< EOT, Fitness >::value; + + /** + * Default Constructor + * @param _neighborhood a neighborhood + * @param _eval an evaluation function + */ + moNeighborFitnessStat(Neighborhood& _neighborhood, moEval& _eval): + moStat(Fitness(), "neighborhood"), + neighborhood(_neighborhood), eval(_eval) + { + if (!neighborhood.isRandom()) { + std::cout << "moNeighborFitnessStat::Warning -> the neighborhood used is not random, the neighbor will not be random" << std::endl; + } + } + + /** + * Compute the fitness of one random neighbor + * @param _solution the first solution + */ + virtual void init(EOT & _solution) { + operator()(_solution); + } + + /** + * Compute the fitness of one random neighbor + * @param _solution the corresponding solution + */ + virtual void operator()(EOT & _solution) { + if (neighborhood.hasNeighbor(_solution)) { + Neighbor current ; + + //init the first neighbor which is suppoed to be random + neighborhood.init(_solution, current); + + //eval the _solution moved with the neighbor and stock the result in the neighbor + eval(_solution, current); + + // the fitness value is collected + value() = current.fitness(); + } else { + //if _solution hasn't neighbor, + value() = Fitness(); + } + } + + /** + * @return the class name + */ + virtual std::string className(void) const { + return "moNeighborFitnessStat"; + } + +private: + // to explore the neighborhood + Neighborhood& neighborhood ; + moEval& eval; + +}; + +#endif diff --git a/trunk/paradiseo-mo/src/mo.h b/trunk/paradiseo-mo/src/mo.h index dcc2ca12f..dba7ec24f 100755 --- a/trunk/paradiseo-mo/src/mo.h +++ b/trunk/paradiseo-mo/src/mo.h @@ -56,6 +56,7 @@ #include #include #include +#include #include #include #include @@ -142,6 +143,7 @@ #include #include #include +#include #include #include diff --git a/trunk/paradiseo-mo/src/sampling/moNeutralDegreeSampling.h b/trunk/paradiseo-mo/src/sampling/moNeutralDegreeSampling.h index 6ea7d4ab0..7b08da84c 100644 --- a/trunk/paradiseo-mo/src/sampling/moNeutralDegreeSampling.h +++ b/trunk/paradiseo-mo/src/sampling/moNeutralDegreeSampling.h @@ -46,9 +46,10 @@ #include /** - * To compute the density of states: - * Sample the fitness of random solution in the search space - * The fitness values of solutions are collected during the random search + * To compute the neutral degree: + * Sample the fitness of random solution in the search space (1er information) + * and sample the neutral degree (2nd information), i.e. the number of neighbor solutions with the same fitness value + * The values are collected during the random search * */ template diff --git a/trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt b/trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt index 7dde0b881..91e3d33d6 100644 --- a/trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt +++ b/trunk/paradiseo-mo/tutorial/Lesson6/CMakeLists.txt @@ -15,6 +15,7 @@ ADD_EXECUTABLE(autocorrelation autocorrelation.cpp) ADD_EXECUTABLE(adaptiveWalks adaptiveWalks.cpp) ADD_EXECUTABLE(fdc fdc.cpp) ADD_EXECUTABLE(neutralDegree neutralDegree.cpp) +ADD_EXECUTABLE(fitnessCloud fitnessCloud.cpp) TARGET_LINK_LIBRARIES(testRandomWalk eoutils ga eo) TARGET_LINK_LIBRARIES(testMetropolisHasting eoutils ga eo) @@ -25,3 +26,4 @@ TARGET_LINK_LIBRARIES(autocorrelation eoutils ga eo) 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) diff --git a/trunk/paradiseo-mo/tutorial/Lesson6/autocorrelation.cpp b/trunk/paradiseo-mo/tutorial/Lesson6/autocorrelation.cpp index 42cca81e2..9b2c63d2a 100644 --- a/trunk/paradiseo-mo/tutorial/Lesson6/autocorrelation.cpp +++ b/trunk/paradiseo-mo/tutorial/Lesson6/autocorrelation.cpp @@ -163,8 +163,10 @@ void main_function(int argc, char **argv) // sampling object : // - random initialization - // - local search to sample the search space - // - one statistic to compute + // - neighborhood to compute the next step + // - fitness function + // - neighbor evaluation + // - number of steps of the walk moAutocorrelationSampling sampling(random, neighborhood, fullEval, neighborEval, nbStep); /* ========================================================= diff --git a/trunk/paradiseo-mo/tutorial/Lesson6/fitnessCloud.cpp b/trunk/paradiseo-mo/tutorial/Lesson6/fitnessCloud.cpp new file mode 100644 index 000000000..eeed37b4f --- /dev/null +++ b/trunk/paradiseo-mo/tutorial/Lesson6/fitnessCloud.cpp @@ -0,0 +1,210 @@ +//----------------------------------------------------------------------------- +/** fitnessCloud.cpp + * + * SV - 06/05/10 + * + */ +//----------------------------------------------------------------------------- + +// standard includes +#define HAVE_SSTREAM + +#include // runtime_error +#include // cout +#include // ostrstream, istrstream +#include +#include + +// the general include for eo +#include + +// declaration of the namespace +using namespace std; + +//----------------------------------------------------------------------------- +// representation of solutions, and neighbors +#include // bit string : see also EO tutorial lesson 1: FirstBitGA.cpp +#include // neighbor of bit string + +//----------------------------------------------------------------------------- +// fitness function, and evaluation of neighbors +#include +#include + +//----------------------------------------------------------------------------- +// neighborhood description +#include // visit one random neighbor possibly the same one several times + +//----------------------------------------------------------------------------- +// the sampling class +#include + +// Declaration of types +//----------------------------------------------------------------------------- +// Indi is the typedef of the solution type like in paradisEO-eo +typedef eoBit 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 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 seedParam(time(0), "seed", "Random number seed", 'S'); + parser.processParam( seedParam ); + unsigned seed = seedParam.value(); + + // length of the bit string + eoValueParam vecSizeParam(20, "vecSize", "Genotype size", 'V'); + parser.processParam( vecSizeParam, "Representation" ); + unsigned vecSize = vecSizeParam.value(); + + // the number of solution sampled + eoValueParam 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 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 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 uGen; + eoInitFixedLength random(vecSize, uGen); + + /* ========================================================= + * + * Eval fitness function (full evaluation) + * + * ========================================================= */ + + // the fitness function is just the number of 1 in the bit string + oneMaxEval fullEval; + + /* ========================================================= + * + * evaluation of a neighbor solution + * + * ========================================================= */ + + // Incremental evaluation of the neighbor: fitness is modified by +/- 1 + moOneMaxIncrEval neighborEval; + + /* ========================================================= + * + * the neighborhood of a solution + * + * ========================================================= */ + + // Exploration of the neighborhood in random order + // at each step one bit is randomly generated + moRndWithReplNeighborhood neighborhood(vecSize); + + /* ========================================================= + * + * The sampling of the search space + * + * ========================================================= */ + + // sampling object : + // - random initialization + // - neighborhood to compute one random neighbor + // - fitness function + // - neighbor evaluation + // - number of solutions to sample + moFitnessCloudSampling sampling(random, neighborhood, fullEval, neighborEval, 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 & fitnessValues = sampling.getValues(0); + const std::vector & neighborFitnessValues = sampling.getValues(1); + + std::cout << "First values:" << std::endl; + std::cout << "Fitness " << fitnessValues[0] << std::endl; + std::cout << "Neighbor Fitness " << neighborFitnessValues[0] << std::endl; + + std::cout << "Last values:" << std::endl; + std::cout << "Fitness " << fitnessValues[fitnessValues.size() - 1] << std::endl; + std::cout << "Neighbor Fitness " << neighborFitnessValues[neighborFitnessValues.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; +}