From d05c43ea3a0ed9542227c8a5479f4594df2833d7 Mon Sep 17 00:00:00 2001 From: verel Date: Tue, 4 May 2010 14:45:18 +0000 Subject: [PATCH] Add moRandomWalk.h, update lesson 6 sampling.cpp git-svn-id: svn://scm.gforge.inria.fr/svnroot/paradiseo@1775 331e1502-861f-0410-8da2-ba01fb791d7f --- trunk/paradiseo-mo/src/algo/moRandomWalk.h | 86 +++++ .../src/explorer/moRandomWalkExplorer.h | 1 + trunk/paradiseo-mo/src/mo.h | 1 + trunk/paradiseo-mo/src/sampling/moSampling.h | 16 +- .../tutorial/Lesson6/sampling.cpp | 321 ++++++++++-------- 5 files changed, 280 insertions(+), 145 deletions(-) create mode 100644 trunk/paradiseo-mo/src/algo/moRandomWalk.h diff --git a/trunk/paradiseo-mo/src/algo/moRandomWalk.h b/trunk/paradiseo-mo/src/algo/moRandomWalk.h new file mode 100644 index 000000000..e1b93c699 --- /dev/null +++ b/trunk/paradiseo-mo/src/algo/moRandomWalk.h @@ -0,0 +1,86 @@ +/* + +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 _moRandomWalk_h +#define _moRandomWalk_h + +#include +#include +#include +#include +#include + +/******************************************************** + * Random Walk: + * Random walk local search + * + * At each iteration, + * one random neighbor is selected and replace the current solution + * the algorithm stops when the number of steps is reached + ********************************************************/ +template +class moRandomWalk: public moLocalSearch +{ +public: + typedef typename Neighbor::EOT EOT; + typedef moNeighborhood Neighborhood ; + + /** + * Simple constructor for a random walk + * @param _neighborhood the neighborhood + * @param _fullEval the full evaluation function + * @param _eval neighbor's evaluation function + * @param _nbStepMax number of step of the walk + */ + moRandomWalk(Neighborhood& _neighborhood, eoEvalFunc& _fullEval, moEval& _eval, unsigned _nbStepMax): + moLocalSearch(explorer, trueCont, _fullEval), + explorer(_neighborhood, _eval, _nbStepMax) + {} + + /** + * Simple constructor for a random walk + * @param _neighborhood the neighborhood + * @param _fullEval the full evaluation function + * @param _eval neighbor's evaluation function + * @param _nbStepMax number of step of the walk + * @param _cont an external continuator + */ + moRandomWalk(Neighborhood& _neighborhood, eoEvalFunc& _fullEval, moEval& _eval, unsigned _nbStepMax, moContinuator& _cont): + moLocalSearch(explorer, _cont, _fullEval), + explorer(_neighborhood, _eval, _nbStepMax) + {} + +private: + // always true continuator + moTrueContinuator trueCont; + // the explorer of the random walk + moRandomWalkExplorer explorer; +}; + +#endif diff --git a/trunk/paradiseo-mo/src/explorer/moRandomWalkExplorer.h b/trunk/paradiseo-mo/src/explorer/moRandomWalkExplorer.h index 41a6e724c..f008751d0 100644 --- a/trunk/paradiseo-mo/src/explorer/moRandomWalkExplorer.h +++ b/trunk/paradiseo-mo/src/explorer/moRandomWalkExplorer.h @@ -98,6 +98,7 @@ public: /** * 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) { diff --git a/trunk/paradiseo-mo/src/mo.h b/trunk/paradiseo-mo/src/mo.h index ed732c1f2..c92e033b3 100755 --- a/trunk/paradiseo-mo/src/mo.h +++ b/trunk/paradiseo-mo/src/mo.h @@ -41,6 +41,7 @@ #include #include #include +#include #include #include diff --git a/trunk/paradiseo-mo/src/sampling/moSampling.h b/trunk/paradiseo-mo/src/sampling/moSampling.h index b2ff3cd91..2e9c70174 100644 --- a/trunk/paradiseo-mo/src/sampling/moSampling.h +++ b/trunk/paradiseo-mo/src/sampling/moSampling.h @@ -93,6 +93,7 @@ public: /** * To sample the search and get the statistics + * the statistics are stored in the moVectorMonitor vector */ void operator()(void) { // clear all statisic vectors @@ -111,14 +112,16 @@ public: // compute the sampling localSearch(solution); - // set to initial continuator + // set back to initial continuator localSearch.setContinuator(*continuator); } /** * to export the vector of values into one file + * @param _filename file name + * @param _delim delimiter between statistics */ - void exportFile(std::string _filename, std::string _delim = " ") { + void fileExport(std::string _filename, std::string _delim = " ") { // create file ofstream os(_filename.c_str()); @@ -145,6 +148,15 @@ public: } + /** + * to get one vector of values + * @param _numStat number of stattistics to get (in order of creation) + * @return the vector of value (all values are converted in double) + */ + const std::vector & getVector(unsigned int _numStat) { + return monitorVec[_numStat]->getVector(); + } + /** * @return name of the class */ diff --git a/trunk/paradiseo-mo/tutorial/Lesson6/sampling.cpp b/trunk/paradiseo-mo/tutorial/Lesson6/sampling.cpp index b0255d5a8..3c581a8dc 100644 --- a/trunk/paradiseo-mo/tutorial/Lesson6/sampling.cpp +++ b/trunk/paradiseo-mo/tutorial/Lesson6/sampling.cpp @@ -11,193 +11,228 @@ #include // runtime_error #include // cout -#include // ostrstream, istrstream +#include // ostrstream, istrstream #include #include // the general include for eo #include -#include +// declaration of the namespace using namespace std; //----------------------------------------------------------------------------- -// fitness function -#include -#include -#include -#include +// 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 #include -#include -#include -#include -#include -#include + +//----------------------------------------------------------------------------- +// neighborhood description +#include // visit one random neighbor possibly the same one several times + +//----------------------------------------------------------------------------- +// the random walk local search: heuristic to sample the search space +#include + +//----------------------------------------------------------------------------- +// the statistics to compute during the sampling #include -#include #include #include -#include -#include - +//----------------------------------------------------------------------------- +// the sampling class #include -// REPRESENTATION + +// Declaration of types //----------------------------------------------------------------------------- -typedef eoBit Indi; -typedef moBitNeighbor Neighbor ; // incremental evaluation -typedef moRndWithReplNeighborhood Neighborhood ; +// 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 - * - * ========================================================= */ + /* ========================================================= + * + * 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); + // 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 - // 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 steps of the random walk + eoValueParam 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 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 + } - eoValueParam seedParam(time(0), "seed", "Random number seed", 'S'); - parser.processParam( seedParam ); - unsigned seed = seedParam.value(); + /* ========================================================= + * + * Random seed + * + * ========================================================= */ - // description of genotype - eoValueParam vecSizeParam(8, "vecSize", "Genotype size", 'V'); - parser.processParam( vecSizeParam, "Representation" ); - unsigned vecSize = vecSizeParam.value(); + // 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); - eoValueParam stepParam(10, "nbStep", "Number of steps of the random walk", 'n'); - parser.processParam( stepParam, "Representation" ); - unsigned nbStep = stepParam.value(); + /* ========================================================= + * + * Initialization of the solution + * + * ========================================================= */ - // 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" ); + // a Indi random initializer: each bit is random + // more information: see EO tutorial lesson 1 (FirstBitGA.cpp) + eoUniformGenerator uGen; + eoInitFixedLength random(vecSize, uGen); - // 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" ); + /* ========================================================= + * + * Eval fitness function (full evaluation) + * + * ========================================================= */ - // 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 - } + // the fitness function is just the number of 1 in the bit string + oneMaxEval fullEval; - /* ========================================================= - * - * Random seed - * - * ========================================================= */ + /* ========================================================= + * + * evaluation of a neighbor solution + * + * ========================================================= */ - //reproducible random seed: if you don't change SEED above, - // you'll aways get the same result, NOT a random run - rng.reseed(seed); + // Use it if there is no incremental evaluation: a neighbor is evaluated by the full evaluation of a solution + // moFullEvalByModif neighborEval(fullEval); + // Incremental evaluation of the neighbor: fitness is modified by +/- 1 + moOneMaxIncrEval neighborEval; - /* ========================================================= - * - * Eval fitness function - * - * ========================================================= */ + /* ========================================================= + * + * the neighborhood of a solution + * + * ========================================================= */ - oneMaxEval eval; + // Exploration of the neighborhood in random order + // at each step one bit is randomly generated + moRndWithReplNeighborhood neighborhood(vecSize); + /* ========================================================= + * + * the local search algorithm to sample the search space + * + * ========================================================= */ - /* ========================================================= - * - * Initilisation of the solution - * - * ========================================================= */ + moRandomWalk walk(neighborhood, fullEval, neighborEval, nbStep); - // a Indi random initializer - eoUniformGenerator uGen; - eoInitFixedLength random(vecSize, uGen); + /* ========================================================= + * + * the statistics to compute + * + * ========================================================= */ + + // fitness of the solution at each step + moFitnessStat fStat; + // Hamming distance to the global optimum + eoHammingDistance distance; // Hamming distance + Indi bestSolution(vecSize, true); // global optimum - /* ========================================================= - * - * evaluation of a neighbor solution - * - * ========================================================= */ + moDistanceStat distStat(distance, bestSolution); // statistic - moFullEvalByModif nhEval(eval); + /* ========================================================= + * + * The sampling of the search space + * + * ========================================================= */ + + // sampling object : + // - random initialization + // - local search to sample the search space + // - one statistic to compute + moSampling sampling(random, walk, fStat); + + // to add another statistics + sampling.add(distStat); - //An eval by copy can be used instead of the eval by modif - //moFullEvalByCopy nhEval(eval); + /* ========================================================= + * + * 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.getVector(0); + const std::vector & distValues = sampling.getVector(1); - /* ========================================================= - * - * the neighborhood of a solution - * - * ========================================================= */ - - Neighborhood neighborhood(vecSize); - - - /* ========================================================= - * - * a neighborhood explorer solution - * - * ========================================================= */ - - moRandomWalkExplorer explorer(neighborhood, nhEval, nbStep); - - - /* ========================================================= - * - * the continuator and the checkpoint - * - * ========================================================= */ - - moTrueContinuator continuator;//always continue - - moFitnessStat fStat; - eoHammingDistance distance; - Indi bestSolution(vecSize, true); - moDistanceStat distStat(distance, bestSolution); - - /* ========================================================= - * - * the local search algorithm - * - * ========================================================= */ - - moLocalSearch localSearch(explorer, continuator, eval); - - /* ========================================================= - * - * The sampling of the search space - * - * ========================================================= */ - - moSampling sampling(random, localSearch, fStat); - - /* ========================================================= - * - * execute the sampling - * - * ========================================================= */ - - sampling(); - - sampling.exportFile(str_out); + std::cout << "First values:" << std::endl; + std::cout << "Fitness " << fitnessValues[0] << std::endl; + std::cout << "Distance " << distValues[0] << std::endl << std::endl; + std::cout << "Last values:" << std::endl; + std::cout << "Fitness " << fitnessValues[fitnessValues.size() - 1] << std::endl; + std::cout << "Distance " << distValues[distValues.size() - 1] << std::endl; } // A main that catches the exceptions