geneticalgo.cpp

/********************************************************************************
 *  FARSA Genetic Algorithm Library                                             *
 *  Copyright (C) 2007-2009 Gianluca Massera <emmegian@yahoo.it>                *
 *                                                                              *
 *  This program is free software; you can redistribute it and/or modify        *
 *  it under the terms of the GNU General Public License as published by        *
 *  the Free Software Foundation; either version 2 of the License, or           *
 *  (at your option) any later version.                                         *
 *                                                                              *
 *  This program is distributed in the hope that it will be useful,             *
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of              *
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               *
 *  GNU General Public License for more details.                                *
 *                                                                              *
 *  You should have received a copy of the GNU General Public License           *
 *  along with this program; if not, write to the Free Software                 *
 *  Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA  *
 ********************************************************************************/

#include "core/geneticalgo.h"
#include "core/genotype.h"
#include "core/genome.h"
#include <cmath>

namespace farsa {

GeneticAlgo::GeneticAlgo()
    : evolutionEnd(false),
      evaluationDone(false),
      genomev(NULL),
      generationv(0),
      numGens(0),
      bestfits(),
      avgfits(),
      meanHdists(),
      varHdists(),
      stdHdists() {
    /* nothing else to do */
}

GeneticAlgo::~GeneticAlgo() {
    delete genomev;
}

void GeneticAlgo::evolve( unsigned int generationToReach ) {
    while((!isEvolutionEnded()) &&
          ((generationv < generationToReach) || ((generationv == generationToReach) && (!evaluationDone)))) {
        gaStep();
    }
}

void GeneticAlgo::evolve( ) {
    while( !isEvolutionEnded() ) {
        gaStep();
    }
}

bool GeneticAlgo::isEvolutionEnded() {
    return evolutionEnd;
}

bool GeneticAlgo::isEvaluationDone() {
    return evaluationDone;
}

void GeneticAlgo::setGenome( Genome* gen ) {
    genomev = gen;
}

Genome* GeneticAlgo::genome() {
    return genomev;
}

const Genome* GeneticAlgo::genome() const {
    return genomev;
}

void GeneticAlgo::setGeneration( unsigned int gen ) {
    generationv = gen;
/*  The vectors will be resized when updateStats() will be called
    bestfits.resize( gen );
    avgfits.resize( gen );
    meanHdists.resize( gen );
    varHdists.resize( gen );
    stdHdists.resize( gen );*/
}

unsigned int GeneticAlgo::generation() const {
    return generationv;
}

void GeneticAlgo::setNumGenerations( int g ) {
    numGens = g;
}

int GeneticAlgo::numGenerations() {
    return numGens;
}

QVector< QVector<double> > GeneticAlgo::bestFits() const {
    return bestfits;
}

QVector< QVector<double> > GeneticAlgo::averageFits() const {
    return avgfits;
}

QVector<double> GeneticAlgo::meanHammingDist() const {
    return meanHdists;
}

QVector<double> GeneticAlgo::varianceHammingDist() const {
    return varHdists;
}

QVector<double> GeneticAlgo::standardDeviationHammingDist() const {
    return stdHdists;
}

void GeneticAlgo::updateStats() {
    // check if it is necessary to grow-up vectors
    bestfits.resize( generationv+1 );
    avgfits.resize( generationv+1 );
    meanHdists.resize( generationv+1 );
    varHdists.resize( generationv+1 );
    stdHdists.resize( generationv+1 );
    // Calculate statistic data for this generation
    QVector<double> bests;
    QVector<double> avegs;
    int numObjs = genomev->at(0)->numOfObjectives();
    bests.resize( numObjs );
    avegs.resize( numObjs );
    for( int i=0; i<numObjs; i++ ) {
        bests[i] = genomev->at(0)->objective(i);
        avegs[i] = bests[i];
    }
    for( unsigned int g=1; g<genomev->size(); g++ ) {
        for( int i=0; i<numObjs; i++ ) {
            bests[i] = qMax( bests[i], genomev->at(g)->objective(i) );
            avegs[i] += genomev->at(g)->objective(i);
        }
    }
    for( int i=0; i<numObjs; i++ ) {
        avegs[i] = avegs[i]/(genomev->size());
    }
    bestfits[generationv] = bests;
    avgfits[generationv] = avegs;
/* *****
    double meanH = 0;
    double varH = 0;
    // ****** Devo fare per forza O(n^2) calcoli ?!?!?
    Genome& genomeref = *genomev;
    unsigned int dim = genomeref.size();
    for( unsigned int i=0; i<dim; i++ ) {
        for( unsigned int j=0; j<dim; j++ ) {
            meanH += genomeref[i]->hammingDistance( genomeref[j] );
        }
    }
    meanH /= dim*dim;
    for( unsigned int i=0; i<dim; i++ ) {
        for( unsigned int j=0; j<dim; j++ ) {
            varH += pow( genomeref[i]->hammingDistance( genomeref[j] ) - meanH, 2 );
        }
    }
    varH /= (dim*dim)-1;
    //--- set data
    meanHdists[generationv] = meanH;
    varHdists[generationv] = varH;
    stdHdists[generationv] = sqrt( varH );
***** */
}

} // end namespace farsa