170 lines
5.4 KiB
C++
170 lines
5.4 KiB
C++
// -*- mode: c++; c-indent-level: 4; c++-member-init-indent: 8; comment-column: 35; -*-
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//-----------------------------------------------------------------------------
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// t-eoFitnessAssembledEA.cpp
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// Marc Wintermantel & Oliver Koenig
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// IMES-ST@ETHZ.CH
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// March 2003
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/*
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This library is free software; you can redistribute it and/or
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modify it under the terms of the GNU Lesser General Public
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License as published by the Free Software Foundation; either
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version 2 of the License, or (at your option) any later version.
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This library is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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Lesser General Public License for more details.
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You should have received a copy of the GNU Lesser General Public
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License along with this library; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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Contact: todos@geneura.ugr.es, http://geneura.ugr.es
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Marc.Schoenauer@inria.fr
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mak@dhi.dk
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*/
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//-----------------------------------------------------------------------------
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#include <iostream>
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#include <cmath>
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// General eo includes
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#include <eo>
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#include <utils/eoRealVectorBounds.h> // The real bounds (not yet in general eo include)
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// Representation dependent includes and typedefs
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#include <es/eoReal.h> // Definition of representation
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#include <es/eoRealInitBounded.h> // Uniformly initializes real vector in bounds
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#include <es/make_genotype_real.h> // Initialization of a genotype
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#include <eoEvalFunc.h> // Base class for fitness evaluation
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#include <es/make_op_real.h> // Variation operators using standard Real operators
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#include <eoScalarFitnessAssembled.h> // The fitness class
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typedef eoReal<eoAssembledMinimizingFitness> Indi;
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// Representation independent modules
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#include <do/make_pop.h> // Initialization of population
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#include <do/make_continue.h> // The stopping criterion
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#include <do/make_checkpoint_assembled.h> // Outputs (stats, population dumps, ...)
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#include <do/make_algo_scalar.h> // Evolution engine (selection and replacement)
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#include <do/make_run.h> // simple call to the algo.stays there for consistency reasons
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// Define a fitness class
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template <class EOT>
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class eoAssembledEvalFunc : public eoEvalFunc<EOT>{
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public:
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// Constructor defining number and descriptions of fitness terms
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eoAssembledEvalFunc() {
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// Define a temporary fitness object to have access to its static traits
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typename EOT::Fitness tmpfit(3, 0.0);
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tmpfit.setDescription(0,"Fitness");
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tmpfit.setDescription(1,"Some Value");
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tmpfit.setDescription(2,"Other Value");
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}
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void operator()(EOT& _eo){
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// Define temporary fitness object
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// (automatically gets initialized with size given in constructor)
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typename EOT::Fitness tmpfit;
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// Eval some dummy fitness
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double sum1=0.0, sum2=0.0;
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for (unsigned i=0; i < _eo.size(); ++i){
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sum1 += _eo[i]*_eo[i];
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sum2 += fabs(_eo[i]) + fabs(_eo[i]);
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}
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// Store some fitness terms
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tmpfit[1]= sum1;
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tmpfit[2]= sum2;
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// Store the fitness
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tmpfit = (sum1 + sum2)/_eo.size();
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// Pass it
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_eo.fitness( tmpfit );
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}
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};
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// checks for help demand, and writes the status file and make_help; in libutils
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void make_help(eoParser & _parser);
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// now use all of the above, + representation dependent things
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int main(int argc, char* argv[]){
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std::cout << "-----------------------------------" << std::endl;
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std::cout << "START t-eoFitnessAssembledEA" << std::endl;
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try{
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// Parser & State
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eoParser parser(argc, argv); // for user-parameter reading
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eoState state; // keeps all things allocated
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////
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// A) Representation dependent stuff
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////
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// The fitness
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eoAssembledEvalFunc<Indi> plainEval;
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// turn that object into an evaluation counter
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eoEvalFuncCounter<Indi> eval(plainEval);
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// The genotype
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eoRealInitBounded<Indi>& init = do_make_genotype(parser, state, Indi() );
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// The variation operators
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eoGenOp<Indi>& op = do_make_op(parser, state, init);
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////
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// B) Create representation independent stuff
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////
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// initialize the population
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// yes, this is representation indepedent once you have an eoInit
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eoPop<Indi>& pop = do_make_pop(parser, state, init);
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// stopping criteria
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eoContinue<Indi> & term = do_make_continue(parser, state, eval);
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// output
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eoCheckPoint<Indi> & checkpoint = do_make_checkpoint_assembled(parser, state, eval, term);
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// algorithm (need the operator!)
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eoAlgo<Indi>& ga = do_make_algo_scalar(parser, state, eval, checkpoint, op);
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make_help(parser); // To be called after all parameters have been read !
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////
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// C) Run the algorithm
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////
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// evaluate intial population AFTER help and status in case it takes time
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apply<Indi>(eval, pop);
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// if you want to print it out
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std::cout << "Initial Population\n";
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pop.sortedPrintOn(std::cout);
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std::cout << std::endl;
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do_run(ga, pop); // run the ga
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std::cout << "Final Population\n";
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pop.sortedPrintOn(std::cout);
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std::cout << std::endl;
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}
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catch(std::exception& e)
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{
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std::cout << e.what() << std::endl;
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return 1;
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}
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std::cout << "-----------------------------------" << std::endl;
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std::cout << "END t-eoFitnessAssembledEA" << std::endl;
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return 0;
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}
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