Migration from SVN
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137
eo/tutorial/Lesson4/ESEA.cpp
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137
eo/tutorial/Lesson4/ESEA.cpp
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// Program to test several EO-ES features
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#ifdef _MSC_VER
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#pragma warning(disable:4786)
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#endif
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#include <algorithm>
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#include <string>
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#include <iostream>
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#include <iterator>
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#include <stdexcept>
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#include <time.h>
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using namespace std;
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#include <eo>
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// representation specific
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#include <es/make_es.h>
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#include "real_value.h" // the sphere fitness
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// Now the main
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///////////////
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typedef eoMinimizingFitness FitT;
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template <class EOT>
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void runAlgorithm(EOT, eoParser& _parser, eoState& _state);
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int main_function(int argc, char *argv[])
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{
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// Create the command-line parser
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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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eoValueParam<bool>& simpleParam = parser.createParam(true, "Isotropic", "Isotropic self-adaptive mutation", 'i', "ES mutation");
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eoValueParam<bool>& stdevsParam = parser.createParam(false, "Stdev", "One self-adaptive stDev per variable", 's', "ES mutation");
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eoValueParam<bool>& corrParam = parser.createParam(false, "Correl", "Use correlated mutations", 'c', "ES mutation");
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// Run the appropriate algorithm
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if (simpleParam.value() == false)
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{
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cout << "Using eoReal" << endl;
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runAlgorithm(eoReal<FitT>(), parser, state);
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}
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else if (stdevsParam.value() == false)
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{
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cout << "Using eoEsSimple" << endl;
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runAlgorithm(eoEsSimple<FitT>(), parser, state);
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}
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else if (corrParam.value() == false)
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{
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cout << "Using eoEsStdev" << endl;
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runAlgorithm(eoEsStdev<FitT>(), parser, state);
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}
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else
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{
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cout << "Using eoEsFull" << endl;
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runAlgorithm(eoEsFull<FitT>(), parser, state);
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}
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return 0;
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}
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// A main that catches the exceptions
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int main(int argc, char **argv)
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{
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try
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{
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main_function(argc, argv);
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}
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catch(exception& e)
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{
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cout << "Exception: " << e.what() << '\n';
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}
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return 1;
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}
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/** The templatized main (sort of)
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* quite similar to the main of other genotypes
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* (e.g. t-eoReal and t-eoGA in test dir)
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*/
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template <class EOT>
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void runAlgorithm(EOT, eoParser& _parser, eoState& _state)
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{
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typedef typename EOT::Fitness FitT;
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///// FIRST, problem or representation dependent stuff
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//////////////////////////////////////////////////////
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// The evaluation fn - encapsulated into an eval counter for output
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eoEvalFuncPtr<EOT, double, const std::vector<double>&>
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mainEval( real_value );
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eoEvalFuncCounter<EOT> eval(mainEval);
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// the genotype - through a genotype initializer
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eoRealInitBounded<EOT>& init = make_genotype(_parser, _state, EOT());
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// Build the variation operator (any seq/prop construct)
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eoGenOp<EOT>& op = make_op(_parser, _state, init);
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//// Now the representation-independent things
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//////////////////////////////////////////////
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// initialize the population - and evaluate
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// yes, this is representation indepedent once you have an eoInit
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eoPop<EOT>& pop = make_pop(_parser, _state, init);
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apply<EOT>(eval, pop);
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// stopping criteria
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eoContinue<EOT> & term = make_continue(_parser, _state, eval);
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// output
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eoCheckPoint<EOT> & checkpoint = make_checkpoint(_parser, _state, eval, term);
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// algorithm (need the operator!)
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eoAlgo<EOT>& ga = make_algo_scalar(_parser, _state, eval, checkpoint, op);
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///// End of construction of the algorith
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/////////////////////////////////////////
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// to be called AFTER all parameters have been read!!!
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make_help(_parser);
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//// GO
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///////
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cout << "Initial Population\n";
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pop.sortedPrintOn(cout);
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cout << endl;
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run_ea(ga, pop); // run the ga
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cout << "Final Population\n";
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pop.sortedPrintOn(cout);
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cout << endl;
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}
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