287 lines
10 KiB
C++
287 lines
10 KiB
C++
#include <eo>
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#include <mo>
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#include <utils/eoLogger.h>
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#include <utils/eoParserLogger.h>
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#include <eoEvalFuncCounterBounder.h>
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#include <do/make_pop.h>
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#include <do/make_run.h>
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#include <do/make_continue.h>
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#include <do/make_checkpoint.h>
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#include <edo>
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#include "Rosenbrock.h"
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#include "Sphere.h"
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typedef eoReal<eoMinimizingFitness> EOT;
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typedef edoNormalMulti< EOT > Distrib;
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int main(int ac, char** av)
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{
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eoParserLogger parser(ac, av);
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// Letters used by the following declarations:
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// a d i p t
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std::string section("Algorithm parameters");
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// FIXME: default value to check
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double initial_temperature = parser.createParam((double)10e5, "temperature", "Initial temperature", 'i', section).value(); // i
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eoState state;
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//-----------------------------------------------------------------------------
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// Instantiate all needed parameters for EDASA algorithm
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//-----------------------------------------------------------------------------
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double selection_rate = parser.createParam((double)0.5, "selection_rate", "Selection Rate", 'R', section).value(); // R
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eoSelect< EOT >* selector = new eoDetSelect< EOT >( selection_rate );
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state.storeFunctor(selector);
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edoEstimator< Distrib >* estimator = new edoEstimatorNormalMulti< EOT >();
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state.storeFunctor(estimator);
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eoSelectOne< EOT >* selectone = new eoDetTournamentSelect< EOT >( 2 );
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state.storeFunctor(selectone);
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edoModifierMass< Distrib >* modifier = new edoNormalMultiCenter< EOT >();
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state.storeFunctor(modifier);
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eoEvalFunc< EOT >* plainEval = new Rosenbrock< EOT >();
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state.storeFunctor(plainEval);
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unsigned long max_eval = parser.getORcreateParam((unsigned long)0, "maxEval", "Maximum number of evaluations (0 = none)", 'E', "Stopping criterion").value(); // E
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eoEvalFuncCounterBounder< EOT > eval(*plainEval, max_eval);
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eoRndGenerator< double >* gen = new eoUniformGenerator< double >(-5, 5);
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state.storeFunctor(gen);
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unsigned int dimension_size = parser.createParam((unsigned int)10, "dimension-size", "Dimension size", 'd', section).value(); // d
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eoInitFixedLength< EOT >* init = new eoInitFixedLength< EOT >( dimension_size, *gen );
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state.storeFunctor(init);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (1) Population init and sampler
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//-----------------------------------------------------------------------------
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// Generation of population from do_make_pop (creates parameters, manages persistance and so on...)
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// ... and creates the parameters: L P r S
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// this first sampler creates a uniform distribution independently from our distribution (it does not use doUniform).
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eoPop< EOT >& pop = do_make_pop(parser, state, *init);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// (2) First evaluation before starting the research algorithm
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//-----------------------------------------------------------------------------
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apply(eval, pop);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Prepare bounder class to set bounds of sampling.
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// This is used by doSampler.
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//-----------------------------------------------------------------------------
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edoBounder< EOT >* bounder = new edoBounderRng< EOT >(EOT(pop[0].size(), -5),
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EOT(pop[0].size(), 5),
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*gen);
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state.storeFunctor(bounder);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Prepare sampler class with a specific distribution
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//-----------------------------------------------------------------------------
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edoSampler< Distrib >* sampler = new edoSamplerNormalMulti< EOT >( *bounder );
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state.storeFunctor(sampler);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Metropolis sample parameters
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//-----------------------------------------------------------------------------
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unsigned int popSize = parser.getORcreateParam((unsigned int)20, "popSize", "Population Size", 'P', "Evolution Engine").value();
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moContinuator< moDummyNeighbor<EOT> >* sa_continue = new moIterContinuator< moDummyNeighbor<EOT> >( popSize );
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state.storeFunctor(sa_continue);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// SA parameters
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//-----------------------------------------------------------------------------
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double threshold_temperature = parser.createParam((double)0.1, "threshold", "Minimal temperature at which stop", 't', section).value(); // t
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double alpha = parser.createParam((double)0.1, "alpha", "Temperature decrease rate", 'a', section).value(); // a
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moCoolingSchedule<EOT>* cooling_schedule = new moSimpleCoolingSchedule<EOT>(initial_temperature, alpha, 0, threshold_temperature);
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state.storeFunctor(cooling_schedule);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// stopping criteria
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// ... and creates the parameter letters: C E g G s T
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//-----------------------------------------------------------------------------
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eoContinue< EOT >& eo_continue = do_make_continue(parser, state, eval);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// population output
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//-----------------------------------------------------------------------------
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eoCheckPoint< EOT >& pop_continue = do_make_checkpoint(parser, state, eval, eo_continue);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// distribution output
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//-----------------------------------------------------------------------------
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edoDummyContinue< Distrib >* dummy_continue = new edoDummyContinue< Distrib >();
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state.storeFunctor(dummy_continue);
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edoCheckPoint< Distrib >* distribution_continue = new edoCheckPoint< Distrib >( *dummy_continue );
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state.storeFunctor(distribution_continue);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// eoEPRemplacement causes the using of the current and previous
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// sample for sampling.
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//-----------------------------------------------------------------------------
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eoReplacement< EOT >* replacor = new eoEPReplacement< EOT >(pop.size());
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// Below, use eoGenerationalReplacement to sample only on the current sample
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//eoReplacement< EOT >* replacor = new eoGenerationalReplacement< EOT >(); // FIXME: to define the size
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state.storeFunctor(replacor);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Some stuff to display helper when we are using -h option
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//-----------------------------------------------------------------------------
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if (parser.userNeedsHelp())
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{
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parser.printHelp(std::cout);
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exit(1);
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}
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// Help + Verbose routines
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make_verbose(parser);
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make_help(parser);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// population output (after helper)
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//
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// FIXME: theses objects are instanciate there in order to avoid a folder
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// removing as edoFileSnapshot does within ctor.
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//-----------------------------------------------------------------------------
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edoPopStat< EOT >* popStat = new edoPopStat<EOT>;
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state.storeFunctor(popStat);
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pop_continue.add(*popStat);
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edoFileSnapshot* fileSnapshot = new edoFileSnapshot("EDASA_ResPop");
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state.storeFunctor(fileSnapshot);
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fileSnapshot->add(*popStat);
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pop_continue.add(*fileSnapshot);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// distribution output (after helper)
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//-----------------------------------------------------------------------------
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edoDistribStat< Distrib >* distrib_stat = new edoStatNormalMulti< EOT >();
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state.storeFunctor(distrib_stat);
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distribution_continue->add( *distrib_stat );
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// eoMonitor* stdout_monitor = new eoStdoutMonitor();
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// state.storeFunctor(stdout_monitor);
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// stdout_monitor->add(*distrib_stat);
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// distribution_continue->add( *stdout_monitor );
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eoFileMonitor* file_monitor = new eoFileMonitor("eda_sa_distribution_bounds.txt");
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state.storeFunctor(file_monitor);
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file_monitor->add(*distrib_stat);
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distribution_continue->add( *file_monitor );
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// EDASA algorithm configuration
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//-----------------------------------------------------------------------------
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edoAlgo< Distrib >* algo = new edoEDASA< Distrib >
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(*selector, *estimator, *selectone, *modifier, *sampler,
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pop_continue, *distribution_continue,
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eval, *sa_continue, *cooling_schedule,
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initial_temperature, *replacor);
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//-----------------------------------------------------------------------------
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//-----------------------------------------------------------------------------
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// Beginning of the algorithm call
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//-----------------------------------------------------------------------------
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try
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{
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do_run(*algo, pop);
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}
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catch (eoEvalFuncCounterBounderException& e)
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{
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eo::log << eo::warnings << "warning: " << e.what() << std::endl;
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}
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catch (std::exception& e)
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{
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eo::log << eo::errors << "error: " << e.what() << std::endl;
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exit(EXIT_FAILURE);
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}
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//-----------------------------------------------------------------------------
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return 0;
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}
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