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eodev/eo/test/t-eoESFull.cpp
2000-06-13 14:30:47 +00:00

150 lines
4.5 KiB
C++

// Program to test several EO-ES features
#ifdef _MSC_VER
#pragma warning(disable:4786)
#endif
#include <algorithm>
#include <string>
#include <iostream>
#include <iterator>
#include <stdexcept>
using namespace std;
#include <utils/eoParser.h>
#include <utils/eoState.h>
#include <utils/eoStat.h>
#include <utils/eoFileMonitor.h>
// population
#include <eoPop.h>
// evaluation specific
#include <eoEvalFuncPtr.h>
// representation specific
#include <es/evolution_strategies>
#include "real_value.h" // the sphere fitness
// Now the main
///////////////
typedef double FitT;
template <class EOT>
void runAlgorithm(EOT, eoParser& _parser, eoState& _state, eoEsObjectiveBounds& _bounds);
main(int argc, char *argv[])
{
// Create the command-line parser
eoParser parser( argc, argv, "Basic EA for vector<float> with adaptive mutations");
// Define Parameters and load them
eoValueParam<uint32>& seed = parser.createParam(static_cast<uint32>(time(0)), "seed", "Random number seed");
eoValueParam<string>& load_name = parser.createParam(string(), "Load","Load a state file",'L');
eoValueParam<string>& save_name = parser.createParam(string(), "Save","Saves a state file",'S');
eoValueParam<bool>& stdevs = parser.createParam(true, "Stdev", "Use adaptive mutation rates", 's');
eoValueParam<bool>& corr = parser.createParam(true, "Correl", "Use correlated mutations", 'c');
eoValueParam<unsigned>& chromSize = parser.createParam(unsigned(1), "ChromSize", "Number of chromosomes", 'n');
eoValueParam<double>& minimum = parser.createParam(-1.e5, "Min", "Minimum for Objective Variables", 'l');
eoValueParam<double>& maximum = parser.createParam(1.e5, "Max", "Maximum for Objective Variables", 'h');
eoState state;
state.registerObject(parser);
rng.reseed(seed.value());
if (!load_name.value().empty())
{ // load the parser. This is only neccessary when the user wants to
// be able to change the parameters in the state file by hand.
state.load(load_name.value()); // load the parser
}
state.registerObject(rng);
eoEsObjectiveBounds bounds(chromSize.value(), minimum.value(), maximum.value());
// Run the appropriate algorithm
if (stdevs.value() == false && corr.value() == false)
{
runAlgorithm(eoEsSimple<FitT>() ,parser, state, bounds);
}
else if (corr.value() == true)
{
runAlgorithm(eoEsFull<FitT>(),parser, state, bounds);
}
else
{
runAlgorithm(eoEsStdev<FitT>(), parser, state, bounds);
}
// and save
if (!save_name.value().empty())
{
string file_name = save_name.value();
save_name.value() = ""; // so that it does not appear in the parser section of the state file
state.save(file_name);
}
return 0;
}
template <class EOT>
void runAlgorithm(EOT, eoParser& _parser, eoState& _state, eoEsObjectiveBounds& _bounds)
{
// evaluation
eoEvalFuncPtr<eoFixedLength<FitT, double> > eval( real_value );
// population parameters, unfortunately these can not be altered in the state file
eoValueParam<unsigned> mu = _parser.createParam(unsigned(50), "mu","Size of the population");
eoValueParam<unsigned>lambda = _parser.createParam(unsigned(250), "lambda", "No. of children to produce");
if (mu.value() > lambda.value())
{
throw logic_error("Mu must be smaller than lambda in a comma strategy");
}
// Initialization
eoEsChromInit<EOT> init(_bounds);
eoPop<EOT>& pop = _state.takeOwnership(eoPop<EOT>(mu.value(), init));
_state.registerObject(pop);
// evaluate initial population
eval.range(pop.begin(), pop.end());
// Ok, time to set up the algorithm
// Proxy for the mutation parameters
eoEsMutationInit mutateInit(_parser);
eoEsMutate<EOT> mutate(mutateInit, _bounds);
// monitoring, statistics etc.
eoAverageStat<EOT> average;
eoFileMonitor monitor("test.csv");
monitor.add(average);
// Okok, I'm lazy, here's the algorithm defined inline
for (unsigned i = 0; i < 20; ++i)
{
pop.resize(pop.size() + lambda.value());
for (unsigned j = mu.value(); j < pop.size(); ++j)
{
pop[j] = pop[rng.random(mu.value())];
mutate(pop[j]);
eval(pop[j]);
}
// comma strategy
std::sort(pop.begin() + mu.value(), pop.end());
copy(pop.begin() + mu.value(), pop.begin() + 2 * mu.value(), pop.begin());
pop.resize(mu.value());
average(pop);
monitor();
}
}