97 lines
3 KiB
C++
97 lines
3 KiB
C++
/*
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The Evolving Distribution Objects framework (EDO) is a template-based,
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ANSI-C++ evolutionary computation library which helps you to write your
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own estimation of distribution algorithms.
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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 2.1 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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
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Copyright (C) 2013 Thales group
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*/
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/*
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Authors:
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Johann Dréo <johann.dreo@thalesgroup.com>
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*/
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#include <vector>
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#include <iostream>
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#include <string>
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#include <cmath>
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#include <eo>
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#include <edo>
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#include <ga.h> // for Bools
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template<class T>
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void print( T v, std::string sep=" " )
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{
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for( typename T::iterator it=v.begin(); it!=v.end(); ++it ) {
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std::cout << *it << sep;
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}
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std::cout << std::endl;
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}
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int main(int ac, char** av)
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{
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typedef eoBit<double> Bools;
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eoParser parser(ac, av);
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std::string section("Algorithm parameters");
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unsigned int popsize = parser.createParam((unsigned int)100000, "popSize", "Population Size", 'P', section).value(); // P
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unsigned int dim = parser.createParam((unsigned int)20, "dim", "Dimension size", 'd', section).value(); // d
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double proba = parser.createParam((double)0.5, "proba", "Probability to estimate", 'b', section).value(); // b
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// This generate a random boolean when called...
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eoBooleanGenerator flip( proba );
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// ... by this initializator...
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eoInitFixedLength<Bools> init( dim, flip );
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// ... when building this pop.
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std::cout << "Init a pop of eoBit of size " << popsize << " at random with p(x=1)=" << proba << std::endl;
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eoPop<Bools> pop( popsize, init );
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// print( pop, "\n" );
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// EDO triplet
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edoBinomial<Bools> distrib(dim,0.0);
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edoEstimatorBinomial<Bools> estimate;
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edoSamplerBinomial<Bools> sample;
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std::cout << "Estimate a distribution from the init pop" << std::endl;
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distrib = estimate(pop);
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print( distrib );
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// std::cout << std::endl;
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std::cout << "Sample a new pop from the init distrib" << std::endl;
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pop.clear();
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for( unsigned int i=0; i<popsize; ++i ) {
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pop.push_back( sample( distrib ) );
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}
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// print( pop, "\n" );
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std::cout << "Estimate a distribution from the sampled pop" << std::endl;
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distrib = estimate(pop);
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print( distrib );
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// std::cout << std::endl;
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double sum=0;
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for( unsigned int i=0; i<distrib.size(); ++i ) {
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sum += distrib[i];
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}
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double e = sum / dim;
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std::cout << "Estimated initial proba = " << e << std::endl;
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}
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