void evolutionary_algorithm::write_data()
{
individual_vector::iterator it = std::max_element(population.begin(), population.end(),
&compare_individuals);
double max_fitness = (*it)->fitness();
double avg = average_fitness(population);
double std = standard_deviation(population);
csv.write(3, avg, std, max_fitness);
if(debug_flag)
{
//print_individuals(population);
for(std::size_t i = 0; i < population.size(); ++i)
{
sstream ss;
ss << "id: " << i << "\tphenotype:\t";
for(std::size_t j = 0; j < population[i]->phenotype()->size(); ++j)
{
ss << " " << (*population[i]->phenotype())[j];
}
ss << "\tgenotype:";
for(std::size_t j = 0; j < population[i]->genotype()->size(); ++j)
{
if(j % development->bit_chunk_size()==0) ss << " ";
ss << (*population[i]->genotype())[j];
}
debug.write(1, ss.str().c_str());
}
}
}
bool GA::has_converged() const {
return (historic_best_fitness - average_fitness()) < convergence_threshold;
}
