int main(int argc, char *argv[])
{
ea::AnsiRandomNumberGenerator g;
// create parent individuals:
std::vector<Sequence*> population;
for(ea::sequence_len_t i = 0; i < 10; ++i)
{
auto seq = base.create(10);
int32_t genes[10];
g.get_unique_int32_seq(0, 9, genes, 10);
for(ea::sequence_len_t j = 0; j < 10; ++j)
{
base.set(seq, j, genes[j]);
}
population.push_back(seq);
}
// create input adapter:
auto input = ea::make_input_adapter(population);
// print parent individuals:
std::for_each(begin(population), end(population), [](Sequence* seq)
{
print_genome(seq);
});
std::cout << std::endl;
// select & print individuals:
std::vector<std::size_t> children;
auto output = ea::make_output_adapter(children);
ea::TournamentSelection<ea::Int32PGenomeBase<Fitness>> sel;
sel.select(input, 5, output);
std::for_each(begin(children), end(children), [&population](uint32_t index)
{
std::cout << "selected child: " << index << " ==> ";
print_genome(population[index]);
});
// cleanup:
ea::dispose(base, begin(population), end(population));
return 0;
}
int main(int argc, char *argv[])
{
// create parent individuals:
auto a = base.create(10);
auto b = base.create(10);
for(ea::sequence_len_t i = 0; i < 10; ++i)
{
base.set(a, i, i);
base.set(b, i, 9 - i);
}
// create children:
std::vector<Sequence*> children;
auto adapter = ea::make_output_adapter(children);
ea::CycleCrossover<ea::Int32PGenomeBase<Fitness>> crossover;
std::size_t n = crossover.crossover(a, b, adapter);
std::cout << "number of created children: " << n << std::endl;
std::for_each(begin(children), end(children), [](Sequence* seq)
{
print_genome(seq);
});
// cleanup:
ea::dispose(base, { a, b });
ea::dispose(base, begin(children), end(children));
return 0;
}
