@Test(dataProvider = "alterProbabilityParameters")
public void alterProbability(
final Integer ngenes, final Integer nchromosomes, final Integer npopulation, final Double p) {
final Population<DoubleGene, Double> population =
newDoubleGenePopulation(ngenes, nchromosomes, npopulation);
// The mutator to test.
final SinglePointCrossover<DoubleGene, Double> crossover = new SinglePointCrossover<>(p);
final long nallgenes = ngenes * nchromosomes * npopulation;
final long N = 200;
final double mean = crossover.getOrder() * npopulation * p;
final long min = 0;
final long max = nallgenes;
final Range<Long> domain = new Range<>(min, max);
final Histogram<Long> histogram = Histogram.ofLong(min, max, 10);
final LongMomentStatistics variance = new LongMomentStatistics();
for (int i = 0; i < N; ++i) {
final long alterations = crossover.alter(population, 1);
histogram.accept(alterations);
variance.accept(alterations);
}
// Normal distribution as approximation for binomial distribution.
System.out.println(histogram);
// TODO: Implement test
// assertDistribution(histogram, new NormalDistribution<>(domain, mean,
// variance.getVariance()));
}
private static String p(final LongMomentStatistics statistics) {
final NumberFormat nf = NumberFormat.getIntegerInstance();
return format(
"max=%s; mean=%6.6f; var=%6.6f",
nf.format(statistics.getMax()), statistics.getMean(), statistics.getVariance());
}
void accept(final Phenotype<?, C> pt, final long generation) {
_age.accept(pt.getAge(generation));
}
