def test_is_stratified(self, shuffled_chromosomes, n_groups):
population = Population(shuffled_chromosomes,
eval_function=lambda x: x).evaluate()
islands = population.group(group_stratified, n_groups=n_groups)
# All islands should have the same total fitness
assert len(
set(
sum(map(lambda i: i.fitness, island.individuals))
for island in islands)) == 1
def test_is_nearly_stratified(self, shuffled_chromosomes, n_groups):
population = Population(shuffled_chromosomes,
eval_function=lambda x: x).evaluate()
islands = population.group(group_stratified, n_groups=n_groups)
# All islands should have roughly the same total fitness
sum_fitnesses = [
sum(map(lambda i: i.fitness, island.individuals))
for island in islands
]
assert max(sum_fitnesses) - min(sum_fitnesses) < n_groups * len(
islands[0])
