def test_uniform_crossover_all(self):
self.indiv1, self.indiv2 = Genotype.xover_genes(self.indiv1,
self.indiv2,
cxpb=1)
indiv1_allchanged = not any([
np.allclose(self.indiv1[0].mean, np.array([0, 0])),
np.allclose(self.indiv1[0].cov, np.array([[1, 0], [0, 1]])),
np.allclose(self.indiv1[1].mean, np.array([5, 5])),
np.allclose(self.indiv1[1].cov, np.array([[5, 0], [0, 10]]))
])
self.assertTrue(indiv1_allchanged)
def test_views_swap_all_genes(self):
orig_all_vals = np.copy(self.indiv2.all_values)
self.indiv1, self.indiv2 = Genotype.xover_genes(self.indiv1,
self.indiv2,
cxpb=1)
self.indiv1.recreate_views()
self.indiv1.resample_values()
close = np.allclose(self.indiv1.all_values, orig_all_vals)
self.assertTrue(close)
def test_uniform_crossover_none(self):
self.indiv1, self.indiv2 = Genotype.xover_genes(self.indiv1,
self.indiv2,
mixing_ratio=0.0)
indiv1_unchanged = all([
np.allclose(self.indiv1[0].mean, np.array([0, 0])),
np.allclose(self.indiv1[0].cov, np.array([[1, 0], [0, 1]])),
np.allclose(self.indiv1[1].mean, np.array([5, 5])),
np.allclose(self.indiv1[1].cov, np.array([[5, 0], [0, 10]]))
])
self.assertTrue(indiv1_unchanged)
def test_uniform_crossover_genes(self):
# Get the sequence of the numbers to be generated
rng = np.random.RandomState(42)
swaps = [
True if rng.rand() < 0.5 else False
for _ in range(len(self.indiv1) * 2)
]
indiv1_means = [i.mean for i in self.indiv1]
indiv2_means = [i.mean for i in self.indiv2]
indiv1_covs = [i.cov for i in self.indiv1]
indiv2_covs = [i.cov for i in self.indiv2]
Genotype.global_rng = np.random.RandomState(42)
self.indiv1, self.indiv2 = Genotype.xover_genes(self.indiv1,
self.indiv2,
mixing_ratio=0.5)
# Test means
for i, (clust1, clust2,
swap) in enumerate(zip(self.indiv1, self.indiv2, swaps[0::2])):
with self.subTest(i=i):
if swap:
self.assertTrue(
np.array_equal(clust1.mean, indiv2_means[i]))
self.assertTrue(
np.array_equal(clust2.mean, indiv1_means[i]))
else:
self.assertTrue(
np.array_equal(clust1.mean, indiv1_means[i]))
self.assertTrue(
np.array_equal(clust2.mean, indiv2_means[i]))
# Test covs
for i, (clust1, clust2,
swap) in enumerate(zip(self.indiv1, self.indiv2, swaps[1::3])):
with self.subTest(i=i):
if swap:
self.assertTrue(np.array_equal(clust1.cov, indiv2_covs[i]))
self.assertTrue(np.array_equal(clust2.cov, indiv1_covs[i]))
else:
self.assertTrue(np.array_equal(clust1.cov, indiv1_covs[i]))
self.assertTrue(np.array_equal(clust2.cov, indiv2_covs[i]))