def test_mutate(self):
"""
Should perform mutation on a subset of the population
"""
ind0 = np.asarray([1., 2., 3., 4.])
pop = Population(individuals=ind0, fitness=ind0)
# should change some values
pop.mutate(p=1.)
count = 0
for f0, f1 in zip(ind0, pop.individuals):
if f0 != f1:
count += 1
self.assertGreater(count, 0)
# should set fitness for changed individuals to nan
self.assertGreater(len(pop.inew), 0)
# should handle > 1d
ind0 = np.random.rand(50, 10)
pop = Population(individuals=ind0, fitness=range(50))
pop.mutate(p=1.)
self.assertGreater(len(pop.inew), 0)
# should not change shape of individuals
self.assertEqual(pop.individuals.shape, ind0.shape)
