def test_tournament_distribution(self) -> None:
# Test default distribution
set_numpy_seed()
population = get_dummy_population(-100, -90, 1000)
values_def = self.fetch_distribution(population)
self.assertListEqual([547, 243, 110, 41, 34, 11, 9, 2, 0, 3], list(values_def))
def test_tournament_distribution_stochastic(self) -> None:
# Test stochastic distribution when k=1
set_numpy_seed()
population = get_dummy_population(-100, -90, 1000)
self.selector.k = 1
values_stochastic = self.fetch_distribution(population)
self.selector.__init__() # reinitialise to reset k to default
self.assertTrue((20-np.sum(np.log10(values_stochastic))) <= 0.02)
def test_tournament_distribution_deterministic(self) -> None:
# Test deterministic tournament selection
set_numpy_seed()
population = get_dummy_population(-100, -90, 1000)
values_def = self.fetch_distribution(population)
self.selector.p = 1 # Set p_select for the fittest member in the tournament to 1
values_deterministic = self.fetch_distribution(population)
self.selector.__init__() # reinitialise to reset p to default
self.assertTrue(values_deterministic[0] > values_def[0])
def test_boltzmann_distribution(self) -> None:
# TODO: come up with a better test for distributions
# self.skipTest("not_working")
population = get_dummy_population(-100, -90, 1000)
parents = []
for i in range(500):
p1, p2 = self.selector(population)
parents.append(p1.cost)
parents.append(p2.cost)
parent_costs = np.array(parents)
values, _ = np.histogram(parent_costs)
self.assertListEqual([515, 250, 108, 59, 31, 17, 11, 5, 3, 1], list(values))
def setUp(self) -> None:
"""Sets the random seed and sets up the dummy population and Rank selector"""
set_numpy_seed()
self.selector = RankSelector()
self.population = get_dummy_population()