def test_random_mimic():
"""Test random_mimic method"""
dists = [(0, 1, 3), (0, 2, 5), (0, 3, 1), (0, 4, 7), (1, 3, 6),
(4, 1, 9), (2, 3, 8), (2, 4, 2), (3, 2, 8), (3, 4, 4)]
pop = np.array([[1, 0, 3, 2, 4], [0, 2, 1, 3, 4], [0, 2, 4, 3, 1],
[4, 1, 3, 2, 0], [3, 4, 0, 2, 1], [2, 4, 0, 3, 1]])
problem = TSPOpt(5, distances=dists)
problem.keep_sample = pop
problem.eval_node_probs()
problem.find_sample_order()
rand = problem.random_mimic()
assert (len(rand) == 5 and len(set(rand)) == 5)
def test_sample_pop():
"""Test sample_pop method"""
dists = [(0, 1, 3), (0, 2, 5), (0, 3, 1), (0, 4, 7), (1, 3, 6),
(4, 1, 9), (2, 3, 8), (2, 4, 2), (3, 2, 8), (3, 4, 4)]
pop = np.array([[1, 0, 3, 2, 4], [0, 2, 1, 3, 4], [0, 2, 4, 3, 1],
[4, 1, 3, 2, 0], [3, 4, 0, 2, 1], [2, 4, 0, 3, 1]])
problem = TSPOpt(5, distances=dists)
problem.keep_sample = pop
problem.eval_node_probs()
sample = problem.sample_pop(100)
row_sums = np.sum(sample, axis=1)
assert (np.shape(sample)[0] == 100 and np.shape(sample)[1] == 5
and max(row_sums) == 10 and min(row_sums) == 10)