def test_random_neighbor_range_eq_step():
"""Test random_neighbor method when range equals step size"""
problem = ContinuousOpt(5, OneMax(), maximize=True,
min_val=0, max_val=1, step=1)
x = np.array([0, 0, 1, 1, 1])
problem.set_state(x)
neigh = problem.random_neighbor()
sum_diff = np.sum(np.abs(x - neigh))
assert (len(neigh) == 5 and sum_diff == 1)
def test_update_state_in_range():
"""Test update_state method where all updated values are within the
tolerated range"""
problem = ContinuousOpt(5, OneMax(), maximize=True,
min_val=0, max_val=20, step=1)
x = np.array([0, 1, 2, 3, 4])
problem.set_state(x)
y = np.array([2, 4, 6, 8, 10])
updated = problem.update_state(y)
assert np.array_equal(updated, (x + y))
def test_update_state_outside_range():
"""Test update_state method where some updated values are outside the
tolerated range"""
problem = ContinuousOpt(5, OneMax(), maximize=True,
min_val=0, max_val=5, step=1)
x = np.array([0, 1, 2, 3, 4])
problem.set_state(x)
y = np.array([2, -4, 6, -8, 10])
updated = problem.update_state(y)
z = np.array([2, 0, 5, 0, 5])
assert np.array_equal(updated, z)
def test_random_neighbor_range_gt_step():
"""Test random_neighbor method when range greater than step size"""
problem = ContinuousOpt(5, OneMax(), maximize=True,
min_val=0, max_val=2, step=1)
x = np.array([0, 1, 2, 3, 4])
problem.set_state(x)
neigh = problem.random_neighbor()
abs_diff = np.abs(x - neigh)
abs_diff[abs_diff > 0] = 1
sum_diff = np.sum(abs_diff)
assert (len(neigh) == 5 and sum_diff == 1)
def test_find_neighbors_range_eq_step():
"""Test find_neighbors method when range equals step size"""
problem = ContinuousOpt(5, OneMax(), maximize=True,
min_val=0, max_val=1, step=1)
x = np.array([0, 1, 0, 1, 0])
problem.set_state(x)
problem.find_neighbors()
neigh = np.array([[1, 1, 0, 1, 0],
[0, 0, 0, 1, 0],
[0, 1, 1, 1, 0],
[0, 1, 0, 0, 0],
[0, 1, 0, 1, 1]])
assert np.array_equal(np.array(problem.neighbors), neigh)