def test_find_maximum():
scores = np.array(range(15))
k_choices = 4
N = 6
output = find_maximum(scores, N, k_choices)
expected = [2, 3, 4, 5]
assert_equal(output, expected)
def test_find_maximum():
scores = np.array(range(15))
k_choices = 4
N = 6
output = find_maximum(scores, N, k_choices)
expected = [2, 3, 4, 5]
assert_equal(output, expected)
def test_combo_from_find_most_distant():
'''
Tests whether the correct combination is picked from the fixture drawn
from Saltelli et al. 2008, in the solution to exercise 3a,
Chapter 3, page 134.
'''
sample_inputs = setup()
N = 6
num_params = 2
k_choices = 4
scores = find_most_distant(sample_inputs, N, num_params, k_choices)
output = find_maximum(scores, N, k_choices)
expected = [0, 2, 3, 5] # trajectories 1, 3, 4, 6
assert_equal(output, expected)
def test_combo_from_find_most_distant():
'''
Tests whether the correct combination is picked from the fixture drawn
from Saltelli et al. 2008, in the solution to exercise 3a,
Chapter 3, page 134.
'''
sample_inputs = setup()
N = 6
num_params = 2
k_choices = 4
scores = find_most_distant(sample_inputs, N, num_params, k_choices)
output = find_maximum(scores, N, k_choices)
expected = [0, 2, 3, 5] # trajectories 1, 3, 4, 6
assert_equal(output, expected)
def test_find_local_maximum_distance():
'''
Test whether finding the local maximum distance equals the global maximum distance
in a simple case. From Saltelli et al. 2008, in the solution to exercise 3a,
Chapter 3, page 134.
'''
sample_inputs = setup()
N=6
num_params = 2
k_choices = 4
scores_global = find_most_distant(sample_inputs, N, num_params, k_choices)
output_global = find_maximum(scores_global, N, k_choices)
output_local = find_local_maximum(sample_inputs, N, num_params, k_choices)
assert_equal(output_global, output_local)
def test_find_local_maximum_distance():
'''
Test whether finding the local maximum distance equals the global maximum distance
in a simple case. From Saltelli et al. 2008, in the solution to exercise 3a,
Chapter 3, page 134.
'''
sample_inputs = setup()
N = 6
num_params = 2
k_choices = 4
scores_global = find_most_distant(sample_inputs, N, num_params, k_choices)
output_global = find_maximum(scores_global, N, k_choices)
output_local = find_local_maximum(sample_inputs, N, num_params, k_choices)
assert_equal(output_global, output_local)
