def test_get_max_sum_index_raises_error(self):
strategy = LocalOptimisation()
indices = [(1, 2, 4), (3, 2, 1), (4, 2, 1)]
distances_wrong = [20, 40]
with raises(ValueError):
strategy.get_max_sum_ind(indices, distances_wrong, 0, 0)
def test_get_max_sum_ind(self):
'''
Tests whether the right maximum indices are returned.
'''
strategy = LocalOptimisation()
indices = np.array([(1, 2, 4), (3, 2, 1), (4, 2, 1)])
distances = np.array([20, 40, 50])
output = strategy.get_max_sum_ind(indices, distances, 0, 0)
expected = (4, 2, 1)
assert_equal(output, expected)