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)