def test_result_equality():
nn_opt = NearestNeighborsOpt(schema)
nn_not_opt = NearestNeighborsNotOpt(schema)
recoms_opt = nn_opt.get_recom_info(5)
recoms_not_opt = nn_not_opt.get_recoms_info(5)
np.testing.assert_array_equal(recoms_opt, recoms_not_opt,
"Results are not equal.")
def test_get_recom_info():
my_problem = NearestNeighborsOpt(schema)
result = my_problem.get_recom_info(5)
expected = np.array([[2, 0, 1, 1, 1, 3, 2, 2],
[1, 0, 2, 0, 1, 2, 1, 3],
[1, 1, 1, 0, 1, 1, 3, 3],
[2, 0, 2, 1, 0, 4, 1, 3],
[1, 1, 1, 0, 1, 1, 3, 3],
[2, 0, 1, 1, 1, 3, 2, 2],
[1, 0, 3, 0, 1, 2, 1, 2],
[1, 1, 1, 0, 0, 2, 2, 4],
[3, 1, 5, 1, 1, 4, 3, 5],
[0, 1, 1, 0, 1, 2, 3, 3]])
np.testing.assert_array_equal(result, expected, "Fail : get_recom_info")
def test_get_nearest_neighbors():
my_problem = NearestNeighborsOpt(schema)
result = my_problem.get_nearest_neighbors(5)
expected = np.array([[7, 9, 0, 3, 5],
[6, 7, 9, 1, 3],
[5, 7, 9, 2, 4],
[0, 5, 7, 1, 3],
[5, 7, 9, 2, 4],
[7, 0, 3, 9, 5],
[8, 9, 1, 3, 6],
[2, 4, 5, 3, 7],
[5, 6, 7, 8, 9],
[2, 3, 4, 5, 9]])
np.testing.assert_array_equal(result, expected, "Fail : get_nearest_neighbors")
def test_get_no_attr_users():
my_problem = NearestNeighborsOpt(schema)
result = my_problem.get_no_attr_users()[0]
expected = np.array([8])
np.testing.assert_array_equal(result, expected, "Fail : get_no_attr_users")
def test_most_popular_item():
my_problem = NearestNeighborsOpt(schema)
result = my_problem.get_most_pop_item()
expected = np.array([3, 1, 5, 1, 1, 4, 3, 5])
np.testing.assert_array_equal(result, expected, "Fail : most_popular_item")
