def test_on_one_row(self):
test_argument = np.array([[1382.0, 390167.0]])
with pytest.raises(ValueError) as exc_info:
split_into_training_and_testing_sets(test_argument)
expected_error_msg = "Argument data_array must have at least 2 rows,"
" it actually has just 1"
assert exc_info.match(expected_error_msg)
def test_on_one_row():
test_argument = np.array([[1382.0, 390167.0]])
# Store information about raised ValueError in exc_info
with pytest.raises(ValueError) as exc_info:
split_into_training_and_testing_sets(test_argument)
expected_error_msg = "Argument data_array must have at least 2 rows, it actually has just 1"
# Check if the raised ValueError contains the correct message
assert exc_info.match(expected_error_msg)
def test_valueerror_on_one_dimensional_argument_message():
example_argument = np.array([2081, 314942, 1059, 186606, 1148, 206186])
# exception_info stores ValueError
with pytest.raises(ValueError) as exception_info:
split_into_training_and_testing_sets(example_argument)
assert exception_info.match(
"Argument data_array must be two dimensional. Got 1 dimensional array instead!"
)
def test_on_six_rows(self):
example_argument = np.array([[2081.0, 314942.0], [1059.0, 186606.0],
[1148.0, 206186.0], [1506.0, 248419.0],
[1210.0, 214114.0], [1697.0, 277794.0]])
expected_training_array_num_rows = 4
expected_testing_array_num_rows = 2
actual = split_into_training_and_testing_sets(example_argument)
assert actual[0].shape[0] == expected_training_array_num_rows, \
"The actual number of rows in the training array is not {}".format(expected_training_array_num_rows)
assert actual[1].shape[0] == expected_testing_array_num_rows, \
"The actual number of rows in the testing array is not {}".format(expected_testing_array_num_rows)
def test_on_six_rows(self):
test_argument = np.array([
[2081.0, 314942.0],
[1059.0, 186606.0],
[1148.0, 206186.0],
[1506.0, 248419.0],
[1210.0, 214114.0],
[1697.0, 277794.0],
])
expected_length_training_set = 4
expected_length_testing_set = 2
actual = split_into_training_and_testing_sets(test_argument)
assert actual[0].shape[0] == expected_length_training_set, \
"The actual number of rows in the training array is not 4"
assert actual[1].shape[0] == expected_length_testing_set, \
"The actual number of rows in the testing array is not 2"
def test_valueerror_on_one_dimensional_argument():
example_argument = np.array([2081, 314942, 1059, 186606, 1148, 206186])
with pytest.raises(ValueError):
split_into_training_and_testing_sets(example_argument)
def test_on_one_dimensional_array(self):
test_argument = np.array([1382.0, 390167.0])
with pytest.raises(ValueError) as exc_info:
split_into_training_and_testing_sets(test_argument)
expected_error_msg = "Argument data_array must be two dimensional. Got 1 dimensional array instead!"
assert exc_info.match(expected_error_msg)
