def test_load_with_too_many_feature_columns_raises_value_error(
saved_random_dataset):
path, dataset = saved_random_dataset
n_features = dataset.features.shape[1]
wrong_n_features = n_features + 3
dataset = Dataset()
with pytest.raises(ValueError):
dataset.load_from_pickle(path, range(wrong_n_features),
range(n_features, n_features + 1))
def test_save_and_load_to_pickle_identical_dataset(generate_random_dataset):
path_to_save = 'test_pickle_save.pkl'
dataset = generate_random_dataset
n_features = dataset.features.shape[1]
dataset.save_to_pickle(path_to_save)
loaded_dataset = Dataset()
loaded_dataset.load_from_pickle(path_to_save, range(n_features),
range(n_features, n_features + 1))
assert np.array_equal(loaded_dataset.features, dataset.features)
assert np.array_equal(loaded_dataset.labels, dataset.labels.reshape(-1, 1))
def test_save_and_load_to_pickle_identical_file_multiple_labels():
n_features = 5
n_samples = 10
n_labels = 3
features = np.random.rand(n_samples, n_features)
labels = np.random.rand(n_samples, n_labels)
path_to_save = 'test_pickle_save.pkl'
dataset = Dataset(features, labels)
dataset.save_to_pickle(path_to_save)
loaded_dataset = Dataset()
loaded_dataset.load_from_pickle(path_to_save, range(n_features),
range(n_features, n_features + n_labels))
assert np.array_equal(loaded_dataset.features, dataset.features)
assert np.array_equal(loaded_dataset.labels, dataset.labels)
def test_load_nonexisting_file_raises_filenotfound_error():
path_to_file = 'nonexisting_file.pkl'
dataset = Dataset()
with pytest.raises(FileNotFoundError):
dataset.load_from_pickle(path_to_file, range(1), range(1, 2))