def saved_random_dataset():
n_features = 5
n_samples = 10
features = np.random.rand(n_samples, n_features)
labels = np.random.rand(n_samples)
path_to_save = 'test_pickle_save.pkl'
dataset = Dataset(features, labels)
dataset.save_to_pickle(path_to_save)
return path_to_save, dataset
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)