def test_agrawal_generator(test_path):
stream = AGRAWALGenerator(classification_function=2,
random_state=112,
balance_classes=False,
perturbation=0.28)
stream.prepare_for_use()
assert stream.n_remaining_samples() == -1
expected_names = [
"salary", "commission", "age", "elevel", "car", "zipcode", "hvalue",
"hyears", "loan"
]
assert stream.feature_names == expected_names
expected_targets = [0, 1]
assert stream.target_values == expected_targets
assert stream.target_names == ['target']
assert stream.n_features == 9
assert stream.n_cat_features == 3
assert stream.n_num_features == 6
assert stream.n_targets == 1
assert stream.get_data_info(
) == 'AGRAWAL Generator - 1 targets, 2 classes, 9 features'
assert stream.has_more_samples() is True
assert stream.is_restartable() is True
# Load test data corresponding to first 10 instances
test_file = os.path.join(test_path, 'agrawal_stream.npz')
data = np.load(test_file)
X_expected = data['X']
y_expected = data['y']
X, y = stream.next_sample()
assert np.alltrue(X[0] == X_expected[0])
assert np.alltrue(y[0] == y_expected[0])
X, y = stream.last_sample()
assert np.alltrue(X[0] == X_expected[0])
assert np.alltrue(y[0] == y_expected[0])
stream.restart()
X, y = stream.next_sample(10)
assert np.alltrue(X == X_expected)
assert np.alltrue(y == y_expected)
assert stream.n_targets == np.array(y).ndim
assert stream.n_features == X.shape[1]
def test_agrawal_drift(test_path):
stream = AGRAWALGenerator(random_state=1)
X, y = stream.next_sample(10)
stream.generate_drift()
X_drift, y_drift = stream.next_sample(10)
# Load test data corresponding to first 10 instances
test_file = os.path.join(test_path, 'agrawal_stream_drift.npz')
data = np.load(test_file)
X_expected = data['X']
y_expected = data['y']
X = np.concatenate((X, X_drift))
y = np.concatenate((y, y_drift))
assert np.alltrue(X == X_expected)
assert np.alltrue(y == y_expected)
def test_agrawal_generator_all_functions(test_path):
for f in range(10):
stream = AGRAWALGenerator(classification_function=f, random_state=1)
# Load test data corresponding to first 10 instances
test_file = os.path.join(test_path, 'agrawal_stream_{}.npz'.format(f))
data = np.load(test_file)
X_expected = data['X']
y_expected = data['y']
X, y = stream.next_sample(10)
assert np.alltrue(X == X_expected)
assert np.alltrue(y == y_expected)