def test_random_rbf_generator_drift(test_path):
stream = RandomRBFGeneratorDrift(model_random_state=99,
sample_random_state=50,
n_classes=4,
n_features=10,
n_centroids=50,
change_speed=0.87,
num_drift_centroids=50)
stream.prepare_for_use()
assert stream.n_remaining_samples() == -1
expected_names = [
'att_num_0', 'att_num_1', 'att_num_2', 'att_num_3', 'att_num_4',
'att_num_5', 'att_num_6', 'att_num_7', 'att_num_8', 'att_num_9'
]
assert stream.feature_names == expected_names
expected_targets = [0, 1, 2, 3]
assert stream.target_values == expected_targets
assert stream.target_names == ['target_0']
assert stream.n_features == 10
assert stream.n_cat_features == 0
assert stream.n_num_features == 10
assert stream.n_targets == 1
assert stream.get_data_info(
) == 'Random RBF Generator with drift - 1 targets, 4 classes, 10 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, 'random_rbf_drift_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_random_rbf_generator_drift(test_path):
stream = RandomRBFGeneratorDrift(model_seed=99,
instance_seed=50,
num_classes=4,
num_att=10,
num_centroids=50,
change_speed=0.87,
num_drift_centroids=50)
stream.prepare_for_use()
assert stream.estimated_remaining_instances() == -1
expected_header = [
'att_num_0', 'att_num_1', 'att_num_2', 'att_num_3', 'att_num_4',
'att_num_5', 'att_num_6', 'att_num_7', 'att_num_8', 'att_num_9'
]
assert stream.get_attributes_header() == expected_header
expected_classes = [0, 1, 2, 3]
assert stream.get_classes() == expected_classes
assert stream.get_classes_header() == ['class']
assert stream.get_num_attributes() == 10
assert stream.get_num_nominal_attributes() == 0
assert stream.get_num_numerical_attributes() == 10
assert stream.get_num_targets() == 4
assert stream.get_num_values_per_nominal_attribute() == 0
assert stream.get_plot_name(
) == 'Random RBF Generator with drift - 4 class labels'
assert stream.has_more_instances() is True
assert stream.is_restartable() is True
# Load test data corresponding to first 10 instances
test_file = os.path.join(test_path, 'random_rbf_drift_stream.npz')
data = np.load(test_file)
X_expected = data['X']
y_expected = data['y']
X, y = stream.next_instance()
assert np.alltrue(X[0] == X_expected[0])
assert np.alltrue(y[0] == y_expected[0])
X, y = stream.get_last_instance()
assert np.alltrue(X[0] == X_expected[0])
assert np.alltrue(y[0] == y_expected[0])
stream.restart()
X, y = stream.next_instance(10)
assert np.alltrue(X == X_expected)
assert np.alltrue(y == y_expected)