def test_graph_net_classifier_score():
iris = load_iris()
X, y = iris.data, iris.target
y = 2 * (y > 0) - 1
X_, mask = to_niimgs(X, (2, 2, 2))
gnc = SpaceNetClassifier(mask=mask, alphas=1. / .01 / X.shape[0],
l1_ratios=1., tol=1e-10,
standardize=False, verbose=0,
screening_percentile=100.).fit(X_, y)
accuracy = gnc.score(X_, y)
assert_equal(accuracy, accuracy_score(y, gnc.predict(X_)))
