def test_nodes_leaves(self):
X, y = load_dataset(
random_state=self._random_state,
n_classes=3,
n_features=5,
n_samples=1500,
)
clf = Stree(random_state=self._random_state)
clf.fit(X, y)
nodes, leaves = clf.nodes_leaves()
self.assertEqual(31, nodes)
self.assertEqual(16, leaves)
X, y = load_wine(return_X_y=True)
clf = Stree(random_state=self._random_state)
clf.fit(X, y)
nodes, leaves = clf.nodes_leaves()
self.assertEqual(11, nodes)
self.assertEqual(6, leaves)
def test_nodes_leaves_artificial(self):
n1 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test1")
n2 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test2")
n3 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test3")
n4 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test4")
n5 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test5")
n6 = Snode(None, [1, 2, 3, 4], [1, 0, 1, 1], [], 0.0, "test6")
n1.set_up(n2)
n2.set_up(n3)
n2.set_down(n4)
n3.set_up(n5)
n4.set_down(n6)
clf = Stree(random_state=self._random_state)
clf.tree_ = n1
nodes, leaves = clf.nodes_leaves()
self.assertEqual(6, nodes)
self.assertEqual(2, leaves)