def test_unknown(self):
a = ConnectivityTree(add_unknown=True)
expected_results = numpy.array([[1, 4, 0],
[2, 3, 4],
[25, 15, 9]])
a.fit([METHANE])
self.assertTrue((a.transform(ALL_DATA) == expected_results).all())
def test_tfidf(self):
a = ConnectivityTree(do_tfidf=True)
expected = numpy.array([[0., 0., 0., 0.], [0., 0., 0., 1.62186043],
[0., 0., 5.49306144, 1.62186043]])
a.fit(ALL_DATA)
try:
m = a.transform(ALL_DATA)
numpy.testing.assert_array_almost_equal(m, expected)
except AssertionError as e:
self.fail(e)
def test_transform_before_fit(self):
a = ConnectivityTree()
with self.assertRaises(ValueError):
a.transform(ALL_DATA)
def test_large_to_small_transform(self):
a = ConnectivityTree(depth=2)
a.fit([BIG])
idxs = numpy.where(ALL_ATOM_TREE[2] != 0)[0]
expected = ALL_ATOM_TREE[:, idxs]
self.assertTrue((a.transform(ALL_DATA) == expected).all())
def test_transform(self):
a = ConnectivityTree()
a.fit(ALL_DATA)
self.assertTrue((a.transform(ALL_DATA) == ALL_ATOM).all())
def test_fit_depth_1_separated(self):
a = ConnectivityTree(depth=1)
a.fit([METHANE2])
self.assertTrue(
(a.transform([METHANE2]) == numpy.array([[1, 4]])).all())