def test_bicgstab(self):
diffusion = Diffusion(n_iter=-1)
adjacency = test_digraph()
scores1 = diffusion.fit_transform(adjacency, {0: 1})
scores2 = self.diffusion.fit_transform(adjacency, {0: 1})
self.assertAlmostEqual(0, np.linalg.norm(scores1 - scores2))
class TestDiffusion(unittest.TestCase):
def setUp(self):
"""Basic diffusion."""
self.diffusion = Diffusion()
def test_unknown_types(self):
with self.assertRaises(TypeError):
# noinspection PyTypeChecker
self.diffusion.fit(sparse.identity(2, format='csr'), seeds='test')
def test_single_node_graph(self):
self.diffusion.fit(sparse.identity(1, format='csr'), {0: 1})
self.assertEqual(self.diffusion.scores_, [1])
def test_range(self):
for adjacency in [test_graph(), test_digraph()]:
score = self.diffusion.fit_transform(adjacency, {
0: 0,
1: 1,
2: 0.5
})
self.assertTrue(np.all(score <= 1) and np.all(score >= 0))
bidiffusion = BiDiffusion()
biadjacency = test_bigraph()
score = bidiffusion.fit_transform(biadjacency, {0: 1})
self.assertTrue(np.all(score <= 1) and np.all(score >= 0))
def test_bicgstab(self):
diffusion = Diffusion(n_iter=-1)
adjacency = test_digraph()
scores1 = diffusion.fit_transform(adjacency, {0: 1})
scores2 = self.diffusion.fit_transform(adjacency, {0: 1})
self.assertAlmostEqual(0, np.linalg.norm(scores1 - scores2))