def test_undirected(self):
adjacency = test_graph()
n = adjacency.shape[0]
method = Spring()
embedding = method.fit_transform(adjacency)
self.assertEqual(embedding.shape, (n, 2))
pred1 = method.predict(adjacency[0])
pred2 = method.predict(adjacency[0].toarray())
self.assertEqual(pred1.shape, (2, ))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)
pred1 = method.predict(adjacency)
pred2 = method.predict(adjacency.toarray())
self.assertTupleEqual(pred1.shape, (n, 2))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)
def test_undirected(self):
adjacency = test_graph()
n = adjacency.shape[0]
for method in self.methods:
with self.assertRaises(ValueError):
method.predict(adjacency[0])
embedding = method.fit_transform(adjacency)
self.assertEqual(embedding.shape, (n, 2))
ref = embedding[0]
pred1 = method.predict(adjacency[0])
pred2 = method.predict(adjacency[0].toarray())
self.assertEqual(pred1.shape, (2, ))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)
self.assertAlmostEqual(np.linalg.norm(pred1 - ref), 0)
pred1 = method.predict(adjacency)
pred2 = method.predict(adjacency.toarray())
self.assertTupleEqual(pred1.shape, (n, 2))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)
self.assertAlmostEqual(np.linalg.norm(pred1 - embedding), 0)
method = Spring()
embedding = method.fit_transform(adjacency)
self.assertEqual(embedding.shape, (n, 2))
pred1 = method.predict(adjacency[0])
pred2 = method.predict(adjacency[0].toarray())
self.assertEqual(pred1.shape, (2, ))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)
pred1 = method.predict(adjacency)
pred2 = method.predict(adjacency.toarray())
self.assertTupleEqual(pred1.shape, (n, 2))
self.assertAlmostEqual(np.linalg.norm(pred1 - pred2), 0)