def test_copagerank(self):
seeds = {0: 1}
biadjacency = test_bigraph()
adjacency = co_neighbor_graph(biadjacency,
method='exact',
normalized=True)
pagerank = PageRank(damping_factor=0.85, solver='lanczos')
pagerank.fit(biadjacency, seeds_row=seeds)
scores1 = pagerank.scores_row_
scores1 /= scores1.sum()
scores2 = PageRank(damping_factor=0.85**2,
solver='lanczos').fit_transform(adjacency, seeds)
self.assertAlmostEqual(np.linalg.norm(scores1 - scores2), 0., places=6)
def test_pagerank(self):
ground_truth = np.ones(3) / 3
adjacency = rock_paper_scissors()
pagerank_sps = PageRank(solver='spsolve')
pagerank_sps.fit(adjacency)
scores = pagerank_sps.scores_
self.assertAlmostEqual(np.linalg.norm(scores - ground_truth), 0.)
pagerank_sps.fit(adjacency, personalization=np.array([0, 1, 0]))
pagerank_sps.fit(adjacency, personalization={1: 1})
pagerank_high_damping = PageRank(damping_factor=0.99)
pagerank_high_damping.fit(adjacency)
scores = pagerank_high_damping.scores_
self.assertAlmostEqual(np.linalg.norm(scores - ground_truth),
0.,
places=1)
pagerank_lcz = PageRank(solver='lanczos')
pagerank_lcz.fit(adjacency)
scores = pagerank_lcz.scores_
self.assertAlmostEqual(np.linalg.norm(scores - ground_truth), 0.)
pagerank_lsq = PageRank(solver='lsqr')
pagerank_lsq.fit(adjacency)
scores = pagerank_lsq.scores_
self.assertAlmostEqual(np.linalg.norm(scores - ground_truth), 0.)
pagerank_naive = PageRank(solver=None)
pagerank_naive.fit(adjacency)