def test_fine_tuned_modularity_seed(self):
community_array = fine_tuned_clustering_q(self.G, seed=2)
computed_metric = modularity_r(self.adj, community_array,
np.unique(community_array))
assert_equal(round(computed_metric, 4), 0.4198)
def test_fine_tuned_modularity_r(self):
community_array = fine_tuned_clustering_q(self.G, r=2.0, seed=100)
computed_metric = modularity_r(self.adj,
community_array,
np.unique(community_array),
r=2.0)
assert_equal(round(computed_metric, 4), 0.5148)
def test_fine_tuned_modularity_method3(self):
community_array = fine_tuned_clustering_q(self.G,
evd_method='lobpcg',
seed=100)
computed_metric = modularity_r(self.adj, community_array,
np.unique(community_array))
assert_equal(round(computed_metric, 4), 0.4198)
def test_constrained_fine_tuned_modularity_size2(self):
community_array = \
constrained_fine_tuned_clustering_q(self.G,
cluster_size=10,
seed=100)
computed_metric = modularity_r(self.adj, community_array,
np.unique(community_array))
assert_equal(round(computed_metric, 4), 0.3909)
def test_fine_tuned_modularity_2(self):
community_array = fine_tuned_clustering_q(self.G,
normalize=False,
r=2,
evd_method='lobpcg',
seed=2)
computed_metric = modularity_r(self.adj,
community_array,
np.unique(community_array),
r=2)
assert_equal(round(computed_metric, 4), 0.5153)
