def test_clustering_integer_nodes(self):
# This tests an error that would happen when a node had an integer value
# greater than the size of the graph
orig_club = nx.karate_club_graph()
club = nx.relabel_nodes(orig_club, { n: n + 5 for n in orig_club.nodes() })
dendrogram = GreedyAgglomerativeClusterer().cluster(club)
dendrogram.clusters() # This would crash
def test_clustering_integer_nodes(self):
# This tests an error that would happen when a node had an integer value
# greater than the size of the graph
orig_club = nx.karate_club_graph()
club = nx.relabel_nodes(orig_club,
{n: n + 5
for n in orig_club.nodes()})
dendrogram = GreedyAgglomerativeClusterer().cluster(club)
dendrogram.clusters() # This would crash
def test_small_graph(self):
graph = nx.Graph();
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
self.assertEqual(list(dendrogram.clusters()), [])
graph.add_node(1)
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
self.assertEqual(list(dendrogram.clusters(1)[0]), [1])
self.assertEqual(list(dendrogram.clusters()[0]), [1])
def test_clusterer_pickling(self):
clusterer = GreedyAgglomerativeClusterer()
p_clusterer = pickle.loads(pickle.dumps(clusterer))
self.assertEqual(clusterer.optimal_clusters,
p_clusterer.optimal_clusters)
clusterer = GreedyAgglomerativeClusterer(100)
p_clusterer = pickle.loads(pickle.dumps(clusterer))
self.assertEqual(clusterer.optimal_clusters,
p_clusterer.optimal_clusters)
def test_non_integer_clustering(self):
graph = nx.Graph()
graph.add_nodes_from(map(lambda i: chr(i), range(10)))
graph.add_edges_from([['a', 'b'], ['b', 'c'], ['a', 'c']])
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
clusters = dendrogram.clusters()
self.assertIn(set(['a', 'b', 'c']), clusters)
for node_index in range(3, 10):
self.assertIn(set([chr(node_index)]), clusters)
def test_orphans(self):
graph = nx.Graph()
graph.add_nodes_from(range(10))
graph.add_edges_from([[0, 1], [1, 2], [0, 2]])
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
clusters = dendrogram.clusters()
self.assertIn(set([0, 1, 2]), clusters)
for node in range(3, 10):
self.assertIn(set([node]), clusters)
def test_non_integer_clustering(self):
graph = nx.Graph();
graph.add_nodes_from(map(lambda i: chr(i), range(10)))
graph.add_edges_from([['a', 'b'], ['b', 'c'], ['a', 'c']])
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
clusters = dendrogram.clusters()
self.assertIn(set(['a', 'b', 'c']), clusters)
for node_index in range(3, 10):
self.assertIn(set([chr(node_index)]), clusters)
def test_orphans(self):
graph = nx.Graph();
graph.add_nodes_from(range(10))
graph.add_edges_from([[0, 1], [1, 2], [0, 2]])
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
clusters = dendrogram.clusters()
self.assertIn(set([0, 1, 2]), clusters)
for node in range(3, 10):
self.assertIn(set([node]), clusters)
def test_small_graph(self):
graph = nx.Graph()
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
self.assertEqual(list(dendrogram.clusters()), [])
graph.add_node(1)
dendrogram = GreedyAgglomerativeClusterer().cluster(graph)
self.assertEqual(list(dendrogram.clusters(1)[0]), [1])
self.assertEqual(list(dendrogram.clusters()[0]), [1])
def karate_clustering(self, *args, **kwargs):
return GreedyAgglomerativeClusterer().cluster(nx.karate_club_graph(),
*args, **kwargs)