def setUp(self):
curdir = os.path.dirname(__file__)
pos_train = os.path.join(curdir, 'data/ppismall/pos_train_edges')
pos_train = os.path.abspath(pos_train)
training_graph = CSFGraph(pos_train)
# obtain data needed to build model
worddictionary = training_graph.get_node_to_index_map()
reverse_worddictionary = training_graph.get_index_to_node_map()
# initialize n2v object
p, q = 1, 1
self.number_of_nodes_in_training = training_graph.node_count()
self.n2v_graph = N2vGraph(csf_graph=training_graph, p=p, q=q)
# generate random walks
self.walk_length = 10
self.num_walks = 5
self.walks = self.n2v_graph.simulate_walks(num_walks=self.num_walks, walk_length=self.walk_length)
# walks is now a list of lists of ints
# build cbow model
self.cbow = ContinuousBagOfWordsWord2Vec(self.walks,
worddictionary=worddictionary,
reverse_worddictionary=reverse_worddictionary,
num_epochs=2)
self.cbow.train()
def test_count_nodes_legacy_edge_file(self):
g = CSFGraph(edge_file=self.legacy_edge_file)
self.assertEqual(3, g.node_count())