def test_gl2vec():
"""
Test the GL2Vec embedding.
"""
graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)]
model = GL2Vec()
model.fit(graphs)
embedding = model.get_embedding()
assert embedding.shape[0] == len(graphs)
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
graphs = [nx.newman_watts_strogatz_graph(150, 5, 0.3) for _ in range(100)]
model = GL2Vec(dimensions=16)
model.fit(graphs)
embedding = model.get_embedding()
assert embedding.shape[0] == len(graphs)
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
g = nx.newman_watts_strogatz_graph(200, 20, 0.05) x = np.random.uniform(0, 1, (200, 200)) model = TADW() model.fit(g, x) #----------------- # GL2Vec example #----------------- graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)] model = GL2Vec() model.fit(graphs) model.get_embedding() #-------------- # FGSD example #-------------- graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)] model = FGSD() model.fit(graphs) model.get_embedding()
