def test_graph2vec():
"""
Test the Graph2Vec embedding.
"""
graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)]
model = Graph2Vec()
model.fit(graphs)
embedding = model.get_embedding()
assert embedding.shape[0] == len(graphs)
assert embedding.shape[1] == model.dimensions
graphs = []
for _ in range(50):
graph = nx.newman_watts_strogatz_graph(50, 5, 0.3)
nx.set_node_attributes(graph, {j: str(j)
for j in range(50)}, "feature")
graphs.append(graph)
model = Graph2Vec(attributed=True)
model.fit(graphs)
embedding = model.get_embedding()
assert embedding.shape[0] == len(graphs)
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
reader = GraphReader("facebook")
graph = reader.get_graph()
target = reader.get_target()
#-------------------------------
# Graph2Vec attributed example
#-------------------------------
graphs = []
for i in range(50):
graph = nx.newman_watts_strogatz_graph(50, 5, 0.3)
nx.set_node_attributes(graph, {j: str(j) for j in range(50)}, "feature")
graphs.append(graph)
model = Graph2Vec(attributed=True)
model.fit(graphs)
model.get_embedding()
#-------------------
# Graph2Vec example
#-------------------
graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(1000)]
model = Graph2Vec()
model.fit(graphs)
model.get_embedding()
#-----------------------------------
# Graph reader example
#-----------------------------------
reader = GraphReader("facebook")
graphs = reader.get_graph()
target = reader.get_target()
#-----------------------------------
# Graph2Vec example
#-----------------------------------
graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(1000)]
model = Graph2Vec()
model.fit(graphs)
model.get_embedding()
#-----------------------------------
# BoostNE example
#-----------------------------------
g = nx.newman_watts_strogatz_graph(100, 20, 0.05)
model = BoostNE()
model.fit(g)
model.get_embedding()