def test_deepwalk():
"""
Testing the DeepWalk class.
"""
model = DeepWalk()
graph = nx.watts_strogatz_graph(100, 10, 0.5)
model.fit(graph)
embedding = model.get_embedding()
assert embedding.shape[0] == graph.number_of_nodes()
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
model = DeepWalk(dimensions=32)
graph = nx.watts_strogatz_graph(150, 10, 0.5)
model.fit(graph)
embedding = model.get_embedding()
assert embedding.shape[0] == graph.number_of_nodes()
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
def embed(self):
seed = np.random.randint(1e6)
model = DW(dimensions=self.dim_embedding,
walk_length=self.walk_length,
window_size=self.window_size,
seed=seed)
model.fit(self.graph.to_undirected())
self.embedding = model.get_embedding()
def deepwalk_embedding(Graph):
dw = DeepWalk(dimensions=256)
G = nx.convert_node_labels_to_integers(Graph)
dw.fit(G)
embeddings = dw.get_embedding()
return embeddings
else:
plt.show()
plt.close()
return
####################################################################################
# Main
####################################################################################
#
# DeepWalk
g = nx.newman_watts_strogatz_graph(100, 20, 0.05)
draw_graph(g)
model = DeepWalk()
model.fit(g)
embedding = model.get_embedding()
#
# Walklets
model = Walklets()
model.fit(g)
embedding = model.get_embedding()
#
# Community Detection with LabelPropagation
# Get graph
reader = GraphReader("facebook")
graph = reader.get_graph()
draw_graph(graph, 'F', 'F', '')
target = reader.get_target()
# Fit
model = LabelPropagation()
model.fit(graph)