def test_GEMSEC():
"""
Test the GEMSEC procedure.
"""
graph = nx.newman_watts_strogatz_graph(100, 5, 0.3)
model = GEMSEC()
model.fit(graph)
memberships = model.get_memberships()
indices = [k for k, v in memberships.items()].sort()
nodes = [node for node in graph.nodes()].sort()
assert graph.number_of_nodes() == len(memberships)
assert indices == nodes
assert type(memberships) == dict
embedding = model.get_embedding()
assert embedding.shape[0] == graph.number_of_nodes()
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
graph = nx.newman_watts_strogatz_graph(150, 5, 0.3)
model = GEMSEC(dimensions=4)
model.fit(graph)
memberships = model.get_memberships()
indices = [k for k, v in memberships.items()].sort()
nodes = [node for node in graph.nodes()].sort()
assert graph.number_of_nodes() == len(memberships)
assert indices == nodes
assert type(memberships) == dict
embedding = model.get_embedding()
assert embedding.shape[0] == graph.number_of_nodes()
assert embedding.shape[1] == model.dimensions
assert type(embedding) == np.ndarray
from karateclub.graph_embedding import Graph2Vec, FGSD, GL2Vec, SF, NetLSD, GeoScattering from karateclub.node_embedding.attributed import BANE, TENE, TADW, FSCNMF, SINE, MUSAE from karateclub.node_embedding.structural import GraphWave, Role2Vec from karateclub.node_embedding.meta import NEU from karateclub.dataset import GraphReader, GraphSetReader #---------------- # GEMSEC example #---------------- g = nx.newman_watts_strogatz_graph(100, 20, 0.05) model = GEMSEC() model.fit(g) memberships = model.get_memberships() #------------------------------- # Geometric Scattering example #------------------------------- graphs = [nx.newman_watts_strogatz_graph(50, 5, 0.3) for _ in range(100)] model = GeoScattering() model.fit(graphs) embedding = model.get_embedding() #-------------------- # NodeSketch example
"""GEMSEC example.""" import networkx as nx from karateclub.community_detection.non_overlapping import GEMSEC g = nx.newman_watts_strogatz_graph(100, 20, 0.05) model = GEMSEC() model.fit(g)