def test_nx2igraph_with_labels(nx_graph):
ig_graph = pyintergraph.nx2igraph(nx_graph)
nodemap = {v.index: v["name"] for v in ig_graph.vs()}
assert list(nx_graph.nodes()) == [v["name"] for v in ig_graph.vs()]
assert [e for e in nx_graph.edges()] == \
[(nodemap[e.tuple[0]], nodemap[e.tuple[1]]) for e in ig_graph.es()]
def test_round_robin_ig(ig_graph):
graph_tool_graph = pyintergraph.igraph2gt(ig_graph,
labelname="somelabelname")
nx_graph = pyintergraph.gt2nx(graph_tool_graph, labelname="somelabelname")
reversed_ig_graph = pyintergraph.nx2igraph(nx_graph)
assert list(v.index for v in ig_graph.vs()) == list(
v.index for v in reversed_ig_graph.vs())
assert list(e.tuple for e in ig_graph.es()) == list(
e.tuple for e in reversed_ig_graph.es())
assert ig_graph.edge_attributes() == reversed_ig_graph.edge_attributes()
assert set(ig_graph.vertex_attributes()).add("name") == set(
reversed_ig_graph.vertex_attributes()).add("name")
assert type(ig_graph) == type(reversed_ig_graph)
edge_labels = {}
count = 0
for i, origin_state in enumerate(new_data):
for j, destination_state in enumerate(origin_state):
rate = new_data[i][j]
if rate > 0:
count = count + 1
try:
G.add_edge(indices[i], indices[j], weight=rate)
except:
pdb.set_trace()
print('ol')
matrix = nx.to_scipy_sparse_matrix(G)
for inflation in [i / 10 for i in range(15, 26)]:
result = mc.run_mcl(matrix, inflation=inflation)
clusters = mc.get_clusters(result)
Q = mc.modularity(matrix=result, clusters=clusters)
print("inflation:", inflation, "modularity:", Q)
#communities_generator = community.girvan_newman(G)
#top_level_communities = next(communities_generator)
result = mc.run_mcl(matrix) # run MCL with default parameters
clusters = mc.get_clusters(result)
pdb.set_trace()
GG = pyintergraph.nx2igraph(G, labelname="node_label")
clusters = nx.clustering(G, weight='weight')
def communities(self, graph):
return self.grouping(
leiden.find_partition(pyintergraph.nx2igraph(graph),
leiden.ModularityVertexPartition))
def test_nx2igraph_raises(wrong_input):
with pytest.raises(TypeError):
g = pyintergraph.nx2igraph(wrong_input)