A library implemented that clusters into a modular structure with a nice feeling called Map equation.
For details, please refer to the following URL. https://www.mapequation.org/index.html https://mapequation.github.io/infomap/
The sample code didn't work when using infomap.
https://github.com/mapequation/infomap/blob/master/examples/python/example-networkx.py
The cause seems to be that the code is old.
(Referenced site) https://mapequation.github.io/infomap/
example-networkx.py
import networkx as nx
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import infomap
"""
Generate and draw a network with NetworkX, colored
according to the community structure found by Infomap.
"""
def findCommunities(G):
"""
Partition network with the Infomap algorithm.
Annotates nodes with 'community' id and return number of communities found.
"""
infomapWrapper = infomap.Infomap("--two-level --directed")
print("Building Infomap network from a NetworkX graph...")
for e in G.edges():
infomapWrapper.addLink(*e)
print("Find communities with Infomap...")
infomapWrapper.run();
communities = {}
for node in infomapWrapper.iterTree():
if node.isLeaf():
communities[node.physicalId] = node.moduleIndex()
nx.set_node_attributes(G, name='community', values=communities)
return infomapWrapper.numTopModules()
def drawNetwork(G):
# position map
pos = nx.spring_layout(G)
# community ids
communities = [v for k,v in nx.get_node_attributes(G, 'community').items()]
numCommunities = max(communities) + 1
# color map from http://colorbrewer2.org/
cmapLight = colors.ListedColormap(['#a6cee3', '#b2df8a', '#fb9a99', '#fdbf6f', '#cab2d6'], 'indexed', numCommunities)
cmapDark = colors.ListedColormap(['#1f78b4', '#33a02c', '#e31a1c', '#ff7f00', '#6a3d9a'], 'indexed', numCommunities)
# edges
nx.draw_networkx_edges(G, pos)
# nodes
nodeCollection = nx.draw_networkx_nodes(G,
pos = pos,
node_color = communities,
cmap = cmapLight
)
# set node border color to the darker shade
darkColors = [cmapDark(v) for v in communities]
nodeCollection.set_edgecolor(darkColors)
# Print node labels separately instead
for n in G.nodes():
plt.annotate(n,
xy = pos[n],
textcoords = 'offset points',
horizontalalignment = 'center',
verticalalignment = 'center',
xytext = [0, 2],
color = cmapDark(communities[n])
)
plt.axis('off')
# plt.savefig("karate.png ")
plt.show()
G=nx.karate_club_graph()
findCommunities(G)
drawNetwork(G)
I would appreciate it if you could let me know if there are any mistakes.
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