<｜begin▁of▁sentence｜>### Instruction:
Given the neural network of the Caenorhabditis elegans, which you can read from a GML file named celegansneural.gml, can you use both the Louvain and Leiden algorithms to perform community detection? And can you compute the Overlapping Normalized Mutual Information using the LFK method to assess the similarity of the two resulting community structures?
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Create a graph from a GML file
G = nx.read_gml('celegansneural.gml')

# Perform community detection using two different algorithms
louvain_communities = algorithms.louvain(G)
leiden_communities = algorithms.leiden(G)

# Calculate the Overlapping Normalized Mutual Information (LFK) between the two partitions
onmi_LFK = evaluation.overlapping_normalized_mutual_information_LFK(louvain_communities, leiden_communities)

print(onmi_LFK.score)
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