<｜begin▁of▁sentence｜>### Instruction:
As a Film Producer overseeing the production of a new blockbuster movie, you are tasked with ensuring that the ensemble cast works harmoniously together to create a successful film. To achieve this, you decide to analyze the dynamics within the cast members using advanced network analysis techniques. Utilizing the hep-th.gml file containing details of cast interactions, you aim to employ the Louvain and Leiden community detection algorithms available through the cdlib API to identify distinct groups of actors who collaborate effectively on set.

In addition, you plan to compute the Overlapping Normalized Mutual Information (LFK version) between the partitions generated by the Louvain and Leiden algorithms. This will allow you to evaluate the similarity between the identified actor communities and gain insights into how cohesive and interconnected they are in the film project. By leveraging these cutting-edge techniques, you aim to optimize the chemistry among cast members and elevate the overall performance of the ensemble in your upcoming movie production.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Load the high-energy theory graph
G = nx.read_gml('hep-th.gml')

# Perform community detection using the Louvain method
louvain_communities = algorithms.louvain(G)

# Perform community detection using the Leiden method
leiden_communities = algorithms.leiden(G)

# Calculate Overlapping Normalized Mutual Information
onmi = evaluation.overlapping_normalized_mutual_information_LFK(louvain_communities, leiden_communities)
print(onmi)
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