<｜begin▁of▁sentence｜>### Instruction:
As a sustainability consultant, you've been tasked with analyzing the Power Grid Graph, which is stored in a GML file called power.gml. You need to use the Louvain method to identify communities within the power grid network and then calculate the Erdos-Renyi modularity for the detected communities. This analysis will provide valuable insights into the network's structure and connectivity, helping to inform decisions related to sustainable energy distribution and infrastructure planning.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Read the power grid graph
G = nx.read_gml('power.gml')

# Perform community detection using the Louvain algorithm
communities = algorithms.louvain(G)

# Compute the Erdos-Renyi modularity of the detected communities
erdos_renyi_mod = evaluation.erdos_renyi_modularity(G, communities)

# Output the Erdos-Renyi modularity value
print(erdos_renyi_mod)
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