<｜begin▁of▁sentence｜>### Instruction:
As a genetic counselor, I often work with data related to neural networks and may need to analyze them for various purposes. Today, I'm tasked with analyzing the neural network of C. elegans obtained from a GML file named celegansneural.gml to identify different communities within the network using the Louvain method in cdlib. Additionally, I need to calculate the number of edges internal to each detected community. This analysis will provide valuable insights into the organization and connectivity patterns of the neural network, which can have implications for understanding genetic conditions and related implications for health and reproduction.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Create a graph from the C. elegans neural network dataset
g = nx.read_gml('celegansneural.gml')

# Perform community detection using the Louvain method
communities = algorithms.louvain(g)

# Compute the number of edges internal to each community
e_internal = evaluation.edges_inside(g, communities)

print(e_internal)
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