<｜begin▁of▁sentence｜>### Instruction:
Given a graph which you can read from 'network_graph.gml', assuming the graph has an edge attribute 'weight' that indicates the strength of the connection, and you want to discover the community structure by using the random walk method of Latapy & Pons with 4 steps for the random walks, how can you use the 'community_walktrap' function in igraph and calculate the modularity score of the resulting clustering?
### Response:
import igraph as ig

# Read graph from a file
g = ig.read('network_graph.gml')

# Run the community_walktrap algorithm
# Assuming 'weight' is the edge attribute representing weights
# Here we perform 4 steps for the random walks
dendrogram = g.community_walktrap(weights='weight', steps=4)

# Convert the dendrogram into a flat clustering and
# then calculate the modularity score for the clustering
clusters = dendrogram.as_clustering()
modularity_score = g.modularity(clusters, weights='weight')

# Print the cluster assignments and modularity score
print(clusters)
print(f'Modularity Score: {modularity_score}')
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