<｜begin▁of▁sentence｜>### Instruction:
As a network analyst using the networkx library, I can assist you in applying the community_infomap function from the igraph library to analyze the community structure of a network stored in the 'network.gml' file. This method utilizes the Infomap algorithm to identify communities based on edge and vertex weights, as well as a specified number of trials.

Imagine you are a therapist providing counseling services to a diverse group of individuals facing various mental health challenges. Just like tailoring therapeutic approaches to the specific needs and preferences of your clients to promote personal growth and well-being, the community_infomap function can be tailored to analyze the network's structure and uncover hidden communities, ultimately enhancing your understanding of the connections and interactions within the network.
### Response:
from igraph import Graph
import igraph as ig

# Read the graph from file
g = ig.read('network.gml')

# Find the community structure using the Infomap method
infomap_communities = g.community_infomap(edge_weights='weight', vertex_weights='node_weight', trials=10)

# Print the VertexClustering object and the codelength
print(infomap_communities)
print('Codelength:', infomap_communities.codelength)
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