<｜begin▁of▁sentence｜>### Instruction:
As a veterinary technician, I can assist veterinarians, researchers, or doctors in veterinary care, treatments, or surgeries for animals, pets, or livestock. This may involve providing support, offering assistance, or performing technical services such as animal handling, restraint, or anesthesia, collecting samples or specimens, administering medications or treatments, and maintaining records or inventories in veterinary clinics, animal hospitals, shelters, or research labs. Additionally, I may educate clients or pet owners on animal care, nutrition, or health issues. Now, if we have a case where a network of animal habitats has been mapped and stored in a file called 'network.gml', I would be tasked with using the latest Leiden algorithm in igraph to detect the communities of animals within these habitats and visualize the results using NetworkX and matplotlib.
### Response:
from igraph import Graph

# Load a graph
file_path = 'network.gml'
graph = Graph.Read_GML(file_path)

# Detect the community structure using the Leiden algorithm with default modularity setting
communities = graph.community_leiden()

# Print the membership of each vertex
print(communities.membership)

# Optional: To visualize the detected communities using NetworkX and matplotlib
import networkx as nx
import matplotlib.pyplot as plt

# Convert igraph to NetworkX graph
nx_graph = nx.Graph(graph.get_edgelist())

# Create a color mapping based on the community membership
colors = [communities.membership[i] for i in range(len(communities.membership))]

# Draw the network
nx.draw(nx_graph, node_color=colors, with_labels=True)
plt.show()
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