<｜begin▁of▁sentence｜>### Instruction:
Imagine you're examining a novel visualization of viral transmission pathways in a population, where this transmission network is represented as a barbell graph resembling two distinct viral strain clusters of three individuals each. These strain clusters are linked by a single transmission event. Considering each cluster as a separate community within your epidemiological model, you are interested in assessing the connectivity strength within and between these communities to better understand the potential for spillover events. To quantify this aspect, you're looking to calculate the modularity of this specific partition of the network. How would you proceed to evaluate the modularity, keeping in mind that the two communities are represented by the two complete graphs of the barbell graph?
### Response:
import networkx as nx

# Create a barbell graph
G = nx.barbell_graph(3, 0)

# Define two communities
communities = [{0, 1, 2}, {3, 4, 5}]

# Calculate the modularity of the given partition of the graph
modularity = nx.community.modularity(G, communities)

print('The modularity of the given partition is:', modularity)
<|EOT|>
