<｜begin▁of▁sentence｜>### Instruction:
As an insurance adjuster, let's consider a scenario where you're tasked with evaluating the risk exposure of a network of 200 policyholders. This network is modeled using an Erdos-Renyi graph with a probability parameter of 0.05, indicating the likelihood of connections between policyholders.

To assess the potential impact of a specific risk factor on a subset of policyholders, you need to sample a representative subgraph from this network. You're required to use the DiffusionSampler tool to sample a subgraph comprising 50 policyholders. Once you have this sampled subgraph, you'll perform an analysis to understand the propagation of risks and the potential implications for the insurance coverage and settlement amounts.

Your task involves integrating the DiffusionSampler API into your workflow to efficiently sample the subgraph and then conduct the necessary analysis to make informed decisions regarding insurance coverage and settlement for the policyholders involved.
### Response:
import networkx as nx
from littleballoffur import DiffusionSampler

G = nx.erdos_renyi_graph(n=200, p=0.05)

sampler = DiffusionSampler(number_of_nodes=50, seed=10)

sampler_G = sampler.sample(G)

# Perform some operation using the sampled graph
result = some_operation(sampler_G)

print(result)
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