<｜begin▁of▁sentence｜>### Instruction:
As a web developer creating an interactive data visualization tool for analyzing social networks, you've integrated the NetworkX library into your project. You've generated an Erdos-Renyi graph representing a social network with 100 individuals, where each pair of individuals is connected with a probability of 0.3. Now, you're tasked with implementing a feature that allows users to sample a subset of this network and analyze the communication patterns within it.

To achieve this, you plan to utilize the Metropolis-Hastings Random Walk Sampler, a method for sampling subgraphs from large networks. Your goal is to sample a subgraph containing 20 individuals and compute the communicability (the measure of how easily information can flow between nodes) between all pairs of individuals within this sampled subgraph.

Your task involves integrating the Metropolis-Hastings Random Walk Sampler from the NetworkX library into your web application and implementing the functionality to sample the subgraph and calculate communicability metrics for analysis.
### Response:
import networkx as nx
from littleballoffur import MetropolisHastingsRandomWalkSampler

G = nx.erdos_renyi_graph(n=100, p=0.3)

sampler = MetropolisHastingsRandomWalkSampler(20)

sampler_G = sampler.sample(G)

result = nx.communicability(sampler_G)

print(result)
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