<｜begin▁of▁sentence｜>### Instruction:
Given a graph whose edge set is [(0,1), (0,2), (1,3), (2,3)] and nodes belong to communities {0:0, 1:0, 2:1, 3:0}, how can we compute the resource allocation index that takes the community structure into account using NetworkX for the node pair (0, 3)?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(0,1), (0,2), (1,3), (2,3)])

# Add community information to the nodes
G.nodes[0]['community'] = 0
G.nodes[1]['community'] = 0
G.nodes[2]['community'] = 1
G.nodes[3]['community'] = 0

# Compute the resource allocation index considering community information
preds = nx.ra_index_soundarajan_hopcroft(G, [(0, 3)])

# Print computed scores
for u, v, p in preds:
    print(f'({u}, {v}) -> {p:.8f}')
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