<｜begin▁of▁sentence｜>### Instruction:
Suppose we have a graph with nodes that belong to certain communities. Two nodes (0 and 1) belong to community 0, node 2 belongs to community 1, and node 3 belongs to community 0. Edges in the graph connect nodes as follows: (0,1), (0,2), (1,3), (2,3). How can we compute the resource allocation index for the pair of nodes (0,3) taking into consideration their community information using NetworkX?
### 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 resource allocation index using community information for specified pairs of nodes
preds = nx.ra_index_soundarajan_hopcroft(G, [(0, 3)])
for u, v, p in preds:
    print(f'({u}, {v}) -> {p:.8f}')

# Output will be:
# (0, 3) -> 0.50000000
<|EOT|>
