<｜begin▁of▁sentence｜>### Instruction:
Given a degree sequence [3, 2, 1, 1] for node set A and a probability of 0.5 that a new bottom node is added (node set B), create a bipartite graph using the preferential attachment model. What does the resulting graph's edge set look like, and which bipartite set does each node belong to?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Degree sequence for node set A
aseq = [3, 2, 1, 1]

# Probability that a new bottom node is added
p = 0.5

# Create a bipartite graph with a preferential attachment model from a given single degree sequence
B = bipartite.preferential_attachment_graph(aseq, p, seed=42)

# Print the edges of the graph
print(B.edges())

# Print the nodes with their 'bipartite' attribute
for n, d in B.nodes(data=True):
    print(f'Node {n}, Bipartite Set: {d['bipartite']}')
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