<｜begin▁of▁sentence｜>### Instruction:
Given a degree sequence [3, 2, 1, 1] for node set A and a probability of 0.05 for adding a new node to set B at each step, create a bipartite graph using the preferential attachment model. Additionally, identify and display the nodes in sets A and B, as well as the list of edges of the created bipartite graph.
### 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 each time
p = 0.05

# Create a bipartite preferential attachment graph
B = bipartite.preferential_attachment_graph(aseq, p, seed=42)

# Get the nodes from set A and B
A_nodes = {n for n, d in B.nodes(data=True) if d['bipartite'] == 0}
B_nodes = set(B) - A_nodes

# Display the sets of nodes and the edges
print('Nodes in set A:', A_nodes)
print('Nodes in set B:', B_nodes)
print('Edges:', list(B.edges()))
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