<｜begin▁of▁sentence｜>### Instruction:
Imagine you're assessing the stability and interconnectedness of a suspension bridge, where the "top" nodes {1, 2, 3, 4} symbolize the main cables and the "bottom" nodes {5, 6, 7, 8} represent the vertical suspenders. In this structural network, the connections between the cables and suspenders are vital to distribute the load of the bridge equally. To better understand the importance of each main cable in the load-distribution network, you would like to evaluate the degree centrality for the set of "top" nodes, essentially quantifying the direct lines of support each cable has to the suspenders. Using the NetworkX library as a tool, how would you calculate this structural parameter for the nodes representing the main cables?
### Response:
import networkx as nx
from networkx.algorithms import bipartite

# Create a bipartite graph
B = nx.Graph()
B.add_edges_from([(1, 5), (1, 6), (2, 5), (2, 6), (3, 7), (4, 8)])

# Define top and bottom nodes
top_nodes = {1, 2, 3, 4}
bottom_nodes = {5, 6, 7, 8}

# Considering top_nodes as one part of the bipartite graph
# Calculate the degree centrality of nodes in top_nodes
centrality = bipartite.degree_centrality(B, top_nodes)
print(centrality)
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