<｜begin▁of▁sentence｜>### Instruction:
Given a graph with weighted edges [(0, 1, 2.5), (1, 2, 3.5), (0, 2, 1.5)], how can you create and display a SciPy sparse adjacency matrix using the NetworkX function `to_scipy_sparse_array`?
### Response:
import networkx as nx
from scipy.sparse import csr_matrix

# Create a NetworkX graph
G = nx.Graph()
G.add_weighted_edges_from([(0, 1, 2.5), (1, 2, 3.5), (0, 2, 1.5)])

# Generate the sparse adjacency matrix
A = nx.to_scipy_sparse_array(G, nodelist=[0, 1, 2], dtype=float, weight='weight', format='csr')

# Convert it to a dense format and print it
print(A.toarray())
<|EOT|>
