<｜begin▁of▁sentence｜>### Instruction:
Suppose you have a small network of four vertices, where vertices are connected with weighted edges (e.g., (0, 1, 1), (1, 2, 1), (2, 0, 1), (1, 3, 10)). How would you use the adjacency_spectral_embedding from graspologic to find a lower dimensional representation of this network's structure, and how would you print the embedding for each node?
### Response:
import networkx as nx
from graspologic.pipeline import adjacency_spectral_embedding

# Create a weighted graph
G = nx.Graph()
G.add_weighted_edges_from([(0, 1, 1), (1, 2, 1), (2, 0, 1), (1, 3, 10)])

# Run adjacency spectral embedding
embedding = adjacency_spectral_embedding(G, dimensions=2)

# printing the embedding for each node
for node_id, node_embedding in enumerate(embedding):
  print(f'Node {node_id}: {node_embedding}')
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