<｜begin▁of▁sentence｜>### Instruction:
Given a NetworkX graph representing a karate club, how can you use the NetLSD model to calculate the heat kernel trace of the normalized Laplacian matrix over a vector of time scales and obtain the graph's embedding?
### Response:
import networkx as nx
from karateclub import NetLSD
import matplotlib.pyplot as plt

# Generate a sample graph
G = nx.karate_club_graph()

# Create the NetLSD model with desired parameters
model = NetLSD(scale_min=-2.0, scale_max=2.0, scale_steps=250, scale_approximations=200, seed=42)

# Fit the model to the graph
model.fit([G])

# Get the graph embedding
embedding = model.get_embedding()
print(embedding)
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