<｜begin▁of▁sentence｜>### Instruction:
As a network analyst, you've been tasked with creating a visualization to showcase the connections and node relationships within a GNP random graph. This graph consists of 100 nodes, with each pair of nodes having a 5% probability of being connected. To achieve this, you are exploring the use of the GraphWave model to generate node embeddings that can be visualized within your network graph. Can you explain how to apply the GraphWave model with this specific graph to obtain node embeddings for visualization?
### Response:
import networkx as nx
from karateclub import GraphWave

# Step 1: Generate a graph
G = nx.gnp_random_graph(100, 0.05)

# Step 2: Initialize GraphWave model
model = GraphWave(sample_number=50, step_size=0.1, heat_coefficient=1.0, approximation=10, mechanism='approximate', switch=1000, seed=42)

# Step 3: Fit the model
model.fit(G)

# Step 4: Get the embeddings
embedding = model.get_embedding()

# Output the embedding
print(embedding)
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