<｜begin▁of▁sentence｜>### Instruction:
A network researcher has a weighted adjacency matrix X representing the connectivity of a network with 10 nodes. These nodes are divided into three categories labeled 'A', 'B', and 'C'. The researcher wants to visually inspect the distribution of edge weights within each node category. How can they use the edgeplot function from graspologic to create a plot that displays the edge weight distribution for each node category, ensuring that the plot only includes nonzero weights, is appropriately sized, and is styled for a presentation?
### Response:
import numpy as np
import matplotlib.pyplot as plt
from graspologic.plot import edgeplot

# Generating a synthetic adjacency matrix as an example
np.random.seed(42)
X = np.random.rand(10, 10)

# Simulating some labels for the nodes
labels = np.array(["A", "A", "A", "B", "B", "B", "C", "C", "C", "C"])

# Plot the edge weight distribution
ax = edgeplot(X, labels=labels, nonzero=True, title='Edge Weight Distribution', context='talk', font_scale=1.2, figsize=(10, 7), palette='Set1')
plt.show()
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