<｜begin▁of▁sentence｜>### Instruction:
Given an adjacency matrix of an unweighted graph where the nodes represent entities and the edges represent connections between them, how can we modify the diagonal of this matrix such that it reflects the average degree (or average sum of edge weights for a weighted graph) of each corresponding node's connections, potentially multiplied by a scalar weight value?
### Response:
import numpy as np
from graspologic.utils import augment_diagonal

# Example adjacency matrix for an unweighted graph
a = np.array([
   [0, 1, 1],
   [1, 0, 0],
   [1, 0, 0]
])

# Use augment_diagonal to add average degrees to the diagonal
augmented_matrix = augment_diagonal(a, weight=1)
print(augmented_matrix)
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