<｜begin▁of▁sentence｜>### Instruction:
In a network of bi-directional data flows between three nodes, some connections only log the activity in one direction, resulting in an adjacency matrix representing the network as asymmetric. How can you make the adjacency matrix symmetric to accurately reflect that the connections between nodes allow for data flow in both directions, and retain the average weight when there's a discrepancy in the logged activity between two directions?
### Response:
import numpy as np
from graspologic.utils import symmetrize

# Create an asymmetric adjacency matrix
a = np.array([
   [0, 1, 1],
   [0, 0, 1],
   [0, 0, 1]])

# Symmetrize the adjacency matrix using the 'avg' method
symmetric_graph = symmetrize(a, method='avg')

print(symmetric_graph)
<|EOT|>
