<｜begin▁of▁sentence｜>### Instruction:
Given two very similar adjacency matrices A and B representing connected graphs, and knowing that vertex 0 in graph A is matched with vertex 0 in graph B, how would you apply the Vertex Nomination via Seeded Graph Matching algorithm to nominate the vertices in graph B that best match vertex 0 of graph A, based on probability of matching?
### Response:
import numpy as np
from graspologic.nominate import VNviaSGM

# Synthetic adjacency matrices for two similar graphs
A = np.array([[0, 1, 0],
              [1, 0, 1],
              [0, 1, 0]])
B = np.array([[0, 1, 0],
              [1, 0, 1],
              [0, 1, 0]])

# Vertex of Interest (VOI) and known seed match
voi = 0
seeds = [[0], [0]]

# Instantiate and run Vertex Nomination via Seeded Graph Matching
vn_sgm = VNviaSGM() # default parameters are used here
vn_sgm.fit(A, B, voi, seeds)
nomination_list = vn_sgm.nomination_list_

# Print out the nomination list
print('Nomination list (vertex, probability):', nomination_list)
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