<｜begin▁of▁sentence｜>### Instruction:
Given two graphs represented by adjacency matrices `A` and `B` where certain vertices are known to match (these are the seeds), can you apply the Vertex Nomination via Seeded Graph Matching (VNviaSGM) technique to rank the vertices in graph `B` that are most likely to match a vertex of interest (VOI) in graph `A`? The method should provide a nomination list with the probabilities that a VOI matches vertices in graph `B`.
### Response:
import numpy as np
from graspologic.nominate import VNviaSGM
import networkx as nx

# Create two simple graphs with known isomorphism
G1 = nx.Graph()
G2 = nx.Graph()
G1.add_edges_from([(0, 1), (0, 2), (1, 2)])
G2.add_edges_from([(3, 4), (3, 5), (4, 5)])

# Adjacency matrices
A = nx.adjacency_matrix(G1).toarray()
B = nx.adjacency_matrix(G2).toarray()

# Known matching vertices (seeds)
seeds_A = [0, 1]
seeds_B = [3, 4]

# Vertex of Interest (VOI)
voi = 2

# Initialize the VNviaSGM class
vnviasgm = VNviaSGM(order_voi_subgraph=1, order_seeds_subgraph=1, n_init=100)

# Fit the model and predict
vnviasgm.fit(A, B, voi, [seeds_A, seeds_B])
nomination_list = vnviasgm.nomination_list_
print('Nomination list:', nomination_list)
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