<｜begin▁of▁sentence｜>### Instruction:
Given an adjacency matrix representing a graph and a subset of seed vertices indices, how can the SpectralVertexNomination class in graspologic be used to rank all the other vertices in order of their relation to members of the seed set?
### Response:
import numpy as np
from graspologic.nominate import SpectralVertexNomination
from graspologic.embed import AdjacencySpectralEmbed

# Given adjacency matrix for the graph
adjacency_matrix = np.array([
    [0, 1, 1, 0],
    [1, 0, 1, 0],
    [1, 1, 0, 1],
    [0, 0, 1, 0]
])

# Seed indices
seed_indices = np.array([0, 1])

# Instantiate the SpectralVertexNomination with Adjacency Spectral Embedding
svn = SpectralVertexNomination(input_graph=True, embedder='ASE', n_neighbors=3)

# Fit and predict
nomination_list, distance_matrix = svn.fit_predict(X=adjacency_matrix, y=seed_indices)

print('Nomination List:\n', nomination_list)
print('Distance Matrix:\n', distance_matrix)
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