<｜begin▁of▁sentence｜>### Instruction:
Given an adjacency matrix of a graph, where the weights of the edges represent the strength of the connections between nodes, how can you transform the adjacency matrix using the 'pass_to_ranks' function from 'graspologic.utils' so that the edge weights are rescaled according to their relative rank within the graph?
### Response:
import numpy as np
import graspologic.utils

# Given an adjacency matrix for a graph
adjacency_matrix = np.array([
    [0, 1, 3],
    [1, 0, 2],
    [3, 2, 0]
])

# Rescale edge weights based on their relative rank
ptr_matrix = graspologic.utils.pass_to_ranks(adjacency_matrix)

# Print the resulting pass-to-ranks matrix
print(ptr_matrix)
<|EOT|>
