<｜begin▁of▁sentence｜>### Instruction:
A graph theorist is conducting an experiment to analyze the correlation between two ErdÅ‘s-RÃ©nyi (ER) graphs with the same set of vertices. They want to generate a pair of ER graphs where each graph has the same number of vertices and a specified probability of edge existence. Additionally, the pair of graphs should have a specified level of correlation between corresponding edges. Using the `graspologic.simulations.er_corr` function, how can the graph theorist generate a pair of correlated ER graphs with 5 vertices, an edge probability of 0.5, and a correlation of 0.3, while ensuring the graphs are undirected and do not contain self-loops?
### Response:
import numpy as np
from graspologic.simulations import er_corr

np.random.seed(2)
n = 5
p = 0.5
r = 0.3

# Generate two correlated ErdÅ‘s-RÃ©nyi graphs
G1, G2 = er_corr(n, p, r, directed=False, loops=False)

# Display the adjacency matrices
print('Graph G1:')
print(G1)
print('Graph G2:')
print(G2)
<|EOT|>
