<｜begin▁of▁sentence｜>### Instruction:
Given a probability p, how can you generate a binary Erdos Renyi graph with n vertices where each possible edge is included with the probability p independently from other edges, using graspologic's er_np function?
### Response:
import numpy as np
from graspologic.simulations import er_np

np.random.seed(42)
n = 10  # Number of vertices
p = 0.3  # Probability of edge existence

# Sample a binary Erdos Renyi (n, p) graph
A = er_np(n, p)
print(A)
<|EOT|>
