Sample from a multinormal distribution when given the correlation coefficient

multinormal.py

import numpy as np

# given
mu_x = 10
mu_y = 20
sigma_x = 2
sigma_y = 3
corr = 0.3
# ---

mu = [mu_x, mu_y]
cov = [[sigma_x**2, corr * sigma_x * sigma_y], [corr * sigma_x * sigma_y, sigma_y**2]]
n_samples = 10_000
samples = np.random.multivariate_normal(mu, cov, size=n_samples)

hat_corr = np.corrcoef(samples[:, 0], samples[:, 1])[0, 1]
print(hat_corr - corr) # Should be close to zero