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"""Multiple MC to show how it can be bad."""
import numpy as np
import matplotlib.pyplot as plt
rng = np.random.default_rng()
n_sample = 256
dim = 2
sample = {}
# MC
sample['MC 1'] = rng.random((n_sample, dim))
sample["MC 2"] = rng.random((n_sample, dim))
fig, axs = plt.subplots(1, 2, figsize=(8, 4))
for i, kind in enumerate(sample):
axs[i].scatter(sample[kind][:, 0], sample[kind][:, 1])
axs[i].set_aspect('equal')
axs[i].set_xlabel(r'$x_1$')
axs[i].set_ylabel(r'$x_2$')
plt.tight_layout()
plt.show()
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