<jupyter_start><jupyter_text>Не обращайте внимание, тут я просто ставил эксперементы над распредлением Пирсона.<jupyter_code>from numpy import random as r
from scipy.stats import multivariate_normal as mnorm
import numpy as np
import matplotlib.pyplot as plt

n1 = r.randn(100)
n2 = r.randn(100)
max_tick = int(max(n1.max(), n2.max())) + 1
min_tick = int(min(n1.min(), n2.min())) - 1
max_tick = max(abs(min_tick), max_tick)
ticks = np.linspace(-max_tick, max_tick, 2*max_tick + 1)
fig, ax = plt.subplots(figsize=(10, 10))
ax.add_artist(plt.Circle((0.0, 0.0), 2.45, color='blue', alpha=0.3))
ax.scatter(n1, n2, color='r', s=5)
ax.set_xticks(ticks)
ax.set_yticks(ticks)
plt.show()<jupyter_output><empty_output>