casuality-1.py

import numpy as np
import matplotlib.pyplot as plt
from sklearn.linear_model import LinearRegression

sample = 200
X = np.random.uniform(-1, 1, sample)
N = np.random.uniform(-1, 1, sample)
Y = X + N

line_fitter = LinearRegression()
line_fitter.fit(np.expand_dims(X, axis = 1), Y)
reverse_fitter = LinearRegression()
reverse_fitter.fit(np.expand_dims(Y, axis = 1), X)

plt.plot(X, Y, 'o')
plt.plot(X, line_fitter.predict(np.expand_dims(X, axis = 1)))
plt.show()

plt.plot(X, Y - line_fitter.predict(np.expand_dims(X, axis = 1)), 'o')
plt.plot([-1, 1], [0, 0])
plt.show()

plt.plot(X, Y, 'o')
plt.plot(reverse_fitter.predict(np.expand_dims(Y, axis = 1)), Y)
plt.show()

plt.plot(X - reverse_fitter.predict(np.expand_dims(Y, axis = 1)), Y, 'o')
plt.plot([-1, 1], [0, 0])
plt.show()