AKF

import numpy as np
import matplotlib.pyplot as plt

# generate some data
x = np.arange(0.,50.,1)
#y = np.sin(x)
y = np.random.uniform(size=30)
yunbiased = y-np.mean(y)
print (yunbiased)
ynorm = np.sum(yunbiased**2)
acor = np.correlate(yunbiased, yunbiased, „same“)/ynorm
# use only second half
acor = acor[len(acor)//2:]

print (acor)
plt.plot(acor)

plt.show()