random.seed() does not work with np.random.choice()

Question

So i’m trying to generate a list of numbers with desired probability; the problem is that random.seed() does not work in this case.

M_NumDependent = []

for i in range(61729):
    random.seed(2020)
    n = np.random.choice(np.arange(0, 4), p=[0.44, 0.21, 0.23, 0.12])
    M_NumDependent.append(n)
print(M_NumDependent)

the desired output should be the same if the random.seed() works, but the output is different everytime i run it. Does anyone know if there’s a function does the similar job of seed() for np.random.choice()?

Asked By: PiCubed

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Source

Answer 1

You are accidentally setting random.random.seed() instead of numpy.random.seed().

Instead of

random.seed(2020)

use

import numpy as np 


np.random.seed(2020)

and your results will always be reproducible.

Answered By: Giorgos Myrianthous

Answer 2

numpy uses its own pseudo random generator. You can seed the Numpy random generator with np.random.seed(..) [numpy-doc]:

np.random.seed(2020)

For example:

>>> np.random.seed(2020)
>>> np.random.choice(np.arange(0, 4), p=[0.44, 0.21, 0.23, 0.12])
3
>>> np.random.seed(2020)
>>> np.random.choice(np.arange(0, 4), p=[0.44, 0.21, 0.23, 0.12])
3
>>> np.random.seed(2020)
>>> np.random.choice(np.arange(0, 4), p=[0.44, 0.21, 0.23, 0.12])
3
>>> np.random.choice(np.arange(0, 4), p=[0.44, 0.21, 0.23, 0.12])
2

As you can see we each time pick 3 whereas if we do not seed the random generator, 2 is the next item after 3.

Answered By: Willem Van Onsem

random.seed() does not work with np.random.choice()

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