how to randomly sample from a numpy array of probabilities?

Question

I have a numpy array like this:

arr = [.2 , .1, .2, .3, .2 ]

Now what I want to do is sample from this array, such that the probability i get a certain index is dependent on the probability at the index. So for example, the probability i get index 3 is .3

Anyone know any nifty ways to do this?

look at the p argument in numpy.random.choice

user8408080
– user8408080

2021-03-14 17:24:40 +00:00
Commented Mar 14, 2021 at 17:24 — user8408080
– user8408080, Commented Mar 14, 2021 at 17:24

Alex · Accepted Answer · 2021-03-14 17:26:47Z

6

You can do weighted sampling with a discrete probability distribution using np.random.choice by providing the sampling distribution as a parameter p:

import numpy as np

x = [.2 , .1, .2, .3, .2 ]

# sample from `x` 100 times according to `x`
n_samples = 100
samples = np.random.choice(x, n_samples, p=x)

answered Mar 14, 2021 at 17:26

Alex

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