Python numpy generate an array of random binary values according to probabilities

Question

Is there any way in which I can do the following in a single line? Suppose I have an array of probabilities,

p=np.array([0.75, 0.63, 0.33, 0.25, 0.47])

where each value corresponds to the probability of selecting a 1 and (1-p) corresponds to probability of selecting 0, i.e., 0.75 is the probability of selecting 1, and 1 - 0.75 is probability of selecting 0, 0.63 for selecting 1, and 1 - 0.63 for selecting 0 and so on. Is there any easier way for me to do the following, hopefully without a loop?

values = np.empty(p.shape)
for i, prob in enumerate(p):
    values[i] = np.random.binomial(1, prob)

I know it can be done using map but is there a way to directly do it in numpy?

vahndi · Accepted Answer · 2016-01-23 01:14:42Z

4

values = np.random.binomial(1, p)

answered Jan 23, 2016 at 1:14

vahndi

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2 Comments

Aditya369 Over a year ago

I never knew it could be used with an array of probabilities. I should have read the documentation better. I'm sorry. Thanks a lot.

vahndi Over a year ago

No worries. Not your fault - the documentation in ipython specifies it should be a float but most operations in numpy are designed to be broadcastable so it's worth giving it a try even if the docs say something else.

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