Generating random numbers with weighted probabilities in python

Question

Given a positive integer array a, the goal is to generate 5 random numbers based on the weight they have in the array.

For example:

a = [2,3,4,4,4,4,4,6,7,8,9]

In this case the number 4 has appeared 5 times, in this case the number 4 should have the probability of 5/11 to appear.

No numbers should be repeated.

Answer 1

Given a, an array of positive integers, you'll first need to compute the frequency of each integer. For example, using bincount:

>>> a = [2,3,4,4,4,4,4,4,5,6,7,8,9,4,9,2,3,6,3,1]
>>> b = np.bincount(a)

b tells you the frequency of each integer in a. The corresponding set of weights is therefore the array b/len(a). Using np.random.choice with these weights and replace=False should then give you what you need:

>>> np.random.choice(np.arange(len(b)), 5, p=b/len(a), replace=False)
array([5, 9, 4, 3, 8])
>>> np.random.choice(np.arange(len(b)), 5, p=b/len(a), replace=False)
array([7, 4, 6, 9, 1])
>>> np.random.choice(np.arange(len(b)), 5, p=b/len(a), replace=False)
array([3, 7, 4, 9, 6])

If you're not working with only positive integers, or if you are working with large positive integers, @user2357112 points out in the comments below that np.unique provides another solution. Here you'd write:

>>> choices, counts = np.unique(a, return_counts=True)
>>> np.random.choice(choices, 5, p=counts/len(a), replace=False)
array([9, 8, 2, 4, 5])