A weighted version of random.choice

Question

I needed to write a weighted version of random.choice (each element in the list has a different probability for being selected). This is what I came up with:

Answer 1

I'm probably too late to contribute anything useful, but here's a simple, short, and very efficient snippet:

def choose_index(probabilies):
    cmf = probabilies[0]
    choice = random.random()
    for k in xrange(len(probabilies)):
        if choice <= cmf:
            return k
        else:
            cmf += probabilies[k+1]

No need to sort your probabilities or create a vector with your cmf, and it terminates once it finds its choice. Memory: O(1), time: O(N), with average running time ~ N/2.

If you have weights, simply add one line:

def choose_index(weights):
    probabilities = weights / sum(weights)
    cmf = probabilies[0]
    choice = random.random()
    for k in xrange(len(probabilies)):
        if choice <= cmf:
            return k
        else:
            cmf += probabilies[k+1]