Roulette Selection in Genetic Algorithms

Question

Can anyone provide some pseudo code for a roulette selection function? How would I implement this:

Answer 1

Lots of correct solutions already, but I think this code is clearer.

def select(fs):
    p = random.uniform(0, sum(fs))
    for i, f in enumerate(fs):
        if p <= 0:
            break
        p -= f
    return i

In addition, if you accumulate the fs, you can produce a more efficient solution.

cfs = [sum(fs[:i+1]) for i in xrange(len(fs))]

def select(cfs):
    return bisect.bisect_left(cfs, random.uniform(0, cfs[-1]))

This is both faster and it's extremely concise code. STL in C++ has a similar bisection algorithm available if that's the language you're using.