"Nick Craig-Wood" <[EMAIL PROTECTED]> wrote: > Paul Rubin <http> wrote: > > The fencepost method still seems to be simplest: > > > > t = sorted(random.sample(xrange(1,50), 4)) > > print [(j-i) for i,j in zip([0]+t, t+[50])] > > Mmm, nice. > > Here is another effort which is easier to reason about the > distribution produced but not as efficient. > > def real(N, M): > while 1: > t = [ random.random() for i in range(N) ] > factor = M / sum(t) > t = [ int(round(x * factor)) for x in t] > if sum(t) == M: > break > print "again" > assert len(t) == N > assert sum(t) == M > return t > > It goes round the while loop on average 0.5 times. > > If 0 isn't required then just test for it and go around the loop again > if found. That of course skews the distribution in difficult to > calculate ways! >
I have been wondering about the following as this thread unrolled: Is it possible to devise a test that can distinguish between sets of: - five random numbers that add to 50, and - four random numbers and a fudge number that add to 50? My stats are way too small and rusty to attempt to answer the question, but it seems intuitively a very difficult thing. - Hendrik -- http://mail.python.org/mailman/listinfo/python-list
