Nick Craig-Wood wrote: > Gerard Flanagan <[EMAIL PROTECTED]> wrote: > > def distribution(N=2): > > p = [0] + sorted( random.random() for _ in range(N-1) ) + [1] > > for j in range(N): > > yield p[j+1] - p[j] > > > > spread = list(distribution(10)) > > > > print spread > > print sum(spread) > > This is simpler, easier to prove correct and most likely quicker. > > def distribution(N=2): > L = [ random.uniform(0,1) for _ in xrange(N) ] > sumL = sum(L) > return [ l/sumL for l in L ] >
simpler:- ok easier to prove correct:- in what sense? quicker:- slightly slower in fact (using xrange in both functions). This must be due to 'uniform' - using random() rather than uniform(0,1) then yes, it's quicker. Roughly tested, I get yours (and Alex Martelli's) to be about twice as fast. (2<=N<1000, probably greater difference as N increases). All the best. Gerard -- http://mail.python.org/mailman/listinfo/python-list
