On 09/07/2008, Paul McGuire <[EMAIL PROTECTED]> wrote: > > def length(self): > > dx,dy = self.p1 - self.p2 > > return (dx**2 + dy **2) ** 0.5 > > How about: > > def length(self): > return math.hypot( *(self.p1 - self.p2) ) > > Compiled C code will be much faster than squaring and square rooting.
Well, here's what I get: Morpork:~ repton$ python -m timeit -s 'dx, dy = (8, 5)' '(dx**2 + dy**2)**0.5' 1000000 loops, best of 3: 0.555 usec per loop Morpork:~ repton$ python -m timeit -s 'dx, dy = (8, 5)' -s 'import math' 'math.hypot(dx, dy)' 1000000 loops, best of 3: 0.6 usec per loop YMMV, but it doesn't make a strong case for "much faster". (if I make a local reference to math.hypot, I can save 0.1 usec, which puts the math.hypot technique in the lead, at the expense of readability: Morpork:~ repton$ python -m timeit -s 'dx, dy = (8, 5)' -s 'import math' -s 'hyp = math.hypot' 'hyp(dx, dy)' 1000000 loops, best of 3: 0.501 usec per loop ) -- John. _______________________________________________ Tutor maillist - Tutor@python.org http://mail.python.org/mailman/listinfo/tutor
