[Numpy-discussion] custom accumlators
mattknox_ca at hotmail.com
Sat Jan 6 01:21:44 EST 2007
> Are you sure about this? I ran this case using timeit, and the first one
> was 5 times or so *faster* than the second case. I just dug around and
> frompyfunc is acutally implemented in C, although it has to call back
> into python to execute the function being vectorized. Can you try using
> timeit instead of profile and see what you get? For example:
> a = np.cumprod(1 + np.random.normal(size=10000)/10)
> if __name__ == '__main__':
> from timeit import Timer
> print Timer('expmave1(a, .5)', 'from scratch import np,
> expmave1, a').timeit(10)
> print Timer('expmave2(a, .5)', 'from scratch import np,
> expmave2, a').timeit(10)
> Anyway, I'm glad that all was helpful.
wow, you're right. Good call. profile and timeit give conflicting results (and
indeed, the timeit results are more accurate, I made a manual timer to test and
compared). I'll have to be more careful using profile in the future.
So that's pretty awesome then, a 5 times speed up using frompyfunc and
accumulate vs the brute force way of doing it. And I think the code looks a
little nicer too which is always nice. Definitely a technique I will be using
in the future.
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