On Wed, 01 May 2013, Matthew Brett wrote:
There really is no point discussing here, this has to do with numpy doing iteration order optimization, and you actually *want* this. Lets for a second assume that the old behavior was better, then the next guy is going to ask: "Why is np.add.reduce(array, axis=0) so much slower then reduce(array, np.add)?". This is huge speed improvement by Marks new iterator for reductions over the slow axes, so instead of trying to track "regressions" down, I think the right thing is to say kudos for doing this improvement :).
I don't believe Yarick meant his bisection to be a criticism, but as an aid to full understanding.
Exactly right, Matthew -- thank you! And kudos to Mark! N.B. I am generally furry and kind, not fuzzy and evil -- Yaroslav O. Halchenko, Ph.D. http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org Senior Research Associate, Psychological and Brain Sciences Dept. Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik