On Thu, Oct 25, 2012 at 6:58 PM, David Warde-Farley <warde...@iro.umontreal.ca> wrote: > On Thu, Oct 25, 2012 at 6:15 PM, Sebastian Berg > <sebast...@sipsolutions.net> wrote: >> On Thu, 2012-10-25 at 17:48 -0400, David Warde-Farley wrote: > >> Don't worry about that failure on Travis... It happens randomly on at >> the moment and its unrelated to anything you are doing. > > Ah, okay. I figured it was something like that. > >> I am not sure though you can change behavior like that since you also >> change the default behavior of the `.copy()` method and someone might >> rely on that? > > Oops, you're right. I assumed I was changing __copy__ only. Pull > request updated. > > Given that behaviour is documented it really ought to be tested. I'll add one. > >> Maybe making it specific to the copy model would make it >> unlikely that anyone relies on the default, it would seem sensible that >> copy.copy(array) does basically the same as np.copy(array) and not as >> the method .copy, though ideally maybe the differences could be removed >> in the long run I guess. > > Agreed, but for now the .copy() method's default shouldn't change. I > think the scikit-learn usecase I described is a good reason why the > copy protocol methods should maintain data ordering, though.
I think this might be something that could wait for a big numpy version change. At least I always assumed that a new array created by copying is the default numpy C order (unless otherwise requested). I never rely on it except sometimes when I think about speed of operation in fortran versus c order. np.copy says: This is equivalent to >>> np.array(a, copy=True) numpy.ma.copy has the order keyword with "c" as default changing the default from "C" to "A" doesn't look like a minor API change. (I'm using numpy 1.5 help file, so maybe I'm outdated.) Josef > > David > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
