On 2012/09/18 7:40 AM, Benjamin Root wrote: > > > On Fri, Sep 7, 2012 at 12:05 PM, Nathaniel Smith <n...@pobox.com > <mailto:n...@pobox.com>> wrote: > > On 7 Sep 2012 14:38, "Benjamin Root" <ben.r...@ou.edu > <mailto:ben.r...@ou.edu>> wrote: > > > > An issue just reported on the matplotlib-users list involved a > user who ran out of memory while attempting to do an imshow() on a > large array. While this wouldn't be totally unexpected, the user's > traceback shows that they ran out of memory before any actual > building of the image occurred. Memory usage sky-rocketed when > imshow() attempted to determine the min and max of the image. The > input data was a masked array, and it appears that the > implementation of min() for masked arrays goes something like this > (paraphrasing here): > > > > obj.filled(inf).min() > > > > The idea is that any masked element is set to the largest > possible value for their dtype in a copied array of itself, and then > a min() is performed on that copied array. I am assuming that max() > does the same thing. > > > > Can this be done differently/more efficiently? If the "filled" > approach has to be done, maybe it would be a good idea to make the > copy in chunks instead of all at once? Ideally, it would be nice to > avoid the copying altogether and utilize some of the special > iterators that Mark Weibe created last year. > > I think what you're looking for is where= support for ufunc.reduce. > This isn't implemented yet but at least it's straightforward in > principle... otherwise I don't know anything better than > reimplementing .min() by hand. > > -n > > > > Yes, it was the where= support that I was thinking of. I take it that > it was pulled out of the 1.7 branch with the rest of the NA stuff?
The where= support was left in: http://docs.scipy.org/doc/numpy/reference/ufuncs.html See also get_ufunc_arguments in ufunc_object.c. Eric > > Ben Root > > > > _______________________________________________ > 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
