[Numpy-discussion] numpy.ma.MaskedArray.min() makes a copy?

[Sebastian Berg]

On Tue, 2012-09-18 at 08:42 -1000, Eric Firing wrote:
> On 2012/09/18 7:40 AM, Benjamin Root wrote:
> >
> >
> > On Fri, Sep 7, 2012 at 12:05 PM, Nathaniel Smith <njs@pobox.com
> > <mailto:njs@pobox.com>> wrote:
> >
> >     On 7 Sep 2012 14:38, "Benjamin Root" <ben.root@ou.edu
> >     <mailto:ben.root@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
> 

It seems though that the keyword argument is still missing from the
ufunc help (`help(np.add)` and individual `np.info(np.add)`) though.


> 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
>