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

Eric Firing efiring@hawaii....
Tue Sep 18 13:42:19 CDT 2012


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

See also get_ufunc_arguments in ufunc_object.c.

Eric


>
> Ben Root
>
>
>
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