[Numpy-discussion] Warnings in numpy.ma.test()

Christopher Barker Chris.Barker@noaa....
Wed Mar 17 14:12:18 CDT 2010


Eric Firing wrote:
> My motivation for going 
> to the C level was speed and control; many ma operations are very slow 
> compared to their numpy counterparts, and moving the mask handling to C 
> can erase nearly all of this penalty.

really? very cool. I was thinking about this the other day, and thinking 
that in some grand future vision, all numpy arrays should be masked 
arrays (or could be). The idea is that missing/invalid data is a really 
common case, and it is simply wonderful to have the software handle that 
gracefully.

One of the things I liked about MATLAB was that NaNs were well handled 
almost all the time. Given all the limitations of NaN, having a masked 
array is a better way to go, but I'd love it if they were "just there", 
and therefore EVERY numpy function and package built on numpy would 
handle them gracefully. I had thought that there would be a significant 
performance penalty, and thus there would be a boatload of "if_mask" 
code all over the place, but maybe not.

Anyway, just a fantasy, but C-level ufuncs that support masks would be 
great.

-Chris





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Christopher Barker, Ph.D.
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