[Numpy-discussion] Warnings in numpy.ma.test()
Thu Mar 18 14:12:10 CDT 2010
> On Wed, Mar 17, 2010 at 3:12 PM, Christopher Barker
>> 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.
> many function are defined differently for missing values, in stats,
> regression or time series analysis with the assumption of equally
> spaced time periods always needs to use special methods to handle
> missing values.
sure -- that's kind of my point -- if EVERY numpy array were
(potentially) masked, then folks would write code to deal with them
> Plus, you have to operate on two arrays and keep both in memory. So
> the penalty is pretty high even in C.
Only if there is actually a mask, which might make this pretty ugly --
lots of "if mask" code branching.
If a given routine either didn't make sense with missing values, or was
simply too costly with them, it could certainly raise an exception if it
got an array with a non-null mask.
>> Anyway, just a fantasy, but C-level ufuncs that support masks would be
Christopher Barker, Ph.D.
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