On Jun 29, 2011, at 1:37 AM, Mark Wiebe wrote: > On Tue, Jun 28, 2011 at 3:45 PM, Pierre GM <pgmdevl...@gmail.com> wrote: > ... > > I think that would really take care of the missing data part in a consistent > and non-ambiguous way. > However, I understand that if a choice would be made, this approach would be > dropped for the most generic "mask way", right ? (By "mask way", I mean > something that is close (but actually optimized) to thenumpy.ma approach). > > The NEP proposes strict NA missing value semantics, where the only way to get > at the masked values is by having another view that doesn't have the value > masked. If someone has use cases where this prevents some functionality they > need, I'd love to hear them.
Mmh... Would you have an example ? I haven't caught up with my lack of sleep yet... > > So, taking this example > >>> np.add(a, b, out=b, mask=(a > threshold)) > If 'b' doesn't already have a mask, masked values will be lost if we go the > mask way ? But kept if we go the bit way ? I prefer the latter, then > Another advantage I see in the "bit-way' is that it's pretty close to the > 'hardmask' idea. You'll never risk to lose the mask as it's already "burned" > in the array... > > I've nearly finished this parameter, and decided to call it 'where' instead, > because it is operating like an SQL where clause. Here if neither a nor b are > masked array it will only modify those values of b where the 'where' > parameter has the value True. OK, sounds fine. Pretty fine, actually. Just to be clear, if 'out' is not defined, the result is a masked array with 'where' as mask. What's the value below the mask ? np.NA ? > And now for something not that completely different: > * Would it be possible to store internally the addresses of the NAs only to > save some space (in the metadata ?) and when the .mask or .valid property is > called, to still get a boolean array with the same shape as the underlying > array ? > > Something like this could be possible, but would certainly complicate the > implementation. If it were desired, it would be a follow-up feature. Oh, no problem. I was suggesting a way to save some space, but if it's too tricky to implement, forget it. _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
