Hi, On Tue, Jun 28, 2011 at 8:41 PM, Eric Firing <efir...@hawaii.edu> wrote: > On 06/28/2011 07:26 AM, Nathaniel Smith wrote: >> On Tue, Jun 28, 2011 at 9:38 AM, Charles R Harris >> <charlesr.har...@gmail.com> wrote: >>> Nathaniel, an implementation using masks will look *exactly* like an >>> implementation using na-dtypes from the user's point of view. Except that >>> taking a masked view of an unmasked array allows ignoring values without >>> destroying or copying the original data. >> >> Charles, I know that :-). >> >> But if that view thing is an advertised feature -- in fact, the key >> selling point for the masking-based implementation, included >> specifically to make a significant contingent of users happy -- then >> it's certainly user-visible. And it will make other users unhappy, >> like I said. That's life. >> >> But who cares? My main point is that implementing a missing data >> solution and a separate masked array solution is probably less work >> than implementing a single everything-to-everybody solution *anyway*, >> *and* it might make both sets of users happier too. Notice that in my >> proposal, there's really nothing there that isn't already in Mark's >> NEP in some form or another, but in my version there's almost no >> overlap between the two features. That's not because I was trying to >> make them artificially different; it's because I tried to think of the >> most natural ways to satisfy each set of use cases, and they're just >> different. > > I think you are exaggerating some of the differences associated with the > implementation, and ignoring one *key* difference: for integer types, > the masked implementation can handle the full numeric range of the type, > while the bit-pattern approach cannot.
Losing the most negative value in an int16 doesn't seem too much, but I agree losing a value in int8 might be annoying. On the other hand, maybe it's OK if we don't suport NAs for int8. See you, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
