On Tue, Jun 28, 2011 at 12:41 PM, Eric Firing <efir...@hawaii.edu> wrote: > 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.
You can get something semantically equivalent to the masked implementation by adding some extra bits and then stealing those. (That was the original "maybe(...)" idea.) My proposal would make it easy to implement either (either for us or for users, if we decide we don't want to clutter up the numpy core with too many pre-canned NA implementations). Doing this would give up either memory or speed versus both the separate-mask approach and the purely-bit-stealing approaches, but I don't know if anyone cares about NA support in integers *that* much -- personally I want it to be possible, because count data is important in statistics, but I don't really care how efficient it is. Floating point is much more important in practice. (Heck, R usually uses doubles for count data too -- you can't get an integer without an explicit cast.) -- Nathaniel _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
