[Numpy-discussion] Missing data again
Wed Mar 7 13:39:04 CST 2012
On Wed, Mar 7, 2012 at 1:26 PM, Nathaniel Smith <firstname.lastname@example.org> wrote:
> On Wed, Mar 7, 2012 at 5:17 PM, Charles R Harris
> <email@example.com> wrote:
> > On Wed, Mar 7, 2012 at 9:35 AM, Pierre Haessig <firstname.lastname@example.org
> >> Coming back to Travis proposition "bit-pattern approaches to missing
> >> data (*at least* for float64 and int32) need to be implemented.", I
> >> wonder what is the amount of extra work to go from nafloat64 to
> >> nafloat32/16 ? Is there an hardware support NaN payloads with these
> >> smaller floats ? If not, or if it is too complicated, I feel it is
> >> acceptable to say "it's too complicated" and fall back to mask. One may
> >> have to choose between fancy types and fancy NAs...
> > I'm in agreement here, and that was a major consideration in making a
> > 'masked' implementation first.
> When it comes to "missing data", bitpatterns can do everything that
> masks can do, are no more complicated to implement, and have better
> performance characteristics.
Not true. bitpatterns inherently destroys the data, while masks do not.
For matplotlib, we can not use bitpatterns because it could over-write user
data (or we have to copy the data). I would imagine other extension
writers would have similar issues when they need to play around with input
data in a safe manner.
Also, I doubt that the performance characteristics for strings and integers
are the same as it is for masks.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion