[Numpy-discussion] NA/Missing Data Conference Call Summary

[Charles R Harris]

On Wed, Jul 6, 2011 at 2:53 PM, Neal Becker <ndbecker2 at gmail.com> wrote:

> Christopher Barker wrote:
>
> > Dag Sverre Seljebotn wrote:
> >> Here's an HPC perspective...:
> >
> >> At least I feel that the transparency of NumPy is a huge part of its
> >> current success. Many more than me spend half their time in C/Fortran
> >> and half their time in Python.
> >
> > Absolutely -- and this point has been raised a couple times in the
> > discussion, so I hope it is not forgotten.
> >
> >   > I tend to look at NumPy this way: Assuming you have some data in
> memory
> >> (possibly loaded by a C or Fortran library). (Almost) no matter how it
> >> is allocated, ordered, packed, aligned -- there's a way to find strides
> >> and dtypes to put a nice NumPy wrapper around it and use the memory from
> >> Python.
> >
> > and vice-versa -- Assuming you have some data in numpy arrays, there's a
> > way to process it with a C or Fortran library without copying the data.
> >
> > And this is where I am skeptical of the bit-pattern idea -- while one
> > can expect C and fortran and GPU, and ??? to understand NaNs for
> > floating point data, is there any support in compilers or hardware for
> > special bit patterns for NA values to integers? I've never seen in my
> > (very limited experience).
> >
> > Maybe having the mask option, too, will make that irrelevant, but I want
> > to be clear about that kind of use case.
> >
> > -Chris
>
> Am I the only one that finds the idea of special values of things like
> int[1] to
> have special meanings to be really ugly?
>
> [1] which already have defined behavior over their entire domain of bit
> patterns
>
>
Umm, no, I find it ugly also. On the other hand, it is an useful artifact
left to us by the ancients and solves a lot of problems. So in the absence
of anything more standardized...

Chuck
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