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

[Christopher Barker]

Christopher Jordan-Squire wrote:
> If we follow those rules for IGNORE for all computations, we sometimes 
> get some weird output. For example:
> [ [1, 2], [3, 4] ] * [ IGNORE, 7] = [ 15, 31 ]. (Where * is matrix 
> multiply and not * with broadcasting.) Or should that sort of operation 
> through an error?

That should throw an error -- matrix computation is heavily influenced 
by the shape and size of matrices, so I think IGNORES really don't make 
sense there.


Nathaniel Smith wrote:
> It's exactly this transparency that worries Matthew and me -- we feel
> that the alterNEP preserves it, and the NEP attempts to erase it. In
> the NEP, there are two totally different underlying data structures,
> but this difference is blurred at the Python level. The idea is that
> you shouldn't have to think about which you have, but if you work with
> C/Fortran, then of course you do have to be constantly aware of the
> underlying implementation anyway. 

I don't think this bothers me -- I think it's analogous to things in 
numpy like Fortran order and non-contiguous arrays -- you can ignore all 
that when working in pure python when performance isn't critical, but 
you need a deeper understanding if you want to work with the data in C 
or Fortran or to tune performance in python.

So as long as there is an API to query and control how things work, I 
like that it's hidden from simple python code.

-Chris





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Christopher Barker, Ph.D.
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