[Numpy-discussion] Do we want scalar casting to behave as it does at the moment?
Nathaniel Smith
njs@pobox....
Thu Jan 3 18:49:24 CST 2013
On 4 Jan 2013 00:39, "Peter Cock" <p.j.a.cock@googlemail.com> wrote:
> I agree with Dag rather than Andrew, "Explicit is better than implicit".
> i.e. What Nathaniel described earlier as the apparent consensus.
>
> Since I've actually used NumPy arrays with specific low memory
> types, I thought I should comment about my use case if case it
> is helpful:
>
> I've only used the low precision types like np.uint8 (unsigned) where
> I needed to limit my memory usage. In this case, the topology of a
> graph allowing multiple edges held as an integer adjacency matrix, A.
> I would calculate things like A^n for paths of length n, and also make
> changes to A directly (e.g. adding edges). So an overflow was always
> possible, and neither the old behaviour (type preserving but wrapping
> on overflow giving data corruption) nor the current behaviour (type
> promotion overriding my deliberate memory management) are nice.
> My preferences here would be for an exception, so I knew right away.
I don't think the changes we're talking about here will help your use case
actually; this is only about the specific case where one of your operands,
itself, cannot be cleanly cast to the types being used for the operation -
it won't detect overflow in general. For that you want #593:
https://github.com/numpy/numpy/issues/593
On another note, while you're here, perhaps I can tempt you into having a
go at fixing #593? :-)
-n
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