[Numpy-discussion] Numpy integers to integer powers again again
shoyer at gmail.com
Tue Oct 25 12:14:40 EDT 2016
I am also concerned about adding more special cases for NumPy scalars vs
arrays. These cases are already confusing (e.g., making no distinction
between 0d arrays and scalars) and poorly documented.
On Mon, Oct 24, 2016 at 4:30 PM, Nathaniel Smith <njs at pobox.com> wrote:
> On Mon, Oct 24, 2016 at 3:41 PM, Charles R Harris
> <charlesr.harris at gmail.com> wrote:
> > Hi All,
> > I've been thinking about this some (a lot) more and have an alternate
> > proposal for the behavior of the `**` operator
> > if both base and power are numpy/python scalar integers, convert to
> > integers and call the `**` operator. That would solve both the precision
> > compatibility problems and I think is the option of least surprise. For
> > those who need type preservation and modular arithmetic, the np.power
> > function remains, although the type conversions can be surpirising as it
> > seems that the base and power should play different roles in determining
> > the type, at least to me.
> > Array, 0-d or not, are treated differently from scalars and integers
> > to negative integer powers always raise an error.
> > I think this solves most problems and would not be difficult to
> > Thoughts?
> My main concern about this is that it adds more special cases to numpy
> scalars, and a new behavioral deviation between 0d arrays and scalars,
> when ideally we should be trying to reduce the
> duplication/discrepancies between these. It's also inconsistent with
> how other operations on integer scalars work, e.g. regular addition
> overflows rather than promoting to Python int:
> In : np.int64(2 ** 63 - 1) + 1
> /home/njs/.user-python3.5-64bit/bin/ipython:1: RuntimeWarning:
> overflow encountered in long_scalars
> Out: -9223372036854775808
> So I'm inclined to try and keep it simple, like in your previous
> proposal... theoretically of course it would be nice to have the
> perfect solution here, but at this point it feels like we might be
> overthinking this trying to get that last 1% of improvement. The thing
> where 2 ** -1 returns 0 is just broken and bites people so we should
> definitely fix it, but beyond that I'm not sure it really matters
> *that* much what we do, and "special cases aren't special enough to
> break the rules" and all that.
> Nathaniel J. Smith -- https://vorpus.org
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
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