On Sat, Jun 4, 2016 at 3:49 PM, Matthew Brett <matthew.br...@gmail.com>
wrote:
> On Sat, Jun 4, 2016 at 12:47 PM, <josef.p...@gmail.com> wrote:
> >
> >
> > On Sat, Jun 4, 2016 at 3:43 PM, Charles R Harris <
> charlesr.har...@gmail.com>
> > wrote:
> >>
> >>
> >>
> >> On Sat, Jun 4, 2016 at 11:22 AM, Charles R Harris
> >> <charlesr.har...@gmail.com> wrote:
> >>>
> >>> Hi All,
> >>>
> >>> I've made a new post so that we can make an explicit decision. AFAICT,
> >>> the two proposals are
> >>>
> >>> Integers to negative integer powers raise an error.
> >>> Integers to integer powers always results in floats.
> >>>
> >>> My own sense is that 1. would be closest to current behavior and using
> a
> >>> float exponential when a float is wanted is an explicit way to
> indicate that
> >>> desire. OTOH, 2. would be the most convenient default for everyday
> numerical
> >>> computation, but I think would more likely break current code. I am
> going to
> >>> come down on the side of 1., which I don't think should cause too many
> >>> problems if we start with a {Future, Deprecation}Warning explaining the
> >>> workaround.
> >
> >
> > I'm in favor of 2. always float for `**`
> > I don't see enough pure integer usecases to throw away a nice operator.
>
> I can't make sense of 'throw away a nice operator' - you still have
> arr ** 2.0 if you want floats.
>
but if we have x**y, then we always need to check the dtype. If we don't we
get RuntimeErrors or overflow, where we might have forgotten to include the
relevant cases in the unit tests.
numpy has got pickier with using only integers in some areas (index, ...).
Now we have to watch out that we convert back to floats for power.
Not a serious problem for a library with unit tests and enough users who
run into the dtype issues and report them.
But I'm sure I will have to fix any scripts or interactive work that I'm
writing.
It's just another thing to watch out for, after we managed to get rid of
integer division 1/2=?.
Josef
>
> Matthew
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