On Sat, Jun 4, 2016 at 9:26 PM, Nathaniel Smith <n...@pobox.com> wrote:
> On Jun 4, 2016 7:23 PM, "Charles R Harris" <charlesr.har...@gmail.com> > wrote: > > > [...] > > We could always try the float option and see what breaks, but I expect > there is a fair amount of code using small exponents like 2 or 3 where it > is expected that the result is still integer. I would like more input from > users than we have seen so far... > > Just to highlight this, if anyone wants to strengthen the argument for > switching to float then this is something you can literally do: tweak a > local checkout of numpy to return float from int**int and > array-of-int**array-of-int, and then try running the test suites of > projects like scikit-learn, astropy, nipy, scikit-image, ... > > (The reason I'm phrasing this as something that people who like the float > idea should do is that generally when proposing a risky > compatibility-breaking change, the onus is on the ones proposing it to > demonstrate that the risk is ok.) > I was tempted for a bit, but I think the biggest compatibility problem is not current usage, but the fact that code written assuming float results will not work for earlier versions of numpy, and that would be a nasty situation. Given that integers raised to negative integer powers is already pretty much broken, making folks write around an exception will result in code compatible with previous numpy versions. Chuck
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