+1 to Alan's point. Having different type behaviour depending on the values of x and y for np.arange(x) ** y would be awful, and it would also be awful to have to worry about overflow here...
... Having said that, it would be equally annoying to not have a way to define integer powers... From: Alan Isaac <alan.is...@gmail.com> <alan.is...@gmail.com> Reply: Discussion of Numerical Python <numpy-discussion@scipy.org> <numpy-discussion@scipy.org> Date: 10 June 2016 at 5:10:57 AM To: Discussion of Numerical Python <numpy-discussion@scipy.org> <numpy-discussion@scipy.org> Subject: Re: [Numpy-discussion] Integers to integer powers, let's make a decision On 6/10/2016 2:42 AM, Nathaniel Smith wrote: > > I dunno, with my user hat on I'd be incredibly surprised / confused / > annoyed if an innocent-looking expression like > > np.arange(10) ** 2 > > started returning floats... having exact ints is a really nice feature > of Python/numpy as compared to R/Javascript, and while it's true that > int64 can overflow, there are also large powers that can be more > precisely represented as int64 than float. > > > > Is np.arange(10)**10 also "innocent looking" to a Python user? > > Also, I am confused by what "large powers" means in this context. > Is 2**40 a "large power"? > > Finally, is np.arange(1,3)**-2 "innocent looking" to a Python user? > > Cheers, > Alan > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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