Re: [Numpy-discussion] Numpy arrays shareable among related processes (PR #7533)

Antoine Pitrou wrote: > When writing C code to interact with buffer-providing objects, you > usually don't bother with memoryviews at all. You just use a Py_buffer > structure. I was taking about "typed memoryviews" which is a Cython abstraction for a Py_buffer struct. I

Re: [Numpy-discussion] Integers to integer powers

At 01:15 PM 5/24/2016, you wrote: On 5/24/2016 3:57 PM, Eric Moore wrote: Changing np.arange(10)**3 to have a non-integer dtype seems like a big change. What about np.arange(100)**5? Interesting, one warning per instantiation (Py2.7): >>> import numpy >>> a=numpy.arange(100)**5 :1:

Re: [Numpy-discussion] Integers to integer powers

On 5/24/2016 3:57 PM, Eric Moore wrote: Changing np.arange(10)**3 to have a non-integer dtype seems like a big change. What about np.arange(100)**5? Alan Isaac ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] Integers to integer powers

Yes, I'm fully aware of that. I'm speaking toward changing the default result dtype. Raising an error for negative exponents is a fine idea. Changing np.arange(10)**3 to have a non-integer dtype seems like a big change. Speaking of this, that some of the integer array operation errors can be

Re: [Numpy-discussion] Integers to integer powers

On Tue, May 24, 2016 at 10:36 AM, Eric Moore wrote: > I'd say the most compelling case for it is that is how it has always worked. > How much code will break if we make that change? (Or if not break, at least > have a change in dtype?) Is that worth it? The current

Re: [Numpy-discussion] Integers to integer powers

On 5/24/2016 1:41 PM, Matthew Brett wrote: It's a well-understood promise though - you always have to be careful of integer overflow. Of course. But **almost all** cases overflow. And "well understood" assume a certain sophistication of the user, while `arange` will certainly be used by

Re: [Numpy-discussion] Integers to integer powers

On 5/24/2016 1:36 PM, Eric Moore wrote: How much code will break if we make that change? Since even arange(10)**10 is already broken, there will probably not be much new breakage. But under any of the new proposals, *something* will break. So the question is, which shows the most foresight?

Re: [Numpy-discussion] Integers to integer powers

On Tue, May 24, 2016 at 1:31 PM, Alan Isaac wrote: > On 5/24/2016 1:19 PM, Stephan Hoyer wrote: >> >> the int ** 2 example feels quite compelling to me > > > > Yes, but that one case is trivial: a*a Right, but you'd have to know to change your code when numpy makes this

Re: [Numpy-discussion] Integers to integer powers

On Tue, May 24, 2016 at 10:31 AM, Alan Isaac wrote: > Yes, but that one case is trivial: a*a an_explicit_name ** 2 is much better than an_explicit_name * an_explicit_name, though. ___ NumPy-Discussion mailing list

Re: [Numpy-discussion] Integers to integer powers

I'd say the most compelling case for it is that is how it has always worked. How much code will break if we make that change? (Or if not break, at least have a change in dtype?) Is that worth it? Eric On Tue, May 24, 2016 at 1:31 PM, Alan Isaac wrote: > On 5/24/2016

Re: [Numpy-discussion] Integers to integer powers

On 5/24/2016 1:19 PM, Stephan Hoyer wrote: the int ** 2 example feels quite compelling to me Yes, but that one case is trivial: a*a And at least as compelling is not have a**-2 fail and not being tricked by say np.arange(10)**10. The latter is a promise of hidden errors. Alan

Re: [Numpy-discussion] Integers to integer powers

On Tue, May 24, 2016 at 9:41 AM, Alan Isaac wrote: > What exactly is the argument against *always* returning float > (even for positive integer exponents)? > If we were starting over from scratch, I would agree with you, but the int ** 2 example feels quite compelling to

Re: [Numpy-discussion] Integers to integer powers

On 5/24/2016 10:03 AM, Marten van Kerkwijk wrote: The error on int ** (-int) is OK with me too (even though I prefer just returning floats). What exactly is the argument against *always* returning float (even for positive integer exponents)? Relevant context is: - int ** int will often

Re: [Numpy-discussion] Integers to integer powers

The error on int ** (-int) is OK with me too (even though I prefer just returning floats). Having a `floor_pow` function may still be good with this solution too. -- Marten ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org

Re: [Numpy-discussion] Integers to integer powers

On Thu, 19 May 2016 20:30:40 -0700 Nathaniel Smith wrote: > > Given these immutable and contradictory constraints, the last bad > option IMHO would be that we make int ** (negative int) an error in > all cases, and the error message can suggest that instead of writing > >

Re: [Numpy-discussion] Numpy arrays shareable among related processes (PR #7533)

On Thu, 12 May 2016 23:14:36 + (UTC) Sturla Molden wrote: > Antoine Pitrou wrote: > > > Can you define "expensive"? > > Slow enough to cause complaints on the Cython mailing list. What kind of complaints? Please be specific. > > Buffer