[Numpy-discussion] Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
Hi all, Unlike conversions of 0-d arrays via: float(np.array([1])) conversions of 1-D or higher dimensional arrays with a single element are a bit strange: float(np.array([1])) And deprecating it has come up often enough with many in favor, but also many worried about the possible annoyance to users. I decided to give the PR a shot, I may have misread the room on it though: https://github.com/numpy/numpy/pull/10615 So if this turns out noisy (or you may simply disagree), I am happy to revert! There was always the worry that it might be painful for downstream. SciPy, pandas, matplotlib should all be fine (were fixed in the past years). And the fact that SciPy required much more changes than the other gives me some hope that many libraries won't mind. For end-users, I would lean towards taking it slow, but if you see issues there we can also revert of course. Cheers, Sebastian ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
[Numpy-discussion] Re: Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
On Thu, Apr 20, 2023 at 9:12 AM Sebastian Berg wrote: > Hi all, > > Unlike conversions of 0-d arrays via: > > float(np.array([1])) > > conversions of 1-D or higher dimensional arrays with a single element > are a bit strange: > > float(np.array([1])) > > And deprecating it has come up often enough with many in favor, but > also many worried about the possible annoyance to users. > I decided to give the PR a shot, I may have misread the room on it > though: > > https://github.com/numpy/numpy/pull/10615 > > So if this turns out noisy (or you may simply disagree), I am happy to > revert! > This looks like a great clean-up to me, thanks for giving this a try! ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
[Numpy-discussion] Re: Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
If symmetry w.r.t. pytorch is any guide, it was nice to have it: In [38]: float(torch.as_tensor([2])) Out[38]: 2.0 In [39]: float(np.asarray([2])) Out[39]: 2.0 I guess this boils down to what is a scalar really: is it `scalar.size == 1` or `scalar.ndim == 0` or something else. But that's just a digression, nevermind. On Thu, Apr 20, 2023 at 7:25 PM Stephan Hoyer wrote: > > > On Thu, Apr 20, 2023 at 9:12 AM Sebastian Berg > wrote: >> >> Hi all, >> >> Unlike conversions of 0-d arrays via: >> >> float(np.array([1])) >> >> conversions of 1-D or higher dimensional arrays with a single element >> are a bit strange: >> >> float(np.array([1])) >> >> And deprecating it has come up often enough with many in favor, but >> also many worried about the possible annoyance to users. >> I decided to give the PR a shot, I may have misread the room on it >> though: >> >> https://github.com/numpy/numpy/pull/10615 >> >> So if this turns out noisy (or you may simply disagree), I am happy to >> revert! > > > This looks like a great clean-up to me, thanks for giving this a try! > ___ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: evgeny.burovs...@gmail.com ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
[Numpy-discussion] Re: Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
On Thu, Apr 20, 2023 at 12:39 PM Evgeni Burovski wrote: > If symmetry w.r.t. pytorch is any guide, it was nice to have it: > > In [38]: float(torch.as_tensor([2])) > Out[38]: 2.0 > > In [39]: float(np.asarray([2])) > Out[39]: 2.0 > My question would be: Did they have a positive use case for this behavior, or were they just reflecting NumPy's behavior? AFAICR, the main reasoning on our side was that there was an unambiguous value that we _could_ return, so we might as well. And in our later experience, it was more trouble than it was worth. -- Robert Kern ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
[Numpy-discussion] Re: Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
On 4/20/23, Sebastian Berg wrote: > Hi all, > > Unlike conversions of 0-d arrays via: > > float(np.array([1])) > > conversions of 1-D or higher dimensional arrays with a single element > are a bit strange: > > float(np.array([1])) > > And deprecating it has come up often enough with many in favor, but > also many worried about the possible annoyance to users. > I decided to give the PR a shot, I may have misread the room on it > though: > > https://github.com/numpy/numpy/pull/10615 > > So if this turns out noisy (or you may simply disagree), I am happy to > revert! > > There was always the worry that it might be painful for downstream. > SciPy, pandas, matplotlib should all be fine (were fixed in the past > years). And the fact that SciPy required much more changes than the > other gives me some hope that many libraries won't mind. > > For end-users, I would lean towards taking it slow, but if you see > issues there we can also revert of course. > > Cheers, > > Sebastian > > Thanks Nico, and Sebastian, and everyone else involved in the PRs. This also affects `np.float64`: ``` In [61]: np.__version__ Out[61]: '1.25.0.dev0+1203.g1acac891f' In [62]: np.float64(0.0) Out[62]: 0.0 In [63]: np.float64(np.array(0.0)) Out[63]: 0.0 In [64]: np.float64(np.array([0.0])) :1: DeprecationWarning: Conversion of an array with ndim > 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.) np.float64(np.array([0.0])) Out[64]: 0.0 In [65]: np.float64(np.array([0.0, 0.0])) Out[65]: array([0., 0.]) ``` In 1.24.2, `np.float64(np.array([0.0])` returns the the scalar 0.0. If passing arrays to `np.float64()` is intentionally supported, it seems it would be more consistent for `np.float64(np.array([0.0]))` to return `np.array([0.0])`. That is how the other numpy types work (e.g. `np.complex128`, `np.int64`, etc.). But I'm not sure if there is a deprecation/update path that would get us there. Warren > > ___ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: warren.weckes...@gmail.com > ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
[Numpy-discussion] Re: Giving deprecation of e.g. `float(np.array([1]))` a shot (not 0-d)
On Thu, 2023-04-20 at 13:59 -0400, Warren Weckesser wrote: > On 4/20/23, Sebastian Berg wrote: > > Hi all, > > > > > > In [64]: np.float64(np.array([0.0])) > :1: DeprecationWarning: Conversion of > an array with ndim > 0 to a scalar is deprecated, and will error in > future. Ensure you extract a single element from your array before > performing this operation. (Deprecated NumPy 1.25.) > np.float64(np.array([0.0])) > Out[64]: 0.0 > > In [65]: np.float64(np.array([0.0, 0.0])) > Out[65]: array([0., 0.]) > Hmmmpf, that would be a good follow-up to fix. In theory a FutureWarning I guess (returning the array), but in practice, I think we should just give the correct array result. (I don't love returning arrays from scalar constructors, but that is another thing and not for now.) - Sebsatian > ``` > > In 1.24.2, `np.float64(np.array([0.0])` returns the the scalar 0.0. > > If passing arrays to `np.float64()` is intentionally supported, it > seems it would be more consistent for `np.float64(np.array([0.0]))` > to > return `np.array([0.0])`. That is how the other numpy types work > (e.g. `np.complex128`, `np.int64`, etc.). But I'm not sure if there > is > a deprecation/update path that would get us there. > > Warren > > > > > ___ > > NumPy-Discussion mailing list -- numpy-discussion@python.org > > To unsubscribe send an email to numpy-discussion-le...@python.org > > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > > Member address: warren.weckes...@gmail.com > > > ___ > NumPy-Discussion mailing list -- numpy-discussion@python.org > To unsubscribe send an email to numpy-discussion-le...@python.org > https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ > Member address: sebast...@sipsolutions.net > ___ NumPy-Discussion mailing list -- numpy-discussion@python.org To unsubscribe send an email to numpy-discussion-le...@python.org https://mail.python.org/mailman3/lists/numpy-discussion.python.org/ Member address: arch...@mail-archive.com
