On Sun, 2021-09-05 at 21:08 +0200, Ralf Gommers wrote: > On Sat, Sep 4, 2021 at 10:02 AM Kshitij Kalambarkar < > kshitijkalambar...@gmail.com> wrote: > > > Hi, > > > > np.trunc returns floating dtype output even for integral dtype > > input. As > > per array-api, it should preserve the input dtype. > > > > Just a note that it's not compatibility with the array API standard > that's > the main driver for the change here (that would be handled in > `numpy.array_api.trunc`, not `numpy.trunc`). But it's just unwanted > behavior, so an improvement to `numpy.trunc` is also desirable. > > > > Note: This is also true for np.rint, np.fix, np.ceil, np.floor > > > > Reference: https://github.com/numpy/numpy/issues/19464 > > > > Possible Fix: > > 1. We update the behaviour directly with an update to release note. > > 2. We add a FutureWarning and update the behaviour in a future > > release. > > > > I'm fine with (1), because (a) it can be considered a bug fix, (b) > it's > unlikely to break anything, and (c) a FutureWarning is not too > helpful > because there's no way to update existing code to be forward-proof > and > remove the warning.
One work-around might be to pass `dtype=arr.dtype` probably, but that would fail on current NumPy. So the only choice would probably be explicitly not calling `trunc`. So, I agree, I lean towards moving forward here. (Unless anyone has e.g. an example of code that would break?) There is a tiny possibility of catastrophic failure (silent wrong results). But my best guess is that the vast majority of code probably will not notice. E.g. one pattern that is probably extremely common is to cast to integer right after the call to `trunc`. Cheers, Sebastian > > Cheers, > Ralf > > > > This email is to gauge the preference for the fix. > > > > Thank You! > > > > Regards, > > Kshiteej K > > > > > > > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@python.org > > https://mail.python.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion
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