On Mon, Aug 2, 2021 at 7:04 PM Sebastian Berg <sebast...@sipsolutions.net> wrote:
> Hi all, > > In NumPy 1.21, the output of `np.unique` changed in the presence of > multiple NaNs. Previously, all NaNs were returned when we now only > return one (all NaNs were considered unique): > > a = np.array([1, 1, np.nan, np.nan, np.nan]) > > Before 1.21: > > >>> np.unique(a) > array([ 1., nan, nan, nan]) > > After 1.21: > > array([ 1., nan]) > > > This change was requested in an old issue: > > https://github.com/numpy/numpy/issues/2111 > > And happened here: > > https://github.com/numpy/numpy/pull/18070 > > While, it has a release note. I am not sure the change got the > attention it deserved. This would be especially worrying if it is a > regression for anyone? > I think it's now the expected answer, not a regression. `unique` is not an elementwise function that needs to adhere to IEEE-754 where nan != nan. I can't remember reviewing this change, but it makes perfect sense to me. Cheers, Ralf
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