On Mon, Aug 2, 2021 at 7:04 PM Sebastian Berg <sebastian@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