unexpected behaviour on full_like(<int_array>, nan)

[naught101]

>>> np.full_like(np.array([1,0]), np.nan)
array([-9223372036854775808, -9223372036854775808])

Normally, conversion of an NaN to an int fails:

>>> np.int(np.nan) 
ValueError: cannot convert float NaN to integer

I suspect the full_like behaviour should similarly raise an error. I'm not sure how common this behaviour is.

[charris]

Hmm... IIRC, there are three treatments of nan -> int, the one shown, conversion to 0, and raising an error. We should try to rationalize things at some point. For the current behavior, I agree that raising an error would be better.

[naught101]

I can't say I really understand how np.nan really works, but it would be cool if there was an equivalent np.intnan or something that would work with integer arrays - NaNs are pretty useful, and it'd be nice to be able to use them with integers too.

[charris]

The problem with integers as that there aren't any left over, whereas for floating point there are bit patterns not used by any actual floating point number.

[naught101]

Ah, fair enough. I guess it would take a change in python itself to specify that e.g -9223372036854775808 wasn't a number, and could be used for nan or inf or similar? And that's almost certainly not going to happen...

[charris]

Google "missing values" to see how various (statistical) projects deal with similar needs. Note that missing values are not quite the same as not-a-number.

[seberg]

This will now at the very least give a RuntimeWarning on main (still a while until a next release).

There is still a more general issue whether:

• Full should allow unsafe casts at all (but we do in practically all filling functions)
• Whether integer casts should be more agressive then giving a warning or sanitize the values.

At least for the second part, I kept gh-14412 as an issue open. So closing this for now, but please feel free to open a new issue if you feel it is important (and there is no current duplicate; if there is a duplicate just comment there!)