John Ladasky wrote: > OK, so there's a dedicated function in numpy to handle this. Thanks! > > I tried "x is NaN" after noting the obvious, that any equality or > inequality test involving NaN will return False. > > In my leisure time, I would like to dig deeper into the issue of why > object identities are not guaranteed for elements in numpy arrays... > with elements of type "float", at least, I thought this would be > trivial.
You mustn't use "is" on numbers ever. It might work under some special circumstances but in general it doesn't do what you expect. NaN isn't a singleton in Python. Python's float type uses IEEE 754 double precision numbers internally. The double type has much more than billions of NaN values (IIRC 2**53). isnan() is the only reliable way to detect NaNs. "x != x" is a hack that works on most platforms, too. Christian -- http://mail.python.org/mailman/listinfo/python-list
