numpy NaN, not surviving pickle/unpickle?
lists at cheimes.de
Mon Sep 14 00:52:48 CEST 2009
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
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.
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