[Numpy-discussion] Should abs([nan]) be supported?
Tue Sep 4 22:49:14 CDT 2012
On Tue, Sep 4, 2012 at 8:38 PM, Travis Oliphant <email@example.com> wrote:
> There is an error context that controls how floating point signals are handled. There is a separate control for underflow, overflow, divide by zero, and invalid. IIRC, it was decided on this list a while ago to make the default ignore for underflow and warning for overflow, invalid and divide by zero.
> However, an oversight pushed versions of NumPy where all the error handlers where set to "ignore" and this test was probably written then. I think the test should be changed to check for RuntimeWarning on some of the cases. This might take a little work as it looks like the code uses generators across multiple tests and would have to be changed to handle expecting warnings.
> Alternatively, the error context can be set before the test runs and then restored afterwords:
> olderr = np.seterr(invalid='ignore')
> or, using an errstate context ---
> with np.errstate(invalid='ignore'):
I see --- so abs([nan]) should emit a warning, but in the test we
should suppress it.
I'll work on that.
The only thing that I don't understand is why it only happens on some
platforms and doesn't on some other platforms (apparently). But it's
clear how to fix it now.
Thanks for the information.
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