On 07/15/2011 03:13 AM, Ralf Gommers wrote:
On Fri, Jul 8, 2011 at 4:17 PM, Derek Homeier
<[email protected]
<mailto:[email protected]>> wrote:
On 07.07.2011, at 7:16PM, Robert Pyle wrote:
>
.............../Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/core/numeric.py:1922:
RuntimeWarning: invalid value encountered in absolute
> return all(less_equal(absolute(x-y), atol + rtol * absolute(y)))
>
>
> Everything else completes with 3 KNOWNFAILs and 1 SKIP. This
warning is not new to this release; I've seen it before but
haven't tried tracking it down until today.
>
> It arises in allclose(). The comments state "If either array
contains NaN, then False is returned." but no test for NaN is
done, and NaNs are indeed what cause the warning.
>
> Inserting
>
> if any(isnan(x)) or any(isnan(y)):
> return False
>
> before current line number 1916 in numeric.py seems to fix it.
The same warning is still present in the current master, I just
never paid attention to it because the tests still pass (it does
correctly identify NaNs because they are not less_equal the
tolerance), but of course this should be properly fixed as you
suggest.
Under Python 2.6 I used to see this but it has disappeared. What's
going on here?
$ python2.7
>>> from numpy import *
>>> absolute(nan)
__main__:1: RuntimeWarning: invalid value encountered in absolute
nan
$ python2.6
>>> from numpy import *
>>> absolute(nan)
nan
Ralf
I do not see this with 64-bit Python2.7 on my Linux system. So perhaps
Mac specific?
By the way, all tests pass with Python 2.7 and 3.2 for rc3.
Bruce
$ python
Python 2.7 (r27:82500, Sep 16 2010, 18:02:00)
[GCC 4.5.1 20100907 (Red Hat 4.5.1-3)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import numpy as np
>>> np.__version__
'1.6.1rc3'
>>> np.absolute(np.nan)
nan
$ python
Python 2.7 (r27:82500, Sep 16 2010, 18:02:00)
[GCC 4.5.1 20100907 (Red Hat 4.5.1-3)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from numpy import *
>>> absolute(nan)
nan
>>>
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