On Dec 8, 2010, at 9:28 AM, Eric A. Borisch wrote:
> == Executive summary ==
> The OS python has different numpy exception handling settings, and this is
> the reason for the performance difference.
>
> == The brief results ==
> with numpy.seterr(all='ignore') -> 13s system, 12s macports
> with numpy.seterr(all='print') and numpy.seterr(under='ignore') -> 56s
> system, 46s macports
>
> == The extended desription ==
> By adding the following after the imports to bench2.py:
>
> old = numpy.seterr(all='ignore')
> print old
>
> We get these results:
>
> MacPro:Downloads$ /usr/bin/python bench2.py
> {'over': 'ignore', 'divide': 'ignore', 'invalid': 'ignore', 'under': 'ignore'}
> CPU time: 13 s
>
> MacPro:Downloads$ /opt/local/bin/python bench2.py
> {'over': 'print', 'divide': 'print', 'invalid': 'print', 'under': 'ignore'}
> CPU time: 12 s
>
> Without the changes, the system python is still 13s, but the macports python
> is 46s. By setting the error handling on the system python to match the
> macports default (print, print, print, ignore) the system python takes 56s.
>
> == Conclusion ==
>
> I haven't looked at how or why these settings are different, but I believe
> this is the culprit.
Nice detective work. I can confirm that setting "numpy.seterr(all='ignore')"
causes the benchmark to run at the faster time.
Cheers!
Frank
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