I don't think it is a specifically Macports issue. On my (oldish)
 Macbook pro the system python & numpy with

 /usr/bin/python bench2.py takes 15 s

 while the 32/64 bit numpy I built took 52 s

 No difference between 32 and 64 bit (i.e.python-32 instead of python-64)

 Same ratio on my Mac Pro: 29s vs 10s.
 my numpy used flags in
 /Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/config/Makefile
 OPT=            -DNDEBUG -g -O3
 BASECFLAGS=     -arch i386 -arch x86_64 -isysroot /  -fno-strict-aliasing
 -fno-common -dynamic
 LDFLAGS=        -arch i386 -arch x86_64 -isysroot / -g

 system numpy presumably uses flags from
 /Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/config/Makefile
 OPT=            -DNDEBUG -g -fwrapv -Os -Wall -Wstrict-prototypes
 EXTRA_CFLAGS=    -DENABLE_DTRACE
 BASECFLAGS=      -fno-strict-aliasing -fno-common -dynamic
 LDFLAGS=        -Wl,-F.

 --George.

>
> On 8 December 2010 07:21, Konrad Hinsen <[email protected]> wrote:
>> On 07.12.2010, at 21:58, Konrad Hinsen wrote:
>>
>>> Somewhat by accident I noticed an enormous speed difference in basic NumPy 
>>> operations between my MacPorts installation (py26-numpy) and the NumPy 
>>> 1.5.1 binaries from the NumPy sourceforge site used with MacPython 2.6, 
>>> also downloaded as a binary.
>>>
>>> ~/projects/solar_system> /usr/local/bin/python bench2.py
>>> CPU time: 16 s
>>> ~/projects/solar_system> /opt/local/bin/python bench2.py
>>> CPU time: 45 s
>>
>> Update: I profiled both runs using Shark, and found that when using the 
>> MacPorts version, 57% of the total time is spent in function feclearexcept. 
>> In the MacPython run, this function doesn't even show up. This makes me 
>> suspect that the difference is in the handling of floating point numbers, 
>> specifically floating-point exceptions.
>>
>> Konrad.
>>
>> _______________________________________________
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>> [email protected]
>> http://lists.macosforge.org/mailman/listinfo.cgi/macports-users
>>
>
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