[Numpy-discussion] bug in numpy.mean() ?

josef.pktd@gmai... josef.pktd@gmai...
Tue Jan 24 23:16:55 CST 2012


On Wed, Jan 25, 2012 at 12:03 AM, Charles R Harris
<charlesr.harris@gmail.com> wrote:
>
>
> On Tue, Jan 24, 2012 at 4:21 PM, Kathleen M Tacina
> <Kathleen.M.Tacina@nasa.gov> wrote:
>>
>> I found something similar, with a very simple example.
>>
>> On 64-bit linux, python 2.7.2, numpy development version:
>>
>> In [22]: a = 4000*np.ones((1024,1024),dtype=np.float32)
>>
>> In [23]: a.mean()
>> Out[23]: 4034.16357421875
>>
>> In [24]: np.version.full_version
>> Out[24]: '2.0.0.dev-55472ca'
>>
>>
>> But, a Windows XP machine running python 2.7.2 with numpy 1.6.1 gives:
>> >>>a = np.ones((1024,1024),dtype=np.float32)
>> >>>a.mean()
>> 4000.0
>> >>>np.version.full_version
>> '1.6.1'
>>
>>
>
> Yes, the results are platform/compiler dependent. The 32 bit platforms tend
> to use extended precision accumulators and the x87 instruction set. The 64
> bit platforms tend to use sse2+. Different precisions, even though you might
> think they are the same.

just to confirm, same computer as before but the python 3.2 version is
64 bit, now I get the "Linux" result

Python 3.2 (r32:88445, Feb 20 2011, 21:30:00) [MSC v.1500 64 bit
(AMD64)] on win32

>>> import numpy as np
>>> np.__version__
'1.5.1'
>>> a = 4000*np.ones((1024,1024),dtype=np.float32)
>>> a.mean()
4034.16357421875
>>> a.mean(0).mean(0)
4000.0
>>> a.mean(dtype=np.float64)
4000.0

Josef

>
> <snip>
>
> Chuck
>
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