On Tue, Jan 24, 2012 at 7:21 PM, eat <e.antero.ta...@gmail.com> wrote:
> Hi
>
> On Wed, Jan 25, 2012 at 1:21 AM, Kathleen M Tacina <
> kathleen.m.tac...@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'
>>
> This indeed looks very nasty, regardless of whether it is a version or
> platform related problem.
>
Looks like platform specific, same result as -eat
Windows 7,
Python 2.6.5 (r265:79096, Mar 19 2010, 21:48:26) [MSC v.1500 32 bit
(Intel)] on win32
>>> a = np.ones((1024,1024),dtype=np.float32)
>>> a.mean()
1.0
>>> (4000*a).dtype
dtype('float32')
>>> (4000*a).mean()
4000.0
>>> b = np.load("data.npy")
>>> b.mean()
3045.7471999999998
>>> b.shape
(1000, 1000)
>>> b.mean(0).mean(0)
3045.7472499999999
>>> _.dtype
dtype('float64')
>>> b.dtype
dtype('float32')
>>> b.mean(dtype=np.float32)
3045.7471999999998
Josef
>
> -eat
>
>>
>>
>>
>> On Tue, 2012-01-24 at 17:12 -0600, eat wrote:
>>
>> Hi,
>>
>>
>>
>> Oddly, but numpy 1.6 seems to behave more consistent manner:
>>
>>
>>
>> In []: sys.version
>>
>> Out[]: '2.7.2 (default, Jun 12 2011, 15:08:59) [MSC v.1500 32 bit
>> (Intel)]'
>>
>> In []: np.version.version
>>
>> Out[]: '1.6.0'
>>
>>
>>
>> In []: d= np.load('data.npy')
>>
>> In []: d.dtype
>>
>> Out[]: dtype('float32')
>>
>>
>>
>> In []: d.mean()
>>
>> Out[]: 3045.7471999999998
>>
>> In []: d.mean(dtype= np.float32)
>>
>> Out[]: 3045.7471999999998
>>
>> In []: d.mean(dtype= np.float64)
>>
>> Out[]: 3045.747251076416
>>
>> In []: (d- d.min()).mean()+ d.min()
>>
>> Out[]: 3045.7472508750002
>>
>> In []: d.mean(axis= 0).mean()
>>
>> Out[]: 3045.7472499999999
>>
>> In []: d.mean(axis= 1).mean()
>>
>> Out[]: 3045.7472499999999
>>
>>
>>
>> Or does the results of calculations depend more on the platform?
>>
>>
>>
>>
>>
>> My 2 cents,
>>
>> eat
>>
>> --
>> --------------------------------------------------
>> Kathleen M. Tacina
>> NASA Glenn Research Center
>> MS 5-10
>> 21000 Brookpark Road
>> Cleveland, OH 44135
>> Telephone: (216) 433-6660
>> Fax: (216) 433-5802
>> --------------------------------------------------
>>
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
