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.
-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
> --------------------------------------------------
>
>
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>
>
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