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'
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
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