24 Jan
2012
24 Jan
'12
11:12 p.m.
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