ehum,then I must have done something wrong. I get the same results doing your example. But, when I use my data, i.e. a cube of shape (30,512,512) and run the different median I get different answers. Although not with your example data (taking shape to be 10,2,5 or something). (data at http://magnusp.homeip.net/data0.fits) code: a = pyfits('data0.fits') a.mean() 90.328727213541669 ndimage.mean(a) 93.617742029825848 weird, or is it just me again? Max Shron wrote:
Can you show us a minimal example where you get different behavior? I'm getting the same result for simple 2d arrays like x = arange(100) x.shape = (10,10) scipy.ndimage,mean(x) -> 49.5 np.mean(x) -> 49.5
Max
On Thu, Sep 10, 2009 at 8:43 AM, n.l.o <magnusp@astro.su.se> wrote:
Hello
I was wondering what the difference is between numpy.mean() and the scipy.ndimage.mean() method?
I get different answers.
Also is there a difference in using the different std() and median() method etc.?
I am applying the methods on 2-D arrays.
Cheers Magnus -- View this message in context: http://www.nabble.com/difference-between-different-mean%28%29s-tp25383547p25... Sent from the Scipy-User mailing list archive at Nabble.com.
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