What I have is some C++ functions that implement statistic functions. What I need is some kind of ufunc where I can "plug" my functions. But I doesn't seem to exist an ufunc that operates on a N-d array and turns it into a number. 2011/4/12 Keith Goodman <kwgoodman@gmail.com>:
On Mon, Apr 11, 2011 at 2:36 PM, Sergio Pascual <sergio.pasra@gmail.com> wrote:
Hi list.
For mi application, I would like to implement some new statistics functions over numpy arrays, such as truncated mean. Ideally this new function should have the same arguments than numpy.mean: axis, dtype and out. Is there a way of writing this function that doesn't imply writing it in C from scratch?
I have read the documentation, but as far a I see ufuncs convert a N dimensional array into another and generalized ufuncs require fixed dimensions. numpy mean converts a N dimensional array either in a number or a N - 1 dimensional array.
Here's a slow, brute force method:
a = np.arange(9).reshape(3,3) a array([[0, 1, 2], [3, 4, 5], [6, 7, 8]]) idx = a > 6 b = a. copy() b[idx] = 0 b array([[0, 1, 2], [3, 4, 5], [6, 0, 0]]) 1.0 * b.sum(axis=0) / (~idx).sum(axis=0) array([ 3. , 2.5, 3.5])
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-- Sergio Pascual http://guaix.fis.ucm.es/~spr gpg fingerprint: 5203 B42D 86A0 5649 410A F4AC A35F D465 F263 BCCC Departamento de Astrofísica -- Universidad Complutense de Madrid (Spain)