[Numpy-discussion] summing over more than one axis
Thu Aug 19 14:13:16 CDT 2010
On Thu, Aug 19, 2010 at 11:29 AM, Joe Harrington <email@example.com> wrote:
> On Thu, 19 Aug 2010 09:06:32 -0500, G?khan Sever <firstname.lastname@example.org> wrote:
>>On Thu, Aug 19, 2010 at 9:01 AM, greg whittier <email@example.com> wrote:
>>> I frequently deal with 3D data and would like to sum (or find the
>>> mean, etc.) over the last two axes. I.e. sum a[i,j,k] over j and k.
>>> I find using .sum() really convenient for 2d arrays but end up
>>> reshaping 2d arrays to do this. I know there has to be a more
>>> convenient way. Here's what I'm doing
>>> a = np.arange(27).reshape(3,3,3)
>>> # sum over axis 1 and 2
>>> result = a.reshape((a.shape, a.shape*a.shape)).sum(axis=1)
>>> Is there a cleaner way to do this? I'm sure I'm missing something obvious.
>>Using two sums
>>np.sum(np.sum(a, axis=-2), axis=1)
> Be careful. This works for sums, but not for operations like median;
> the median of the row medians may not be the global median. So, you
> need to do the medians in one step. I'm not aware of a method cleaner
> than manually reshaping first. There may also be speed reasons to do
> things in one step. But, two steps may look cleaner in code.
I think, two .sums() are the most accurate, if precision matters. One
big summation is often not very precise.
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