[Numpy-discussion] summing over more than one axis
Thu Aug 19 15:03:29 CDT 2010
Precise in what sense? Numerical accuracy? If so, why is that?
On Thu, Aug 19, 2010 at 12:13 PM, <email@example.com> wrote:
> On Thu, Aug 19, 2010 at 11:29 AM, Joe Harrington <firstname.lastname@example.org>
> > On Thu, 19 Aug 2010 09:06:32 -0500, G?khan Sever <email@example.com>
> >>On Thu, Aug 19, 2010 at 9:01 AM, greg whittier <firstname.lastname@example.org> 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
> >>> Thanks,
> >>> Greg
> >>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.
> > --jh--
> > _______________________________________________
> > NumPy-Discussion mailing list
> > NumPy-Discussion@scipy.org
> > http://mail.scipy.org/mailman/listinfo/numpy-discussion
> NumPy-Discussion mailing list
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion