Numpy.sum() nD array of (2,2,2...n) to a 1D array of shape (2,)

Question

I want to numpy.sum() my nD arrays (matrix) of shape (2,2,2...n) to 1D arrays of shape (2,).

Basically along the axis=0. (Sum the first number of each 1d array of shape (2,) and sum the second number of the same arrays into one single resulting 1d array of shape (2,)).

However matrix.sum(axis=0) only seems to work for those of shape (2,2), while I think matrix.sum(axis=(1,2)) works for (2,2,2). But then what about (2,2,2,2) arrays and so on?

The n-dimensions have been confusing me. A generalised solution, along with a brief explanation, would be much appreciated.

EDIT: I've provided an example of the nD arrays I'm trying to sum below. I want to sum along axis=0 to get a (2,) 1D array. numpy.sum(axis=0) seems to only work for the array of shape (2,2)...

#Of shape (2,2):
[[9.99695358e-02 9.99232016e-01]
 [9.00030464e-01 7.67983971e-04]].sum(axis=0) seems to work

#Of shape (2,2,2):
[[[2.02737071e-01 7.75883149e-01]
  [2.02650032e-08 1.58192237e-02]]
 [[7.31718878e-06 1.41793363e-03]
  [4.12802168e-03 7.26350831e-06]]].sum(axis=(1,2)) seems to work

#Of shape… (2,2,2,2)
[[[[1.83819962e+00 1.02712560e-02]
   [5.05122135e-02 2.80555725e-04]]
  [[5.60304309e-07 5.44521143e-04]
   [2.41592380e-03 1.49436734e-05]]]
 [[[7.04398015e-05 7.66717944e-06]
   [1.76843337e-05 1.98868986e-06]]
  [[9.74010599e-02 1.12527543e-07]
   [2.61427056e-04 2.70778171e-08]]]].sum(axis=?) # What axis? And how to generalise?

What have you tried so far? I'd encourage you to add a minimal reproducible example illustrating what you've tried so far and to narrow this down to a specific question, otherwise this will likely keep getting downvotes and close votes. — EJoshuaS - Stand with Ukraine
– EJoshuaS - Stand with Ukraine, Commented Nov 21, 2019 at 17:53
Won't the answers to your previous question work if you simply replace multiplication * with addition +? — Divakar
– Divakar, Commented Nov 21, 2019 at 17:56

tstanisl · Accepted Answer · 2019-11-21 20:59:52Z

1

What do you think about reshaping x to 2D and summing along the second axis?

x.reshape(x.shape[0], -1).sum(axis=1)

answered Nov 21, 2019 at 20:59

tstanisl

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