Remove 2d slice from 3d numpy array

Question

I need to remove the last arrays from a 3D numpy cube. I have:

a = np.array(
[[[1,2,3],
 [4,5,6],
 [7,8,9]],

[[9,8,7],
 [6,5,4],
 [3,2,1]],

[[0,0,0],
 [0,0,0],
 [0,0,0]],

[[0,0,0],
 [0,0,0],
 [0,0,0]]])

How do I remove the arrays with zero sub-arrays like at the bottom side of the cube, using np.delete?

(I cannot simply remove all zero values, because there will be zeros in the data on the top side)

Answer 1

For a 3D cube, you might check all against the last two axes

a = np.asarray(a)
a[~(a==0).all((2,1))]

---

array([[[1, 2, 3],
        [4, 5, 6],
        [7, 8, 9]],

       [[9, 8, 7],
        [6, 5, 4],
        [3, 2, 1]]])

Answer 2

Here's one way to remove trailing all zeros slices, as mentioned in the question that we want to keep the all zeros slices in the data on the top side -

a[:-(a==0).all((1,2))[::-1].argmin()]

Sample run -

In [80]: a
Out[80]: 
array([[[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]],

       [[9, 8, 7],
        [6, 5, 4],
        [3, 2, 1]],

       [[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]],

       [[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]]])

In [81]: a[:-(a==0).all((1,2))[::-1].argmin()]
Out[81]: 
array([[[0, 0, 0],
        [0, 0, 0],
        [0, 0, 0]],

       [[9, 8, 7],
        [6, 5, 4],
        [3, 2, 1]]])