sum numpy ndarray with 3d array along a given axis 1

Question

I have an numpy ndarray with shape (2,3,3),for example:

array([[[ 1,  2,  3],
    [ 4,  5,  6],
    [12, 34, 90]],

   [[ 4,  5,  6],
    [ 2,  5,  6],
    [ 7,  3,  4]]])

I am getting lost in np.sum(above ndarray ,axis=1), why that answer is:

array([[17, 41, 99],
   [13, 13, 16]])

Thanks

Answer 1

Axes are defined for arrays with more than one dimension. A 2-dimensional array has two corresponding axes: the first running vertically downwards across rows (axis 0), and the second running horizontally across columns (axis 1).

Let A be the array, then in your example when the axis is 1, [i,:,k] is added. Likewise, for axis 0, [:,j,k] are added and when axis is 2, [i,j,:] are added.

A = np.array([
   [[ 1,  2,  3],[ 4,  5,  6], [12, 34, 90]],
   [[ 4,  5,  6],[ 2,  5,  6], [ 7,  3,  4]]
])

np.sum(A,axis = 0)
    array([[ 5,  7,  9],
           [ 6, 10, 12],
           [19, 37, 94]])
np.sum(A,axis = 1)
    array([[17, 41, 99],
           [13, 13, 16]])
np.sum(A,axis = 2)
    array([[ 6, 15,136],
           [15, 13, 14]])