I define an array as :
XRN =np.array([[[0,1,0,1,0,1,0,1,0,1],
[0,1,1,0,0,1,0,1,0,1],
[0,1,0,0,1,1,0,1,0,1],
[0,1,0,1,0,0,1,1,0,1],],
[[0,1,0,1,0,1,1,0,0,1],
[0,1,0,1,0,1,0,1,1,0],
[1,1,1,0,0,0,0,1,0,1],
[0,1,0,1,0,0,1,1,0,1],],
[[0,1,0,1,0,1,1,1,0,0],
[0,1,0,1,1,1,0,1,0,0],
[0,1,0,1,1,0,0,1,0,1],
[0,1,0,1,0,0,1,1,0,1],]])
print(XRN.shape,XRN)
XRN_LEN = XRN.shape[1]
I can obtain the sum of inner matrix with :
XRN_UP = XRN.sum(axis=1)
print("XRN_UP",XRN_UP.shape,XRN_UP)
XRN_UP (3, 10) [[0 4 1 2 1 3 1 4 0 4]
[1 4 1 3 0 2 2 3 1 3]
[0 4 0 4 2 2 2 4 0 2]]
I want to get the sum of all diagonals with the same shape (3,10)
I tested the code :
RIGHT = [XRN.diagonal(i,axis1=0,axis2=1).sum(axis=1) for i in range(XRN_LEN)]
np_RIGHT = np.array(RIGHT)
print("np_RIGHT=",np_RIGHT.shape,np_RIGHT)
but got
np_RIGHT= (4, 10) [[0 3 0 3 1 2 0 3 1 2]
[1 3 2 1 0 1 1 3 0 3]
[0 2 0 1 1 1 1 2 0 2]
[0 1 0 1 0 0 1 1 0 1]]
I checked all values for axis1 and axis 2 but never got the shape(3,10) : How can I do ?
axis1 axis2 shape
0 1 (4,10)
0 2 (4,4)
1 0 (4,10)
1 2 (4,3)
2 0 (4,4)
2 1 (4,3)
If I understand correctly, you want to sum all possible diagonals on the three elements separately. If that's the case, then you must apply np.diagonal on axis1=1 and axis2=2. This way, you end up with 10 diagonals per element which you sum down to 10 values per element. There are 3 elements, so the resulting shape is (10, 3):
>>> np.array([XRN.diagonal(i, 1, 2).sum(1) for i in range(XRN.shape[-1])])
array([[2, 3, 2],
[2, 1, 2],
[1, 1, 2],
[3, 2, 3],
[2, 2, 2],
[2, 2, 2],
[2, 3, 3],
[2, 2, 2],
[1, 0, 0],
[1, 1, 0]])