Numpy Matrix tiling and multiplication combination

December 12, 2024

I’m looking for a function capable of taking a m x n array, which repeats each row n times over a identity-like grid of m size.

For demo:

input = [[a1, b1, c1],
         [a2, b2, c2]]

output = [[a1, b1, c1,  0,  0,  0],
          [a1, b1, c1,  0,  0,  0],
          [a1, b1, c1,  0,  0,  0],
          [ 0,  0,  0, a2, b2, c2],
          [ 0,  0,  0, a2, b2, c2],
          [ 0,  0,  0, a2, b2, c2]]

Last time I asked something similar I was told of the Kronecker product, is there some similar function?

>Solution :

Not very elegant perhaps (and I already sense more elegant answers incoming), but it does the job:

import numpy as np
import scipy

a = np.asarray([[11, 21, 31],  [21, 22, 32], [31, 32, 33]])
print(a)
# [[11 21 31]
#  [21 22 32]
#  [31 32 33]]

blocked = scipy.linalg.block_diag(*a)
print(blocked)
# [[11 21 31  0  0  0  0  0  0]
#  [ 0  0  0 21 22 32  0  0  0]
#  [ 0  0  0  0  0  0 31 32 33]]

result = np.repeat(blocked, a.shape[1], axis=0)
print(result)
# [[11 21 31  0  0  0  0  0  0]
#  [11 21 31  0  0  0  0  0  0]
#  [11 21 31  0  0  0  0  0  0]
#  [ 0  0  0 21 22 32  0  0  0]
#  [ 0  0  0 21 22 32  0  0  0]
#  [ 0  0  0 21 22 32  0  0  0]
#  [ 0  0  0  0  0  0 31 32 33]
#  [ 0  0  0  0  0  0 31 32 33]
#  [ 0  0  0  0  0  0 31 32 33]]