How to "scale" a numpy array?

Question

I would like to scale an array of shape (h, w) by a factor of n, resulting in an array of shape (h*n, w*n), with the.

Say that I have a 2x2 array:

array([[1, 1],        [0, 1]]) 

I would like to scale the array to become 4x4:

array([[1, 1, 1, 1],        [1, 1, 1, 1],        [0, 0, 1, 1],        [0, 0, 1, 1]]) 

That is, the value of each cell in the original array is copied into 4 corresponding cells in the resulting array. Assuming arbitrary array size and scaling factor, what's the most efficient way to do this?

Answer 1

You should use the Kronecker product, numpy.kron:

Computes the Kronecker product, a composite array made of blocks of the second array scaled by the first

import numpy as np a = np.array([[1, 1],               [0, 1]]) n = 2 np.kron(a, np.ones((n,n))) 

which gives what you want:

array([[1, 1, 1, 1],        [1, 1, 1, 1],        [0, 0, 1, 1],        [0, 0, 1, 1]])