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pythonarraysnumpyscaling

How to "scale" a numpy array?

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?

Solution

  • 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]])