Expanding/Zooming in a numpy array

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I have the following array:

import numpy as np
a = np.array([[2, 3, 5],
              [4, 6, 7],
              [1, 5, 7]])

I want to expand it to this array: 

b = [[2 2 2 3 3 3 5 5 5]
     [2 2 2 3 3 3 5 5 5]
     [2 2 2 3 3 3 5 5 5]
     [4 4 4 6 6 6 7 7 7]
     [4 4 4 6 6 6 7 7 7]
     [4 4 4 6 6 6 7 7 7]
     [1 1 1 5 5 5 7 7 7]
     [1 1 1 5 5 5 7 7 7]
     [1 1 1 5 5 5 7 7 7]]

So I'm using the following command: 

import scipy.ndimage
b = scipy.ndimage.interpolation.zoom(a, 3, order=0)

based on this question and answer here Resampling a numpy array representing an image.

However, what I'm getting is this: 

b = [[2 2 3 3 3 3 5 5 5]
     [2 2 3 3 3 3 5 5 5]
     [4 4 6 6 6 6 7 7 7]
     [4 4 6 6 6 6 7 7 7]
     [4 4 6 6 6 6 7 7 7]
     [4 4 6 6 6 6 7 7 7]
     [1 1 5 5 5 5 7 7 7]
     [1 1 5 5 5 5 7 7 7]
     [1 1 5 5 5 5 7 7 7]]

I want the expansion to be exactly by 3, or whatever the zoom factor is, but currently it's different for each element of the array.

Is there a direct way to do this? Or shall I do it manually with some coding?

scipy zooming numpy arrays python
3 Answers

Here is my approach, which uses simple numpy functions. It returns the same dtype as the input.

import numpy as np

def zoom(a, factor):
    sx, sy = (factor * dim for dim in a.shape)
    X, Y = np.ogrid[0:sx, 0:sy]
    return a[X//factor, Y//factor]
user_3270260
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