numpy 3D array reshape/flattern to 1D array based on row order

Question

I have a 3D NumPy array

x = np.array([[[0, 0, 0, 0],
               [1, 1, 1, 1],
               [2, 2, 2, 2]],

              [[0, 0, 0, 0],
               [1, 1, 1, 1],
               [2, 2, 2, 2]]])

If I want to flatten the 3D array to 1D array by taking row n°0 of x[0], row n°0 of x[1], row n°1 of x[0], row n°1 of x[1], row n°2 of x[0], row n°2 of x[1], and get the following layout:

[0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2]

How can I achieve this? Tried to reshape, flatten, none of them worked.

Ivan · Accepted Answer · 2021-08-25 15:24:49Z

1

You can stack then flatten the array:

>>> np.stack(x, axis=1).flatten()
array([0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2])

answered Aug 25, 2021 at 15:24

Ivan

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1 Comment

mit10000 Over a year ago

Worked like a charm! Thanks.

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