Numpy concatenate arrays with interleaving

Question

I have 4 arrays and I want to concatenate them into one single array with interleaving. How do I do this?

>>> import numpy as np
>>> a = np.tile(0,(5,2))
>>> b = np.tile(1,(5,2))
>>> c = np.tile(2,(5,2))
>>> d = np.tile(3,(5,2))
>>> e = np.concatenate((a,b,c,d),axis=1)
>>> e
    array([[0, 0, 1, 1, 2, 2, 3, 3],
           [0, 0, 1, 1, 2, 2, 3, 3],
           [0, 0, 1, 1, 2, 2, 3, 3],
           [0, 0, 1, 1, 2, 2, 3, 3],
           [0, 0, 1, 1, 2, 2, 3, 3]])

This gives just the concatenation.

However, my desired_output is:

>>> desired_output
    array([[0, 1, 2, 3, 0, 1, 2, 3],
           [0, 1, 2, 3, 0, 1, 2, 3],
           [0, 1, 2, 3, 0, 1, 2, 3],
           [0, 1, 2, 3, 0, 1, 2, 3],
           [0, 1, 2, 3, 0, 1, 2, 3]])

I mean I know I can select the interleaved columns from e using:

>>> f = e[:, ::2]
>>> array([[0, 1, 2, 3],
           [0, 1, 2, 3],
           [0, 1, 2, 3],
           [0, 1, 2, 3],
           [0, 1, 2, 3]])

But how do I make one big array?

score 5 · Accepted Answer · answered Nov 22 '17 at 09:18

5

Use np.dstack or np.stack to stack along the last axis that gives us a 3D array and then reshape back to 2D -

np.dstack([a,b,c,d]).reshape(a.shape[0],-1)
np.stack([a,b,c,d],axis=2).reshape(a.shape[0],-1)

answered Nov 22 '17 at 09:18

Divakar

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Sweet!! Thanks man! That was really fast. Do you do this for a living or what? =) – bFig8 Nov 22 '17 at 09:33
@bFig8 Mostly ;) – Divakar Nov 22 '17 at 09:35
@bFig8 If you are asking about that `-1`, here's something to help out - https://stackoverflow.com/questions/41776579/. – Divakar Nov 22 '17 at 10:04

Numpy concatenate arrays with interleaving

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