Concatenate two numpy arrays in the 4th dimension

Question

I have two numpy arrays with three dimensions (3 x 4 x 5) and I want to concatenate them so the result has four dimensions (3 x 4 x 5 x 2). In Matlab, this can be done with

Answer 1

The accepted answer above is great. But I'll add the following because I'm a math dork and it's a nice use of the fact that a.shape is a.T.shape[::-1]...i.e. taking a transpose reverses the order of the indices of a numpy array. So if you have your building blocks in an array called blocks, then the solution above is:

new = np.concatenate([block[..., np.newaxis] for block in blocks],
                     axis=len(blocks[0].shape))

but you could also do

new2 = np.array([block.T for block in blocks]).T

which I think reads more cleanly. It's worth noting that the already-accepted answer runs more quickly:

%%timeit
new = np.concatenate([block[..., np.newaxis] for block in blocks],
                     axis=len(blocks[0].shape))
1000 loops, best of 3: 321 µs per loop

while

%%timeit
new2 = np.array([block.T for block in blocks]).T
1000 loops, best of 3: 407 µs per loop