Append a "layer" to 3D-Array with Numpy

Question

I have a numpy array with dimensions 12 x 12 x 4. Now I'm trying to add an extra layer to this cube resulting in a 12 x 13 x 4 array. This 13th layer should contain the corresponding indices from the first axis, so for example addressing [7, 13, :] results in [7, 7, 7, 7].

Hard to explain but maybe someone has some advice on how to achieve this with numpy?

EDIT: I've found a solution, though it seems a little overcomplicated:

# Generate extra layer
layer = np.repeat(np.arange(0, 12)[:, np.newaxis], data.shape[2], axis=1)

# Get dimensions right...
layer = np.expand_dims(layer, axis=1)

# ... and finally append to data
result = np.append(data, layer, axis=1)

Still open for better suggestions.

Use concatenate. But be careful about dimensions.

hpaulj
– hpaulj

2018-02-06 15:47:27 +00:00
Commented Feb 6, 2018 at 15:47 — hpaulj
– hpaulj, Commented Feb 6, 2018 at 15:47

hpaulj · Accepted Answer · 2018-02-06 17:50:18Z

2

You have the right idea. A slight simplification:

layer = np.repeat(np.arange(3)[:,None,None], data.shape[2], axis=2)
result = np.concatenate((data, layer), axis=1)

answered Feb 6, 2018 at 17:50

hpaulj

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