Stacking a single 2D array into 3D efficiently

Question

I have a single 2D array that I want to stack identical versions of into a third dimension, specifically axis=1 . The following code does the job, but it's very slow for a 2D array of size (300,300) stacked into a third-dimension of length 300.

arr_2d = arr_2d.reshape(arr_2d.shape[0],arr_2d.shape[1],1)
arr_3d = np.empty((sampling,sampling,sampling)) # allocate space 
arr_3d = [arr_3d[:,:,i]==arr_2d for i in range(sampling)]

Is there a better, more efficient way of doing this?

Answer 1

You can use numpy.repeat after you add a new third dimension to stack on:

import numpy as np
arr = np.random.rand(300, 300)
# arr.shape => (300, 300)
dup_arr = np.repeat(arr.reshape(*arr.shape, 1), repeats=10, axis=-1)
# dup_arr.shape => (300, 300, 10)

As commented by @xdurch0 and since you're stacking your copies along the last dimension, you can also use numpy.tile:

dup_arr = np.tile(arr.reshape(*arr.shape, 1), reps=10)
# dup_arr.shape => (300, 300, 10)