I want to do something like this:
I give a 2D numpy array:
[[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9]]
And I want to get a 3D numpy array:
[[[1, 1, 1],
[2, 2, 2],
[3, 3, 3]],
[[4, 4, 4],
[5, 5, 5],
[6, 6, 6]],
[[7, 7, 7],
[8, 8, 8],
[9, 9, 9]]]
Does numpy has a function that can do this transformation?
One can use np.tile. Before doing this, a dimension needs to be added at the end of the array.
In [28]: x = np.array([[ 1, 2, 3],
...: [ 4, 5, 6],
...: [ 7, 8, 9]])
In [29]: np.tile(x[..., None], 3)
Out[29]:
array([[[1, 1, 1],
[2, 2, 2],
[3, 3, 3]],
[[4, 4, 4],
[5, 5, 5],
[6, 6, 6]],
[[7, 7, 7],
[8, 8, 8],
[9, 9, 9]]])
First extend the dimension of 2D array using arr[:, :, np.newaxis], this changes dimension from (3, 3) to (3, 3, 1). Now repeat this 3D array along the third dimension.
Use:
arr = np.repeat(arr[:, :, np.newaxis], 3, -1)
Output:
>>> np.repeat(arr[:, :, np.newaxis], 3, -1)
array([[[1, 1, 1],
[2, 2, 2],
[3, 3, 3]],
[[4, 4, 4],
[5, 5, 5],
[6, 6, 6]],
[[7, 7, 7],
[8, 8, 8],
[9, 9, 9]]])
