If I have a 2d array like:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
And I want to end up with a 3d array like:
array([[[0, 4, 8],
[1, 5, 9]],
[[2, 6, 10],
[3, 7, 11]]])
How should I reshape the array to get what I want?
In [11]: a # Input array
Out[11]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
In [12]: a.reshape(-1,2,2).transpose(1,2,0)
Out[12]:
array([[[ 0, 4, 8],
[ 1, 5, 9]],
[[ 2, 6, 10],
[ 3, 7, 11]]])
With np.moveaxis -
np.moveaxis(a.reshape(-1,2,2), 0,-1)
Generalizing it and assuming that you want the length along the first axis as half of no. of columns -
In [16]: m,n = a.shape
In [17]: a.reshape(m,-1,2).transpose(1,2,0)
Out[17]:
array([[[ 0, 4, 8],
[ 1, 5, 9]],
[[ 2, 6, 10],
[ 3, 7, 11]]])
If that length is supposed to be 2 -
In [15]: a.reshape(m,2,-1).transpose(1,2,0)
Out[15]:
array([[[ 0, 4, 8],
[ 1, 5, 9]],
[[ 2, 6, 10],
[ 3, 7, 11]]])
