I have a 4d numpy array which represents a dataset with 3d instances.
Lets say that the shape of the array is (32, 32, 3, 73257).
How can i change the shape of the array to (73257, 32, 32, 3)?
--- Question update It seems that both rollaxis and transpose do the trick.
Thanx for replying!
The np.transpose function does exactly what you want, you can pass an axis argument which controls which axis you want to swap:
a = np.empty((32, 32, 3, 73257))
b = np.transpose(a, (3, 0, 1, 2))
The axis of b are permuted versions of the ones of a: the axis 0 of b is the 3-rd axis of a, the axis 1 of b is the 0-th axis of a, etc...
That way, you can specify which of the axis of size 32 you want in second or in third place:
b = np.transpose(a, (3, 1, 0, 2))
Also gives an array of the desired shape, but is different from the previous one.
It looks like np.rollaxis(arr, axis=-1) will do what you want. Example:
>>> arr = np.empty(32, 32, 3, 73257)
>>> arr2 = np.rollaxis(arr, axis=-1)
>>> arr2.shape
(73257, 32, 32, 3)
This will make arr[i,j,k,l] == arr2[l,i,j,k] for all ijkl
