I have a numpy array of size nxm. I want the number of columns to be limited to k and rest of the columns to be extended in new rows. Following is the scenario -
Initial array: nxm
Final array: pxk
where p = (m/k)*n
Eg. n = 2, m = 6, k = 2
Initial array:
[[1, 2, 3, 4, 5, 6,],
[7, 8, 9, 10, 11, 12]]
Final array:
[[1, 2],
[7, 8],
[3, 4],
[9, 10],
[5, 6],
[11, 12]]
I tried using reshape but not getting the desired result.
Here's one way to do it
q=array([[1, 2, 3, 4, 5, 6,],
[7, 8, 9, 10, 11, 12]])
r=q.T.reshape(-1,2,2)
s=r.swapaxes(1,2)
t=s.reshape(-1,2)
as a one liner,
q.T.reshape(-1,2,2).swapaxes(1,2).reshape(-1,2)
array([[ 1, 2],
[ 7, 8],
[ 3, 4],
[ 9, 10],
[ 5, 6],
[11, 12]])
EDIT: for the general case, use
q=arange(1,1+n*m).reshape(n,m) #example input
r=q.T.reshape(-1,k,n)
s=r.swapaxes(1,2)
t=s.reshape(-1,k)
one liner is:
q.T.reshape(-1,k,n).swapaxes(1,2).reshape(-1,k)
example for n=3,m=12,k=4
q=array([[ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12],
[13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24],
[25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]])
result is
array([[ 1, 2, 3, 4],
[13, 14, 15, 16],
[25, 26, 27, 28],
[ 5, 6, 7, 8],
[17, 18, 19, 20],
[29, 30, 31, 32],
[ 9, 10, 11, 12],
[21, 22, 23, 24],
[33, 34, 35, 36]])
Using numpy.vstack and numpy.hsplit:
a = np.array([[1, 2, 3, 4, 5, 6,],
[7, 8, 9, 10, 11, 12]])
n, m, k = 2, 6, 2
np.vstack(np.hsplit(a, m/k))
result array:
array([[ 1, 2],
[ 7, 8],
[ 3, 4],
[ 9, 10],
[ 5, 6],
[11, 12]])
UPDATE As flebool commented, above code is very slow, because hsplit returns a python list, and then vstack reconstructs the final array from a list of arrays.
Here's alternative solution that is much faster.
a.reshape(-1, m/k, k).transpose(1, 0, 2).reshape(-1, k)
or
a.reshape(-1, m/k, k).swapaxes(0, 1).reshape(-1, k)
hsplit returns a python list, and then vstack reconstructs the final array from a list of arrays. This is much slower.