import numpy as np
from time import process_time as T

N=10000
a = np.random.rand(N,N,3)
# values are stored  a[0,0,0] a[0,0,1] a[0,0,2] ... a[0,0,N] a[0,1,0] a[0,1,1] ... 
tic = T()
a[:,:,0] = a[:,:,1] # values are far in memory, collecting them is slow
a[:,:,2] = a[:,:,0]
a[:,:,1] = a[:,:,2] # ahem, this is *not* a swapping operation
toc = T() - tic
print(toc,"seconds using (N,N,3) in default row major order")

# change index order to fortran's column major order
# values are stored  a[0,0,0] a[1,0,0] a[2,0,0] ... a[N,0,0] a[0,1,0] a[1,1,0] ...
a = np.random.rand(N,N,3)
tic = T()
a = np.asfortranarray(a) # this takes time
a[:,:,0] = a[:,:,1] # values are consequtive in memory, collecting them is fast
a[:,:,2] = a[:,:,0]
a[:,:,1] = a[:,:,2]
toc = T() - tic
print(toc,"seconds using (N,N,3) in column major order")

# same size task, but define the array in different order to begin with
a = np.random.rand(3,N,N)
tic = T()
a[0,:,:] = a[1,:,:] # values are consequtive in memory, collecting them is fast
a[2,:,:] = a[0,:,:]
a[1,:,:] = a[2,:,:]
toc = T() - tic
print(toc,"seconds using (3,N,N) in default row major order")
#0.9668405870000001 seconds using (N,N,3) in default row major order
#0.9624588530000002 seconds using (N,N,3) in column major order 
#0.12479739399999978 seconds using (3,N,N) in default row major order