[Numpy-discussion] Data cube optimization for combination

[Jose Miguel Ibáñez]

Hello everyone,

does anyone know of an efficient implementation (maybe using
numpy.where statement) of the next code for data cube (3d array)
combining ?

import numpy as np

def combine( )

  cube = np.random.rand(32,2048,2048)
  result = np.zeros([2048,2048], np.float32)

   for ii in range(2048):
       for jj in range(2048):
            result[, ii, jj] = np.sqrt((cube[:,ii, jj])).sum()


It takes long time to run, however,


>> result = np.median(cube,0)


only around one second ! where is the point ? any suggestions ?



Thanks !