Efficient Two Dimensional Numpy Array Statistics

I have many 100x100 grids, is there an efficient way using numpy to calculate the median for every grid point and return just one 100x100 grid with the median values? Presently, I'

Solution 1:

Create as 100x100xN array (or stack together if that's not possible) and use np.median with the correct axis to do it in one go:

import numpy as np
a = np.random.rand(100,100)
b = np.random.rand(100,100)
c = np.random.rand(100,100)
d = np.dstack((a,b,c))
result = np.median(d,axis=2)

Solution 2:

How many grids are there?

One option would be to create a 3D array that is 100x100xnumGrids and compute the median across the 3rd dimension.

Solution 3:

use axis parameter of median:

import numpy as np

data = np.random.rand(100, 5, 5)

print np.median(data, axis=0)

print np.median(data[:, 0, 0])
print np.median(data[:, 1, 0])