data wrangling with numpy arrays-CodePudding

Suppose I get a 2d numpy array as an output after each for loop for processing multiple data files.

I intend to stack all 2d numpy arrays every time one loop ends. At the end, I want to get only one 2d numpy array which contains the average of all 2d arrays.

For instance, if I get following arrays after 2 loops,

arr1 = np.arange(1, 10).reshape(3, 3)
array([[1, 2, 3],
       [4, 5, 6],
       [7, 8, 9]])
arr2 = np.arange(10, 19).reshape(3, 3)
array([[10, 11, 12],
       [13, 14, 15],
       [16, 17, 18]])

I want to get the following array as a final output (outside of the for loop).

array([[5.5, 6.5, 7.5],
       [8.5, 9.5, 10.5],
       [11.5, 12.5, 13.5]])

I'd appreciate any idea how to (to which direction) stack 2d arrays so that I can obtain the final output with the average.

If there is an ambiguity, I'm happy to provide more backgrounds.

CodePudding user response：

Are you looking for dstack?

np.dstack([arr1, arr2])

Output:

array([[[ 1, 10],
        [ 2, 11],
        [ 3, 12]],

       [[ 4, 13],
        [ 5, 14],
        [ 6, 15]],

       [[ 7, 16],
        [ 8, 17],
        [ 9, 18]]])

For the average:

np.dstack([arr1, arr2]).mean(2)

Output:

array([[ 5.5,  6.5,  7.5],
       [ 8.5,  9.5, 10.5],
       [11.5, 12.5, 13.5]])