Reshape an array in NumPy

arrays, numpy, python, reshape

Solution

a = np.arange(18).reshape(9,2)
b = a.reshape(3,3,2).swapaxes(0,2)

# a: 
array([[ 0,  1],
       [ 2,  3],
       [ 4,  5],
       [ 6,  7],
       [ 8,  9],
       [10, 11],
       [12, 13],
       [14, 15],
       [16, 17]])


# b:
array([[[ 0,  6, 12],
        [ 2,  8, 14],
        [ 4, 10, 16]],

       [[ 1,  7, 13],
        [ 3,  9, 15],
        [ 5, 11, 17]]])

Problem

Consider an array of the following form (just an example): ``` [[ 0 1] [ 2 3] [ 4 5] [ 6 7] [ 8 9] [10 11] [12 13] [14 15] [16 17]] ``` It's shape is [9,2]. Now I want to transform the array so that each column becomes a shape [3,3], like this: ``` [[ 0 6 12] [ 2 8 14] [ 4 10 16]] [[ 1 7 13] [ 3 9 15] [ 5 11 17]] ``` The most obvious (and surely "non-pythonic") solution is to initialise an array of zeroes with the proper dimension and run two for-loops where it will be filled with data. I'm interested in a solution that is language-conform...

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