[python] Reshape an array in NumPy

There are two possible result rearrangements (following example by @eumiro). Einops package provides a powerful notation to describe such operations non-ambigously

>> a = np.arange(18).reshape(9,2)

# this version corresponds to eumiro's answer
>> einops.rearrange(a, '(x y) z -> z y x', x=3)

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

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

# this has the same shape, but order of elements is different (note that each paer was trasnposed)
>> einops.rearrange(a, '(x y) z -> z x y', x=3)

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

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

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