Here's a vectorized approach with reshape and permute -
reshape(permute(reshape(a,size(a,1),4,[]),[1,3,2]),[],4)
Making it generic, we could introduce the number of columns as a parameter. Hence, let ncols
be that one. So, the solution becomes -
ncols = 4
reshape(permute(reshape(a,size(a,1),ncols,[]),[1,3,2]),[],ncols)
Sample run -
>> a
a =
20 79 18 82 27 23 59 66 46 21 48 95
96 83 46 49 34 88 23 42 17 27 15 54
11 88 34 92 23 62 86 56 32 32 91 54
>> reshape(permute(reshape(a,size(a,1),4,[]),[1,3,2]),[],4)
ans =
20 79 18 82
96 83 46 49
11 88 34 92
27 23 59 66
34 88 23 42
23 62 86 56
46 21 48 95
17 27 15 54
32 32 91 54
More info on the intuition behind such a General idea for nd to nd transformation, which even though originally was meant for NumPy/Python, extends to any programming paradigm in general.