Hi, Sorry, I've been away in Oregon...
The result isn't quite the same. The arrays must be in the range [0,1], so I just have it divide x3 and y. I also have it add 1 to size[1], as I realized that was also necessary for that behavior: x = np.arange(size[0]) x2 = np.column_stack([x,x+1]).reshape([-1,1]) x3 = np.array(x2.repeat(size[1]+1,axis=1).flatten(),"f") y = np.array(np.arange(size[1]+1).repeat(size[0]*2),"f") array = np.zeros([len(y),3]) array[:,0] = x3/size[0] array[:,1] = y/size[1] array = np.array(array,"f") When size is [3,2], the result from this code is: [[ 0. 0. 0. ] [ 0. 0. 0. ] [ 0. 0. 0. ] [ 0.33333334 0. 0. ] [ 0.33333334 0. 0. ] [ 0.33333334 0. 0. ] [ 0.33333334 0.5 0. ] [ 0.33333334 0.5 0. ] [ 0.33333334 0.5 0. ] [ 0.66666669 0.5 0. ] [ 0.66666669 0.5 0. ] [ 0.66666669 0.5 0. ] [ 0.66666669 1. 0. ] [ 0.66666669 1. 0. ] [ 0.66666669 1. 0. ] [ 1. 1. 0. ] [ 1. 1. 0. ] [ 1. 1. 0. ]] The correct output is: [[ 0. 0. 0. ] [ 0.33333334 0. 0. ] [ 0. 0.5 0. ] [ 0.33333334 0.5 0. ] [ 0. 1. 0. ] [ 0.33333334 1. 0. ] [ 0.33333334 0. 0. ] [ 0.66666669 0. 0. ] [ 0.33333334 0.5 0. ] [ 0.66666669 0.5 0. ] [ 0.33333334 1. 0. ] [ 0.66666669 1. 0. ] [ 0.66666669 0. 0. ] [ 1. 0. 0. ] [ 0.66666669 0.5 0. ] [ 1. 0.5 0. ] [ 0.66666669 1. 0. ] [ 1. 1. 0. ]] Thanks, Ian
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