I have image data stored in a 3D array. the code is pretty simple, but what i don't like about it is needing to transpose the array twice. here's the code... def map_rgb_array(surf, a): "returns an array of 2d mapped pixels from a 3d array" #image info needed to convert map rgb data loss = surf.get_losses[:3] shift = surf.get_shifts()[:3] prep = a >> loss << shift return transpose(bitwise_or.reduce(transpose(prep))) once i get to the 'prep' line, my 3d image has all the values for R,G,B mapped to the appropriate bitspace. all i need to do is bitwise_or the values together "finalcolor = R|G|B". this is where my lack of guru-ness with numpy comes in. the only way i could figure to do this was transpose the array and then apply the bitwise_or. only problem is then i need to de-transpose the array to get it back to where i started. is there some form or mix of bitwise_or i can use to make it operate on the 3rd axis instead of the 1st? thanks all, hopefully this can be improved. legibility comes second to speed as a priority :] ... hmm, tinkering time passes ... i did find this, "prep[:,:,0] | prep[:,:,1] | prep[:,:,2]". is something like that going to be best? "bitwise_or.reduce((prep[:,:,0], prep[:,:,1], prep[:,:,2]))"