Some time ago I asked this question http://stackoverflow.com/questions/25486506/julia-broadcasting-equivalent-of-numpy-newaxis
As a more interesting example, here is some real python code I use: dist = mag_sqr (demod_out[:,np.newaxis] - const.map[np.newaxis,:]) where demod_out, const.map are each vectors, mag_sqr performs element-wise euclidean distance, and the result is a 2D array whose 1st axis matches the 1st axis of demod_out, and the 2nd axis matches the 2nd axis of const.map. >From the answers I've seen, julia doesn't really have an equivalent functionality. The idea here is, without allocating a new array, manipulate the strides to cause broadcasting. AFAICT, the best for Julia would be just forget the vectorized code, and explicitly write out loops to perform the computation. OK, I guess, but maybe not as readable. Is there any news on this front?
