Those coming to Julia from languages like Python, R, Matlab/Octave, etc.
have it ingrained in them to "fear the loop" and to perform loop-like
calculations in "verbose and convoluted" ways. It is actually quite easy
to do this calculation in Julia with very little storage allocation by
writing three nested loops.
function mindist(pos::Matrix{Float64}, Acp::Matrix{Float64})
m,n = size(pos)
r,s = size(Acp)
m == r || throw(DimensionMismatch(""))
res = fill(Inf,(n,))
for i in 1:n
for j in 1:s
sm = 0.
for k in 1:m
sm += abs2(pos[k,i] - Acp[k,j])
end
if sm < res[i]
res[i] = sm
end
end
end
res
end
On my machine timing the second execution (the first execution includes
compile time) I get
julia> @time mindist(pos,Acp);
elapsed time: 0.002806999 seconds (744 bytes allocated)
