My vectorized code is slower than a loop

[Dave Cottingham 2]

In the process of writing a routine to compute the Qn statistic of Croux and
Rousseeuw, I started from the Fortran code they published in their paper
(C&R, "Time-efficient algorithms for two highly robust estimators of scale")
and ran into unexpected trouble with one section. Here's a fairly literal
translation of the original, where x is an array of length n, and left and
right are also arrays of length n that contain integers:

w = zeros(1, n);
j = 1
for i = 1:n
  if(left(i) <= right(i))
    for jj = left(i):right(i)
      w(j) = x(i) - x(n+1-jj);
      j += 1;
    endfor
  endif
endfor

Before we get to this section, left and right are such that at most n items
will get copied into w.

Not surprisingly, this code is pretty slow. I see no way to eliminate the
outside loop on i; but getting rid of the inside loop on jj is
straightforward:

w = zeros(1, n);
j = 1
for i = 1:n
  if(left(i) <= right(i))
    w(j:j+right(i)-left(i)) = x(i) - x(n+1-[left(i):right(i)]);
    j = j + right(i)-left(i)+1;
  endif
endfor

Problem is, the second, vectorized, code takes twice as long as the first,
non-vectorized, code.

Anybody have an idea why? I'm stumped.

I have attached a script that contains these two snippets, some setup, and
tics and tocs, for anyone who wants to play with it.

Thanks,
Dave Cottingham

looptest.m <http://octave.1599824.n4.nabble.com/file/n4680192/looptest.m>  



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