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up vote 3 down vote favorite

I'm learning MATLAB (still trying to "think in vectors") and have the following piece of code:

stats = regionprops(bwconncomp(mask), 'all');

% find the object nearest our nucleus
smallest_dist = flintmax;
location = [cell_x, cell_y];
for j = 1:numel(stats)
    stat = stats(j);
    dist = pdist([location;[stat.Centroid]], 'euclidean');
    if dist < smallest_dist
        regions{channel} = stat; 
        smallest_dist = dist;
    end
end

All that is doing is searching through a struct array for the region which has a location (centroid) closest to my known cell's X/Y. I'm sure this is not canonical and that it could be improved.

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1 Answer 1

up vote 2 down vote accepted

I think this comes pretty close. The use of arrayfun() or other *fun()-Operations is very often better than for loops.

Your code was not working out of the box. Thus, I created code, which is directly executable:

function minimalExample()
    target.x = 10;
    target.y = 5;

    source(1) = struct('x', 1, 'y', 3);
    source(2) = struct('x', 5, 'y', 15);

    [~, minIndex] = min(arrayfun(@(x) (myDistance(x, target)), source));

    minSource = source(minIndex);
    disp(minSource);

    function d = myDistance(source, target)
        d = (source.x - target.x)^2 + (source.y - target.y)^2;
        d = sqrt(d);
    end
end
share|improve this answer
    
Thanks for the answer, I'll accept it. As it's been almost two weeks since posting I have learned mroe about MATLAB and changed this to use arrayfun myself (actually, I used arrayfun to implement minby, so it's now minby(stats, @(s)(pdist([p, [s.Centroid]], 'euclidean')));, which uses find(x,'first') internally). Again though, thanks. –  Ed S. May 26 '14 at 17:52
    
I just found this code review page. Great, you found *fun() already. There are millions of great applications for those and most of the time they are more readable than vectorized versions with a lot of reshape and repmat. –  Lukas May 26 '14 at 18:13

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