% computes a clustering solution total cost
function cost = compute_cost_pc(points, centroids)
    cost = 0;
    % TODO compute clustering solution cost
   [n m] = size(points);
   [a b] = size(centroids);
    poz = zeros(n,1);
    for i = 1:n
      k = 1;
      dist_min = norm(points(i,:) - centroids(1,:));
      for j = 2:a
        dist = norm(points(i,:) - centroids(j,:));
        if (dist < dist_min)
          dist_min = dist;
          k = j;
        endif
      endfor
      poz(i) = k;
    endfor
    val = 1;
    while (val <= a)
      sum = 0;
      for m = 1:n
        if (val == poz(m))
          sum = sum + norm(points(m,:) - centroids(val,:));
        endif
      endfor
      cost = cost + sum;
      val = val + 1;
    endwhile
end