%add the path to the toolbox (we can't save pathes on a CSL installation machine)
addpath(genpath('/afs/cs.wisc.edu/p/zhu/public/html/space2/TTP2/advanced_image_selection/bin/toolbox'))
%toolbox_compile



%read the file with feature vectors!
radiusOfGaussian = 25;

filename = 'histogram.txt';
X = [];
IDS = [];

fid = fopen(filename, 'r');


rows = fscanf(fid,'%d',[1 1]);
cols = fscanf(fid,'%d',[1 1]);

X(1:rows,1:cols) = 0;


for i = 1 : rows
 cur_id = fscanf(fid,'%d',[1 1]);
 IDS = [IDS; cur_id];
 for j = 1 : cols
  luv1 = fscanf(fid, '%f', [1 1]);
  X(i,j) = luv1;
 end
end

fclose(fid);


[IDX,M] = meanshift(X,radiusOfGaussian );

Indexes = [];
Indexes(1:size(IDX,1)) = 0;
for i = 1:size(IDX,1)
   Indexes(IDX(i)) = Indexes(IDX(i)) + 1;
end



[T,V] = max(Indexes);

sumCenters = [];
sumCenters(1:cols) = 0;
numCenters = 0;

for i = 1:size(IDX,1)
   if (IDX(i) == V)
     numCenters = numCenters + 1;
     sumCenters = sumCenters + X(i,:);     
   end;
end;


sumCenters;
numCenters;
CenterOfCluster = sumCenters / numCenters;



%T = find(r>sqrt(sum((data - repmat(Prev,1,n)).^2,1))); 

bestDistIdx = 1
MinDiff = norm(CenterOfCluster -X(1,:));
for i = 1:rows
      Diff = norm(CenterOfCluster - X(i,:));
      if(Diff < MinDiff)
         MinDiff = Diff;
         bestDistIdx = i;
      end 
end

%IDS(bestDistIdx);

fid = fopen('resultStep3.txt', 'wt');
fprintf(fid,'%d',IDS(bestDistIdx));
fclose(fid);