- refactored

common/clusters/eudist.m

@@ -0,0 +1,31 @@
+% clusters.m
+% function cb = clusters(input,ref,maxIt)
+% clusters(randn(2,400)/sqrt(12),randn(2,1)/sqrt(12));
+% 17.01.2003, Jens Ahrensfeld
+
+function [indices, output] = eudist(input,ref)
+
+[nDim, nData] = size(input);
+[nDimr, nClasses] = size(ref);
+
+if (nDim ~= nDimr),
+    error('Dimensions must match!');
+end;
+
+cnt = zeros(nClasses,1);
+for j=1:nClasses,
+   indices{j} = [];
+end;
+for i=1:nData,
+   for j=1:nClasses,
+     d(j) = sqrt(sum((input(:,i)-ref(:,j)).^2));			% Calc distances between references and input
+   end;  
+   [value nearestClass] = min(d);
+   cnt(nearestClass) = cnt(nearestClass) + 1;
+   indices{nearestClass} = [ indices{nearestClass} i ];
+end;   
+
+% Separate data
+for j=1:nClasses,
+	output{j} = input(:,indices{j});
+end;