diff --git a/src/MATLAB/clusterExamples/goLR.m b/src/MATLAB/clusterExamples/goLR.m
index 0e7d6bb75e8885f0db224c659c865d59fce873f5..80bfc5d2101e59381acca5df1de800b4be43e283 100644
--- a/src/MATLAB/clusterExamples/goLR.m
+++ b/src/MATLAB/clusterExamples/goLR.m
@@ -16,8 +16,8 @@ tblMeta = tblMeta(contains(tblMeta.scanType,'Optic'),:);
 
 p = ljsStartParallel(96);
 
-radii = {[0.5,8,8],[5,5,5],[0,0,0]}; % plate,blob
-% radii = {[0.5,8,8]}; % plate
+% radii = {[0.5,8,8],[5,5,5],[0,0,0]}; % plate,blob
+radii = {[0.5,8,8]}; % plate
 
 % radii = {[3]} % dark tubes
 imf = RSF.getImf(tblMeta,radii);
@@ -35,25 +35,46 @@ A = Cluster.Regularize(d);
 
 tblMeta.Y = Y;
 
+
 tS = tblMeta(strcmp(tblMeta.eye,'OD'),:);
 tD = tblMeta(strcmp(tblMeta.eye,'OS'),:);
 t1 = tS;
 t2 = tD;
 
-tO = tblMeta(contains(tblMeta.scanType,'Optic'),:);
-tM = tblMeta(contains(tblMeta.scanType,'Macular'),:);
-t3 = tO;
-t4 = tM;
-
+% tO = tblMeta(contains(tblMeta.scanType,'Optic'),:);
+% tM = tblMeta(contains(tblMeta.scanType,'Macular'),:);
+% t3 = tO;
+% t4 = tM;
+    idxOD = find(strcmp(tblMeta.eye,'OD'));
+    idxOS = find(strcmp(tblMeta.eye,'OS'));
     clf;hold on
-    plot3(t1.Y(:,1),t1.Y(:,2),t1.Y(:,3),'r*')
-    plot3(t2.Y(:,1),t2.Y(:,2),t2.Y(:,3),'og')
-    legend({'OS','OD'})
+    if size(Y,2) > 2
+        plot3(Y(idxOD,1),Y(idxOD,2),Y(idxOD,3),'r*')
+        plot3(Y(idxOS,1),Y(idxOS,2),Y(idxOS,3),'og')
+        zlabel('NCD3')
+    else
+        plot(Y(idxOD,1),Y(idxOD,2),'r*')
+        plot(Y(idxOS,1),Y(idxOS,2),'og')
+        
+    end
+    legend({'OD','OS'})
     xlabel('NCD1')
     ylabel('NCD2')
-    zlabel('NCD3')
+    
+% 
+% plot3(t3.Y(:,1),t3.Y(:,2),t3.Y(:,3),'mx')
+% plot3(t4.Y(:,1),t4.Y(:,2),t4.Y(:,3),'cs')
+% legend({'ONH','macula'})
+toc
 
-plot3(t3.Y(:,1),t3.Y(:,2),t3.Y(:,3),'mx')
-plot3(t4.Y(:,1),t4.Y(:,2),t4.Y(:,3),'cs')
-legend({'ONH','macula'})
-toc
\ No newline at end of file
+idxOD = find(strcmp(tblMeta.eye,'OS'));
+aOD = A(idxOD,idxOD);
+
+csf_mean = []; csf_std = [];
+for k = 1:10
+[idx,Y] = Cluster.SpectralCluster(A,k);
+csf = CSF.csf_spatial(Y,idx);
+csf_mean(k) = mean(csf);
+csf_std(k) = std(csf);
+end
+clf;errorbar(csf_mean,csf_std);xlim([0,10])