csf_spatial

src/MATLAB/+CSF/csf_spatial.m

-function [csf_mean,csf_std] = csf_spatial(Y,idxTrue)
+function csf = csf_spatial(Y,idxTrue)
 
 K = length(unique(idxTrue));
-mcdf = [];
-scdf = [];
+
+if size(Y,2)~=K
+    fprintf(2,'csf_spatial Y input dimensionality=%d must match K=%d',size(Y,2),K);
+    csf_mean = nan;
+    csf_std = nan;
+    return;
+end
+
+csf = [];
 for ik=1:K
     idxk=find(idxTrue==ik);
     yk=Y(idxk,:);
-    [dk,sk] = CSF.od2d(yk);
-    mcdf(ik)=dk;
-    scdf(ik)=sk;
+    dx = CSF.od_rkhs(yk);
+    csf(idxk) = dx;
 end
-
-csf_mean = mean(mcdf);
-csf_std = std(mcdf);
 4;
\ No newline at end of file

src/MATLAB/+CSF/od2d.m

-function [dk,sk] = od2d(xk)
-
-cx = repmat(mean(xk),size(xk,1),1);
-dd = vecnorm(cx - xk, 2, 2);
-% dd = sqrt( (cx(:,1)-xk(:,1)).^2 + (cx(:,2)-xk(:,2)).^2 );
-idx=find( abs(dd-mean(dd))<std(dd));
-dd = dd(idx);
-dk = mean(dd) + log2(length(idx))/length(idx);
-sk = std(dd);
-4;
-
-% KX = NCD.Press(xk,[]);
-% dx = pdist2(xk,xk);
-% 
-% dk = KX - kx + log2(length(xk));
-
-% dx = pdist(xk);
-% dk = max(dx) - min(dx);
-% sk = norm(std(xk));
-
-% xx = (xk - mean(xk)) ./ std(xk);
-% [h,p] = kstest(xx);
-% dk = 1-p;
\ No newline at end of file

src/MATLAB/+CSF/od_rkhs.m

+% computes optimality deficiency for each xk in the rkhs
+% od = Z(x) - z(x) + log|x|
+function dx = od_rkhs(xk)
+
+cx = repmat(mean(xk),size(xk,1),1);
+dx = vecnorm(cx - xk, 2, 2) + log2(size(xk,1));
+4;