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function Cd = som_cldist(D,clinds1,clinds2,cldist,q,mask)
% SOM_CLDIST Distances between two clusters.
%
% Cd = som_cldist(Md,c1,c2,'single')
% Cd = som_cldist(Md,c1,c2,'average')
% Cd = som_cldist(Md,c1,c2,'complete')
% Cd = som_cldist(Md,c1,c2,'neighf',H)
% Cd = som_cldist(Md,c1,[],...)
% Cd = som_cldist(D,c1,c2,'centroid',q,mask)
% Cd = som_cldist(D,c1,c2,'ward',q,mask)
% Cd = som_cldist(D,c1,[],...)
%
% Input and output arguments ([]'s are optional):
% D (matrix) size dlen x dim, the data set
% (struct) map or data struct
% Md (matrix) size dlen x dlen, mutual distance matrix, see SOM_MDIST
% c1 (cell array) size n1 x 1, indices of clusters from which
% the distances should be calculated, each cell
% contains indices of vectors that belong to that
% cluster (indices are between 1...dlen)
% c2 (cell array) size n2 x 1, same as c1 but have the clusters
% to which the distances should be calculated
% (empty) c1 is used in place of c2
% [q] (scalar) distance norm, default = 2
% [mask] (vector) size dim x 1, the weighting mask, a vector of ones
% by default
% H (matrix) size dlen x dlen, neighborhood function values
%
% Cd (matrix) size n1 x n2, distances between the clusters
%
% See also SOM_MDIST.
% Copyright (c) 2000 by Juha Vesanto
% Contributed to SOM Toolbox on XXX by Juha Vesanto
% http://www.cis.hut.fi/projects/somtoolbox/
% Version 2.0beta juuso 250800
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
[dlen dim] = size(D);
if nargin<5, q = 2; end
if nargin<6, mask = ones(dim,1); end
if ~iscell(clinds1), clinds1 = {clinds1}; end
if ~isempty(clinds2) & ~iscell(clinds2), clinds2 = {clinds2}; end
n1 = length(clinds1);
n2 = length(clinds2);
if n2>0, Cd = zeros(n1,n2); else Cd = zeros(n1); end
if n1==0, return; end
switch cldist,
% centroid distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'centroid',
C1 = zeros(n1,dim); for i=1:n1, C1(i,:) = mean(D(clinds1{i},:),1); end
C2 = zeros(n2,dim); for i=1:n2, C2(i,:) = mean(D(clinds2{i},:),1); end
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
diff = C1(i,:)-C1(j,:);
switch q,
case 1, Cd(i,j)=abs(diff)*mask;
case 2, Cd(i,j)=sqrt((diff.^2)*mask);
case Inf, Cd(i,j)=max(diag(mask)*abs(diff),[],2);
otherwise, Cd(i,j)=((abs(diff).^q)*mask).^(1/q);
end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
diff = C1(i,:)-C2(j,:);
switch q,
case 1, Cd(i,j)=abs(diff)*mask;
case 2, Cd(i,j)=sqrt((diff.^2)*mask);
case Inf, Cd(i,j)=max(diag(mask)*abs(diff),[],2);
otherwise, Cd(i,j)=((abs(diff).^q)*mask).^(1/q);
end
end
end
end
% ward distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'ward',
C1 = zeros(n1,dim); nn1 = zeros(n1,dim);
for i=1:n1, C1(i,:) = mean(D(clinds1{i},:),1); nn1(i) = length(clinds1{i}); end
C2 = zeros(n2,dim); nn2 = zeros(n2,dim);
for i=1:n2, C2(i,:) = mean(D(clinds2{i},:),1); nn2(i) = length(clinds2{i}); end
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
diff = C1(i,:) - C1(j,:);
f = 2*nn1(i)*nn1(j) / (nn1(i)+nn1(j));
switch q,
case 1, Cd(i,j)=f*abs(diff)*mask;
case 2, Cd(i,j)=f*sqrt((diff.^2)*mask);
case Inf, Cd(i,j)=f*max(diag(mask)*abs(diff),[],2);
otherwise, Cd(i,j)=f*((abs(diff).^q)*mask).^(1/q);
end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
diff = C1(i,:) - C2(j,:);
f = 2*nn1(i)*nn2(j) / (nn1(i)+nn2(j));
switch q,
case 1, Cd(i,j)=f*abs(diff)*mask;
case 2, Cd(i,j)=f*sqrt((diff.^2)*mask);
case Inf, Cd(i,j)=f*max(diag(mask)*abs(diff),[],2);
otherwise, Cd(i,j)=f*((abs(diff).^q)*mask).^(1/q);
end
end
end
end
% single linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'single',
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
vd = D(clinds1{i},clinds1{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = min(vd(fi)); else Cd(i,j) = Inf; end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
vd = D(clinds1{i},clinds2{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = min(vd(fi)); else Cd(i,j) = Inf; end
end
end
end
% average linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'average',
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
vd = D(clinds1{i},clinds1{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = mean(vd(fi)); else Cd(i,j) = Inf; end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
vd = D(clinds1{i},clinds2{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = mean(vd(fi)); else Cd(i,j) = Inf; end
end
end
end
% complete linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'complete',
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
vd = D(clinds1{i},clinds1{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = max(vd(fi)); else Cd(i,j) = Inf; end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
vd = D(clinds1{i},clinds2{j});
fi = isfinite(vd(:));
if any(fi), Cd(i,j) = max(vd(fi)); else Cd(i,j) = Inf; end
end
end
end
% neighborhood function linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
case 'neighf',
if n2==0,
for i=1:n1-1,
for j=i+1:n1,
vd = D(clinds1{i},clinds1{j});
fi = isfinite(vd(:));
if any(fi),
hd = q(clinds1{i},clinds1{j});
hd = hd(fi);
Cd(i,j) = sum(hd.*vd(fi))/sum(hd);
else Cd(i,j) = Inf;
end
end
Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
end
else
for i=1:n1,
for j=1:n2,
vd = D(clinds1{i},clinds2{j});
fi = isfinite(vd(:));
if any(fi),
hd = q(clinds1{i},clinds2{j});
hd = hd(fi);
Cd(i,j) = sum(hd.*vd(fi))/sum(hd);
else Cd(i,j) = Inf;
end
end
end
end
otherwise, error(['Unknown cluster distance metric: ' cldist]);
end
return;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%