function sC = som_clstruct(Z,varargin)%SOM_CLSTRUCT Create a clustering struct or set its field values.%%  sC = som_clstruct(Z, [argID, value, ...]) %%    Z  = linkage(pdist(sM.codebook));%    sC = som_clstruct(Z); %    sC = som_clstruct(sC,'coord',som_vis_coords(lattice,msize));%    sC = som_clstruct(sC,'color',som_colorcode(sM));%    sC = som_clstruct(sC,'base',sC.base(som_bmus(sM,sD)));%%  Input and output arguments ([]'s are optional): %   Z         (matrix) size clen-1 x 3, where clen is the number of %                      base clusters. This is a clustering matrix %                      similar to that produced by LINKAGE in %                      Statistical Toolbox. See SOM_LINKAGE.%             (struct) clustering struct (as produced by this function)%   [argID,   (string) See below. Each pair is the fieldname and %    value]   (varies) the value to be given to that field.%%   sC        (struct) clustering struct% %   The clustering struct is based on the assumption that there %   is a base partitioning of the SOM (or data) which is saved in %   the .base field of the struct. Then a hierarchical clustering%   is applied to this base partitioning. The results are saved to %   .tree field of the struct. Each cluster (base and combined)%   has also three properties: height, coordinate and color, which %   are used in the visualizations. The fields of the struct are:%     .type   (string) 'som_clustering'%     .name   (string) Identifier for the clustering.%     .tree   (matrix) Size clen-1 x 3, as argument Z above. %     .base   (vector) Size dlen x 1, the basic groups of data %                      forming the base clusters, e.g. as a result %                      of partitive clustering. Allowed values are %                       1:clen indicating the base cluster%                              to which the data belongs to. %                       NaN    indicating that the data has%                              been ignored in the clustering%                      By default [1:clen]. %     .height (vector) Size 2*clen-1 x 1, (clustering) height for each %                      cluster. By default 0 for each base cluster and%                      .tree(:,3) for the others.%     .coord  (matrix) Size 2*clen-1 x *, coordinate for each cluster, %                      By default the coordinates are set so that %                      the base clusters are ordered on a line, and the%                      position of each combined cluster is average of %                      the base clusters that constitute it.%     .color  (matrix) Size 2*clen-1 x 3, color for each cluster. %                      By default the colors are set so that the %                      base clusters are ordered on a line, like above,%                      and then colors are assigned from the 'hsv' %                      colormap to the base clusters. The color%                      of each combined cluster is average as above.%% Height, coord and color can also be specified in alternate forms:%   'height' (vector) size 2*clen-1 x 1, if given explicitly%                     size clen-1 x 1, specified heights of the %                          combined clusters (the base cluster heights%                          are all = 0)%                     size 0 x 0, default value is used%   'coord'  (matrix) size 2*clen-1 x *, if given explicitly%                     size clen x *, to give coordinates for base %                          clusters; the coordinate of combined clusters%                          are averaged from these%                     size dlen x *, to give coordinates of the %                          original data: the cluster coordinates are%                          averaged from these based on base clusters%                     size 0 x 0, default value is used%   'color'  (matrix) as 'coord'%% See also  SOM_CLPLOT, SOM_CLVALIDITY, SOM_CLGET, SOM_CLLINKAGE.% Copyright (c) 2000 by the SOM toolbox programming team.% Contributed to SOM Toolbox on XXX by Juha Vesanto% http://www.cis.hut.fi/projects/somtoolbox/% Version 2.0beta juuso 180800%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%if isstruct(Z),   base = Z.base;   color = Z.color;   coord = Z.coord;   height = Z.height;   name = Z.name;   Z = Z.tree; else  base  = [];   color = [];   coord = [];   height = [];   name = ''; end    clen  = size(Z,1)+1; i=1; while i<=length(varargin),   argok = 1;   if ischar(varargin{i}),     switch varargin{i},      case 'tree',   i=i+1; Z = varargin{i}; clen = size(Z,1)+1;     case 'base',   i=i+1; base = varargin{i};      case 'color',  i=i+1; color = varargin{i};      case 'coord',  i=i+1; coord = varargin{i};      case 'height', i=i+1; height = varargin{i};      case 'name',   i=i+1; name = varargin{i};      otherwise argok=0;     end  else argok = 0;   end  if ~argok, disp(['(som_clstruct) Ignoring invalid argument #' num2str(i+1)]); end  i = i+1; endif isempty(base),   dlen = clen;   base = 1:dlen; else  dlen = length(base);   if any(base)>clen | any(base)<1, error('Incorrect base partition vector.'); endend%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% analysis of hierarchy% order of base clustersorder = 2*clen-1; nonleaves = 1; while any(nonleaves),   j = nonleaves(1);   ch = Z(order(j)-clen,1:2);  if j==1, oleft = []; else oleft = order(1:(j-1)); end  if j==length(order), oright = []; else oright = order((j+1):length(order)); end  order = [oleft, ch, oright];  nonleaves = find(order>clen); end% base cluster indeces for each non-base clusterbasecl = cell(clen-1,1); for i=1:clen-1,   c1 = Z(i,1); if c1>clen, c1 = basecl{c1-clen}; end  c2 = Z(i,2); if c2>clen, c2 = basecl{c2-clen}; end  basecl{i} = [c1 c2];   end%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% set coordinates, color and height and make the struct% coordinatesif size(coord,1)==2*clen-1, % this is ok alreadyelse  if size(coord,1)==0, % the default        [dummy,coord] = sort(order);     coord = coord';   elseif size(coord,1)==dlen & dlen>clen, % coordinates given for original data    codata = coord;     coord = zeros(clen,size(coord,2));     for i=1:clen, coord(i,:) = mean(codata(find(base==i),:),1); end    end  if size(coord,1)==clen, % average from base clusters    coord = [coord; zeros(clen-1,size(coord,2))];     for i=1:clen-1, coord(i+clen,:) = mean(coord(basecl{i},:),1); end  else    error('Incorrect coordinate matrix.');   endend% colorif size(color,1)==2*clen-1, % this is ok alreadyelse  if size(color,1)==0, % the default    color(order,:) = hsv(length(order));   elseif size(color,1)==dlen & dlen>clen, % colors given for original data    codata = color;     color = zeros(clen,3);     for i=1:clen, color(i,:) = mean(codata(find(base==i),:),1); end    end  if size(color,1)==clen, % average from base clusters    color = [color; zeros(clen-1,3)];     for i=1:clen-1, color(i+clen,:) = mean(color(basecl{i},:),1); end  else    error('Incorrect color matrix.');   endend% height if isempty(height),   height = [zeros(clen,1); Z(:,3)]; elseif length(height)==clen-1,   if size(height,2)==clen-1, height = height'; end  height = [zeros(clen,1); height]; elseif length(height)~=2*clen-1,   error('Incorrect height vector.'); end% make the structsC = struct('type','som_clustering',...	    'name',name,'base',base,'tree',Z,...	    'color',color,'coord',coord,'height',height); return; %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%