function [color,best,kmeans]=som_kmeanscolor(sM,C,initRGB,contrast)% SOM_KMEANSCOLOR Map unit color code according to K-means clustering%% [color, best, kmeans] = som_kmeanscolor(sM, C, [initRGB],[contrast])%%  color        = som_kmeanscolor(sM,15,som_colorcode(sM,'rgb1'),'enhance');%  [color,best] = som_kmeanscolor(sM,15,[],'normal');%  %  Input and output arguments ([]'s are optional):%   sM       (struct) map struct%   C        (scalar) maximum number of clusters%   initRGB  (string, matrix) color code string accepted by SOM_COLORCODE%                     or an Mx3 matrix of RGB triples, where M is the number%                     of map units. Default: SOM_COLORCODEs default%   contrast (string) 'flat', 'enhanced' color contrast mode, default:%                     'enhanced'%%   color    (matrix) MxCx3 of RGB triples%   best     (scalar) index for "best" clustering according to %                     Davies-Boulding index; color(:,:,best) includes the %                     corresponding color code.%   kmeans   (cell)   output of KMEANS_CLUSTERS in a cell array.% % The function gives a set of color codings according to K-means % clustering. For clustering, it uses function KMEANS_CLUSTERS for map units, % and it calculates color codings for 1,2,...,C clusters. % The idea of coloring is that the color of a cluster is the mean of the % original colors (RGB values) of the map units belonging to that cluster, % see SOM_CLUSTERCOLOR. The original colors are defined by  SOM_COLORCODE% by default. Input 'contrast' simply specifies whether or not % to linearly redistribute R,G, and B values so that minimum is 0 and % maximum 1 ('enahanced')  or to use directly the output of % SOM_CLUSTERCOLOR ('flat'). KMEANS_CLUSTERS uses certain heuristics to % select the best of 5 trials for each  number of clusters. Evaluating the % clustering multiple times may take some time. %% EXAMPLE% %  load iris; % or any other map struct sM %  [color,b]=som_kmeanscolor(sM,10);%  som_show(sM,'color',color,'color',{color(:,:,b),'"Best clustering"');% % See also SOM_SHOW, SOM_COLORCODE, SOM_CLUSTERCOLOR, KMEANS_CLUSTERS% Contributed to SOM Toolbox 2.0, April 1st, 2000 by Johan Himberg% Copyright (c) by Johan Himberg% http://www.cis.hut.fi/projects/somtoolbox/% corrected help text 11032005 johan%%% Check number of inputserror(nargchk(2, 4, nargin));  % check no. of input args%%% Check input args & set defaultsif isstruct(sM) & isfield(sM,'type') & strcmp(sM.type,'som_map'),   [tmp,lattice,msize]=vis_planeGetArgs(sM);   munits=prod(msize);   if length(msize)>2       error('Does not work with 3D maps.')   endelse   error('Map struct requires for first input argument!');endif ~vis_valuetype(C,{'1x1'}),   error('Scalar value expect for maximum number of clusters.');end% check initial color codingif nargin<3 | isempty(initRGB)   initRGB=som_colorcode(sM);end% check contrast checkingif nargin<4 | isempty(contrast),   contrast='enhanced';endif ~ischar(contrast),   error('String input expected for input arg. ''contrast''.');else   switch lower(contrast)   case {'flat','enhanced'}      ;   otherwise       error(['''flat'' or ''enhanced'' expected for '...            'input argument ''contrast''.']);   endendif ischar(initRGB),   try       initRGB=som_colorcode(sM,initRGB);   catch      error(['Color code ' initRGB ...            'was not recognized by SOM_COLORCODE.']);   endelseif vis_valuetype(initRGB,{'nx3rgb',[munits 3]},'all'),   ;else   error(['The initial color code must be a string '...         'or an Mx3 matrix of RGB triples.']);end%%% Action %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%disp('Wait...');[c,p,err,ind]=kmeans_clusters(sM,C,5,0); % use 5 trials, verbose off% Store outputs to kmeanskmeans{1}=c; kmeans{2}=p; kmeans{3}=err; kmeans{4}=ind;%%% Build outputcolor=som_clustercolor(sM,cat(2,p{:}),initRGB);[tmp,best]=min(ind);switch contrastcase 'flat'   ;case 'enhanced'   warning off;   ncolor=maxnorm(color);   ncolor(~isfinite(ncolor))=color(~isfinite(ncolor));   color=ncolor;   warning on;end%%% Subfunctions %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%function X=maxnorm(x)% normalize columns of x between [0,1]x=x-repmat(min(x),[size(x,1) 1 1]);X=x./repmat(max(x),[size(x,1) 1 1]);