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annotate toolboxes/MIRtoolbox1.3.2/somtoolbox/som_kmeanscolor.m @ 0:e9a9cd732c1e tip

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first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
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wolffd@0 1 function [color,best,kmeans]=som_kmeanscolor(sM,C,initRGB,contrast)
wolffd@0 2
wolffd@0 3 % SOM_KMEANSCOLOR Map unit color code according to K-means clustering
wolffd@0 4 %
wolffd@0 5 % [color, best, kmeans] = som_kmeanscolor(sM, C, [initRGB],[contrast])
wolffd@0 6 %
wolffd@0 7 % color = som_kmeanscolor(sM,15,som_colorcode(sM,'rgb1'),'enhance');
wolffd@0 8 % [color,best] = som_kmeanscolor(sM,15,[],'normal');
wolffd@0 9 %
wolffd@0 10 % Input and output arguments ([]'s are optional):
wolffd@0 11 % sM (struct) map struct
wolffd@0 12 % C (scalar) maximum number of clusters
wolffd@0 13 % initRGB (string, matrix) color code string accepted by SOM_COLORCODE
wolffd@0 14 % or an Mx3 matrix of RGB triples, where M is the number
wolffd@0 15 % of map units. Default: SOM_COLORCODEs default
wolffd@0 16 % contrast (string) 'flat', 'enhanced' color contrast mode, default:
wolffd@0 17 % 'enhanced'
wolffd@0 18 %
wolffd@0 19 % color (matrix) MxCx3 of RGB triples
wolffd@0 20 % best (scalar) index for "best" clustering according to
wolffd@0 21 % Davies-Boulding index; color(:,:,best) includes the
wolffd@0 22 % corresponding color code.
wolffd@0 23 % kmeans (cell) output of KMEANS_CLUSTERS in a cell array.
wolffd@0 24 %
wolffd@0 25 % The function gives a set of color codings according to K-means
wolffd@0 26 % clustering. For clustering, it uses function KMEANS_CLUSTERS for map units,
wolffd@0 27 % and it calculates color codings for 1,2,...,C clusters.
wolffd@0 28 % The idea of coloring is that the color of a cluster is the mean of the
wolffd@0 29 % original colors (RGB values) of the map units belonging to that cluster,
wolffd@0 30 % see SOM_CLUSTERCOLOR. The original colors are defined by SOM_COLORCODE
wolffd@0 31 % by default. Input 'contrast' simply specifies whether or not
wolffd@0 32 % to linearly redistribute R,G, and B values so that minimum is 0 and
wolffd@0 33 % maximum 1 ('enahanced') or to use directly the output of
wolffd@0 34 % SOM_CLUSTERCOLOR ('flat'). KMEANS_CLUSTERS uses certain heuristics to
wolffd@0 35 % select the best of 5 trials for each number of clusters. Evaluating the
wolffd@0 36 % clustering multiple times may take some time.
wolffd@0 37 %
wolffd@0 38 % EXAMPLE
wolffd@0 39 %
wolffd@0 40 % load iris; % or any other map struct sM
wolffd@0 41 % [color,b]=som_kmeanscolor(sM,10);
wolffd@0 42 % som_show(sM,'color',color,'color',{color(:,:,b),'"Best clustering"');
wolffd@0 43 %
wolffd@0 44 % See also SOM_SHOW, SOM_COLORCODE, SOM_CLUSTERCOLOR, KMEANS_CLUSTERS
wolffd@0 45
wolffd@0 46 % Contributed to SOM Toolbox 2.0, April 1st, 2000 by Johan Himberg
wolffd@0 47 % Copyright (c) by Johan Himberg
wolffd@0 48 % http://www.cis.hut.fi/projects/somtoolbox/
wolffd@0 49
wolffd@0 50 % corrected help text 11032005 johan
wolffd@0 51
wolffd@0 52 %%% Check number of inputs
wolffd@0 53
wolffd@0 54 error(nargchk(2, 4, nargin)); % check no. of input args
wolffd@0 55
wolffd@0 56 %%% Check input args & set defaults
wolffd@0 57
wolffd@0 58 if isstruct(sM) & isfield(sM,'type') & strcmp(sM.type,'som_map'),
wolffd@0 59 [tmp,lattice,msize]=vis_planeGetArgs(sM);
wolffd@0 60 munits=prod(msize);
wolffd@0 61 if length(msize)>2
wolffd@0 62 error('Does not work with 3D maps.')
wolffd@0 63 end
wolffd@0 64 else
wolffd@0 65 error('Map struct requires for first input argument!');
wolffd@0 66 end
wolffd@0 67
wolffd@0 68 if ~vis_valuetype(C,{'1x1'}),
wolffd@0 69 error('Scalar value expect for maximum number of clusters.');
wolffd@0 70 end
wolffd@0 71
wolffd@0 72 % check initial color coding
wolffd@0 73 if nargin<3 | isempty(initRGB)
wolffd@0 74 initRGB=som_colorcode(sM);
wolffd@0 75 end
wolffd@0 76
wolffd@0 77 % check contrast checking
wolffd@0 78 if nargin<4 | isempty(contrast),
wolffd@0 79 contrast='enhanced';
wolffd@0 80 end
wolffd@0 81
wolffd@0 82 if ~ischar(contrast),
wolffd@0 83 error('String input expected for input arg. ''contrast''.');
wolffd@0 84 else
wolffd@0 85 switch lower(contrast)
wolffd@0 86 case {'flat','enhanced'}
wolffd@0 87 ;
wolffd@0 88 otherwise
wolffd@0 89 error(['''flat'' or ''enhanced'' expected for '...
wolffd@0 90 'input argument ''contrast''.']);
wolffd@0 91 end
wolffd@0 92 end
wolffd@0 93
wolffd@0 94 if ischar(initRGB),
wolffd@0 95 try
wolffd@0 96 initRGB=som_colorcode(sM,initRGB);
wolffd@0 97 catch
wolffd@0 98 error(['Color code ' initRGB ...
wolffd@0 99 'was not recognized by SOM_COLORCODE.']);
wolffd@0 100 end
wolffd@0 101 elseif vis_valuetype(initRGB,{'nx3rgb',[munits 3]},'all'),
wolffd@0 102 ;
wolffd@0 103 else
wolffd@0 104 error(['The initial color code must be a string '...
wolffd@0 105 'or an Mx3 matrix of RGB triples.']);
wolffd@0 106 end
wolffd@0 107
wolffd@0 108 %%% Action %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 109
wolffd@0 110 disp('Wait...');
wolffd@0 111 [c,p,err,ind]=kmeans_clusters(sM,C,5,0); % use 5 trials, verbose off
wolffd@0 112
wolffd@0 113 % Store outputs to kmeans
wolffd@0 114 kmeans{1}=c;
wolffd@0 115 kmeans{2}=p;
wolffd@0 116 kmeans{3}=err;
wolffd@0 117 kmeans{4}=ind;
wolffd@0 118
wolffd@0 119 %%% Build output
wolffd@0 120 color=som_clustercolor(sM,cat(2,p{:}),initRGB);
wolffd@0 121 [tmp,best]=min(ind);
wolffd@0 122
wolffd@0 123 switch contrast
wolffd@0 124 case 'flat'
wolffd@0 125 ;
wolffd@0 126 case 'enhanced'
wolffd@0 127 warning off;
wolffd@0 128 ncolor=maxnorm(color);
wolffd@0 129 ncolor(~isfinite(ncolor))=color(~isfinite(ncolor));
wolffd@0 130 color=ncolor;
wolffd@0 131 warning on;
wolffd@0 132 end
wolffd@0 133
wolffd@0 134 %%% Subfunctions %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 135 function X=maxnorm(x)
wolffd@0 136 % normalize columns of x between [0,1]
wolffd@0 137
wolffd@0 138 x=x-repmat(min(x),[size(x,1) 1 1]);
wolffd@0 139 X=x./repmat(max(x),[size(x,1) 1 1]);