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annotate toolboxes/MIRtoolbox1.3.2/somtoolbox/som_cldist.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 Cd = som_cldist(D,clinds1,clinds2,cldist,q,mask)
wolffd@0 2
wolffd@0 3 % SOM_CLDIST Distances between two clusters.
wolffd@0 4 %
wolffd@0 5 % Cd = som_cldist(Md,c1,c2,'single')
wolffd@0 6 % Cd = som_cldist(Md,c1,c2,'average')
wolffd@0 7 % Cd = som_cldist(Md,c1,c2,'complete')
wolffd@0 8 % Cd = som_cldist(Md,c1,c2,'neighf',H)
wolffd@0 9 % Cd = som_cldist(Md,c1,[],...)
wolffd@0 10 % Cd = som_cldist(D,c1,c2,'centroid',q,mask)
wolffd@0 11 % Cd = som_cldist(D,c1,c2,'ward',q,mask)
wolffd@0 12 % Cd = som_cldist(D,c1,[],...)
wolffd@0 13 %
wolffd@0 14 % Input and output arguments ([]'s are optional):
wolffd@0 15 % D (matrix) size dlen x dim, the data set
wolffd@0 16 % (struct) map or data struct
wolffd@0 17 % Md (matrix) size dlen x dlen, mutual distance matrix, see SOM_MDIST
wolffd@0 18 % c1 (cell array) size n1 x 1, indices of clusters from which
wolffd@0 19 % the distances should be calculated, each cell
wolffd@0 20 % contains indices of vectors that belong to that
wolffd@0 21 % cluster (indices are between 1...dlen)
wolffd@0 22 % c2 (cell array) size n2 x 1, same as c1 but have the clusters
wolffd@0 23 % to which the distances should be calculated
wolffd@0 24 % (empty) c1 is used in place of c2
wolffd@0 25 % [q] (scalar) distance norm, default = 2
wolffd@0 26 % [mask] (vector) size dim x 1, the weighting mask, a vector of ones
wolffd@0 27 % by default
wolffd@0 28 % H (matrix) size dlen x dlen, neighborhood function values
wolffd@0 29 %
wolffd@0 30 % Cd (matrix) size n1 x n2, distances between the clusters
wolffd@0 31 %
wolffd@0 32 % See also SOM_MDIST.
wolffd@0 33
wolffd@0 34 % Copyright (c) 2000 by Juha Vesanto
wolffd@0 35 % Contributed to SOM Toolbox on XXX by Juha Vesanto
wolffd@0 36 % http://www.cis.hut.fi/projects/somtoolbox/
wolffd@0 37
wolffd@0 38 % Version 2.0beta juuso 250800
wolffd@0 39
wolffd@0 40 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 41
wolffd@0 42 [dlen dim] = size(D);
wolffd@0 43 if nargin<5, q = 2; end
wolffd@0 44 if nargin<6, mask = ones(dim,1); end
wolffd@0 45 if ~iscell(clinds1), clinds1 = {clinds1}; end
wolffd@0 46 if ~isempty(clinds2) & ~iscell(clinds2), clinds2 = {clinds2}; end
wolffd@0 47
wolffd@0 48 n1 = length(clinds1);
wolffd@0 49 n2 = length(clinds2);
wolffd@0 50 if n2>0, Cd = zeros(n1,n2); else Cd = zeros(n1); end
wolffd@0 51 if n1==0, return; end
wolffd@0 52
wolffd@0 53 switch cldist,
wolffd@0 54
wolffd@0 55 % centroid distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 56 case 'centroid',
wolffd@0 57
wolffd@0 58 C1 = zeros(n1,dim); for i=1:n1, C1(i,:) = mean(D(clinds1{i},:),1); end
wolffd@0 59 C2 = zeros(n2,dim); for i=1:n2, C2(i,:) = mean(D(clinds2{i},:),1); end
wolffd@0 60 if n2==0,
wolffd@0 61 for i=1:n1-1,
wolffd@0 62 for j=i+1:n1,
wolffd@0 63 diff = C1(i,:)-C1(j,:);
wolffd@0 64 switch q,
wolffd@0 65 case 1, Cd(i,j)=abs(diff)*mask;
wolffd@0 66 case 2, Cd(i,j)=sqrt((diff.^2)*mask);
wolffd@0 67 case Inf, Cd(i,j)=max(diag(mask)*abs(diff),[],2);
wolffd@0 68 otherwise, Cd(i,j)=((abs(diff).^q)*mask).^(1/q);
wolffd@0 69 end
wolffd@0 70 end
wolffd@0 71 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 72 end
wolffd@0 73 else
wolffd@0 74 for i=1:n1,
wolffd@0 75 for j=1:n2,
wolffd@0 76 diff = C1(i,:)-C2(j,:);
wolffd@0 77 switch q,
wolffd@0 78 case 1, Cd(i,j)=abs(diff)*mask;
wolffd@0 79 case 2, Cd(i,j)=sqrt((diff.^2)*mask);
wolffd@0 80 case Inf, Cd(i,j)=max(diag(mask)*abs(diff),[],2);
wolffd@0 81 otherwise, Cd(i,j)=((abs(diff).^q)*mask).^(1/q);
wolffd@0 82 end
wolffd@0 83 end
wolffd@0 84 end
wolffd@0 85 end
wolffd@0 86
wolffd@0 87 % ward distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 88 case 'ward',
wolffd@0 89
wolffd@0 90 C1 = zeros(n1,dim); nn1 = zeros(n1,dim);
wolffd@0 91 for i=1:n1, C1(i,:) = mean(D(clinds1{i},:),1); nn1(i) = length(clinds1{i}); end
wolffd@0 92 C2 = zeros(n2,dim); nn2 = zeros(n2,dim);
wolffd@0 93 for i=1:n2, C2(i,:) = mean(D(clinds2{i},:),1); nn2(i) = length(clinds2{i}); end
wolffd@0 94 if n2==0,
wolffd@0 95 for i=1:n1-1,
wolffd@0 96 for j=i+1:n1,
wolffd@0 97 diff = C1(i,:) - C1(j,:);
wolffd@0 98 f = 2*nn1(i)*nn1(j) / (nn1(i)+nn1(j));
wolffd@0 99 switch q,
wolffd@0 100 case 1, Cd(i,j)=f*abs(diff)*mask;
wolffd@0 101 case 2, Cd(i,j)=f*sqrt((diff.^2)*mask);
wolffd@0 102 case Inf, Cd(i,j)=f*max(diag(mask)*abs(diff),[],2);
wolffd@0 103 otherwise, Cd(i,j)=f*((abs(diff).^q)*mask).^(1/q);
wolffd@0 104 end
wolffd@0 105 end
wolffd@0 106 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 107 end
wolffd@0 108 else
wolffd@0 109 for i=1:n1,
wolffd@0 110 for j=1:n2,
wolffd@0 111 diff = C1(i,:) - C2(j,:);
wolffd@0 112 f = 2*nn1(i)*nn2(j) / (nn1(i)+nn2(j));
wolffd@0 113 switch q,
wolffd@0 114 case 1, Cd(i,j)=f*abs(diff)*mask;
wolffd@0 115 case 2, Cd(i,j)=f*sqrt((diff.^2)*mask);
wolffd@0 116 case Inf, Cd(i,j)=f*max(diag(mask)*abs(diff),[],2);
wolffd@0 117 otherwise, Cd(i,j)=f*((abs(diff).^q)*mask).^(1/q);
wolffd@0 118 end
wolffd@0 119 end
wolffd@0 120 end
wolffd@0 121 end
wolffd@0 122
wolffd@0 123 % single linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 124 case 'single',
wolffd@0 125
wolffd@0 126 if n2==0,
wolffd@0 127 for i=1:n1-1,
wolffd@0 128 for j=i+1:n1,
wolffd@0 129 vd = D(clinds1{i},clinds1{j});
wolffd@0 130 fi = isfinite(vd(:));
wolffd@0 131 if any(fi), Cd(i,j) = min(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 132 end
wolffd@0 133 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 134 end
wolffd@0 135 else
wolffd@0 136 for i=1:n1,
wolffd@0 137 for j=1:n2,
wolffd@0 138 vd = D(clinds1{i},clinds2{j});
wolffd@0 139 fi = isfinite(vd(:));
wolffd@0 140 if any(fi), Cd(i,j) = min(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 141 end
wolffd@0 142 end
wolffd@0 143 end
wolffd@0 144
wolffd@0 145 % average linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 146 case 'average',
wolffd@0 147
wolffd@0 148 if n2==0,
wolffd@0 149 for i=1:n1-1,
wolffd@0 150 for j=i+1:n1,
wolffd@0 151 vd = D(clinds1{i},clinds1{j});
wolffd@0 152 fi = isfinite(vd(:));
wolffd@0 153 if any(fi), Cd(i,j) = mean(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 154 end
wolffd@0 155 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 156 end
wolffd@0 157 else
wolffd@0 158 for i=1:n1,
wolffd@0 159 for j=1:n2,
wolffd@0 160 vd = D(clinds1{i},clinds2{j});
wolffd@0 161 fi = isfinite(vd(:));
wolffd@0 162 if any(fi), Cd(i,j) = mean(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 163 end
wolffd@0 164 end
wolffd@0 165 end
wolffd@0 166
wolffd@0 167 % complete linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 168 case 'complete',
wolffd@0 169
wolffd@0 170 if n2==0,
wolffd@0 171 for i=1:n1-1,
wolffd@0 172 for j=i+1:n1,
wolffd@0 173 vd = D(clinds1{i},clinds1{j});
wolffd@0 174 fi = isfinite(vd(:));
wolffd@0 175 if any(fi), Cd(i,j) = max(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 176 end
wolffd@0 177 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 178 end
wolffd@0 179 else
wolffd@0 180 for i=1:n1,
wolffd@0 181 for j=1:n2,
wolffd@0 182 vd = D(clinds1{i},clinds2{j});
wolffd@0 183 fi = isfinite(vd(:));
wolffd@0 184 if any(fi), Cd(i,j) = max(vd(fi)); else Cd(i,j) = Inf; end
wolffd@0 185 end
wolffd@0 186 end
wolffd@0 187 end
wolffd@0 188
wolffd@0 189 % neighborhood function linkage distance %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 190 case 'neighf',
wolffd@0 191
wolffd@0 192 if n2==0,
wolffd@0 193 for i=1:n1-1,
wolffd@0 194 for j=i+1:n1,
wolffd@0 195 vd = D(clinds1{i},clinds1{j});
wolffd@0 196 fi = isfinite(vd(:));
wolffd@0 197 if any(fi),
wolffd@0 198 hd = q(clinds1{i},clinds1{j});
wolffd@0 199 hd = hd(fi);
wolffd@0 200 Cd(i,j) = sum(hd.*vd(fi))/sum(hd);
wolffd@0 201 else Cd(i,j) = Inf;
wolffd@0 202 end
wolffd@0 203 end
wolffd@0 204 Cd([(i+1):n1],i) = Cd(i,[(i+1):n1])';
wolffd@0 205 end
wolffd@0 206 else
wolffd@0 207 for i=1:n1,
wolffd@0 208 for j=1:n2,
wolffd@0 209 vd = D(clinds1{i},clinds2{j});
wolffd@0 210 fi = isfinite(vd(:));
wolffd@0 211 if any(fi),
wolffd@0 212 hd = q(clinds1{i},clinds2{j});
wolffd@0 213 hd = hd(fi);
wolffd@0 214 Cd(i,j) = sum(hd.*vd(fi))/sum(hd);
wolffd@0 215 else Cd(i,j) = Inf;
wolffd@0 216 end
wolffd@0 217 end
wolffd@0 218 end
wolffd@0 219 end
wolffd@0 220
wolffd@0 221 otherwise, error(['Unknown cluster distance metric: ' cldist]);
wolffd@0 222 end
wolffd@0 223
wolffd@0 224 return;
wolffd@0 225
wolffd@0 226 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0 227