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1 function [base,seed] = som_dmatclusters(sM,linkage,neigh,ignore)
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2
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3 % SOM_DMATCLUSTERS Cluster map based on neighbor distance matrix.
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4 %
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5 % base = som_dmatclusters(sM,linkage,neigh,ignore)
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6 %
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7 % sM (struct) map or data struct
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8 % (matrix) data matrix, size n x dim
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9 % [linkage] (string) 'closest', 'single', 'average', 'complete',
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10 % 'centroid', 'ward', and 'neighf' (last for SOM only)
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11 % default is 'centroid'
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12 % [neigh] (string) 'kNN' or 'Nk' (which is valid for a SOM only)
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13 % for example '6NN' or 'N1'
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14 % default is '10NN' for a data set and 'N1' for SOM
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15 % (matrix) 0/1 matrix of size size n x n, 1=connection exists
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16 % [ignore] (vector) indeces of vectors to be ignored in the spreading
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17 % phase, empty vector by default
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18 %
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19 % base (vector) size n x 1, cluster indeces (1...c)
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20 % seed (vector) size c x 1, indeces of seed units for the clusters
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21 %
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22 % See also SOM_NEIGHBORS, KMEANS_CLUSTERS, SOM_DMATMINIMA.
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23
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24 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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25 %% input arguments
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26
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27 if nargin<2 | isempty(linkage), linkage = 'centroid'; end
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28
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29 if nargin<3 | isempty(neigh),
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30 if isstruct(sM) & strcmp(sM.type,'som_map'),
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31 neigh = 'N1';
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32 else
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33 neigh = '10NN';
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34 end
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35 end
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36
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37 if nargin<4, ignore = []; end
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38 n = size(sM.codebook,1);
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39
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40 % neighborhoods
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41 if ischar(neigh),
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42 Ne = som_neighbors(sM,neigh);
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43 else
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44 Ne = neigh;
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45 end
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46
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47 % find seed points
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48 seed = som_dmatminima(sM,[],Ne);
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49
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50 % make partition
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51 base = zeros(n,1);
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52 base(seed) = 1:length(seed);
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53 if any(ignore), base(ignore) = NaN; end
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54 base = som_clspread(sM,base,linkage,Ne,0);
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55
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56 % assign the ignored units, too
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57 base(isnan(base)) = 0;
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58 if any(base==0), base = som_clspread(sM,base,linkage,Ne,0); end
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59
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60 return;
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61
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