somtoolbox2/som_neighbors.m
4dbef185
 function Ne = som_neighbors(sM,neigh)
 
 % Ne = som_neighbors(sM,neigh)
 %
 % sM      (struct) map or data struct
 %         (matrix) data matrix, size n x dim
 % [neigh] (string) 'kNN' or 'Nk' (which is valid for a SOM only)
 %                  for example '6NN' or 'N1'
 %                  default is '10NN' for a data set and 'N1' for SOM
 %
 % Ne      (matrix) size n x n, a sparse matrix
 %                  indicating the neighbors of each sample by value 1 
 %                  (note: the unit itself also has value 0)
 
 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
 
 if isstruct(sM), 
   switch sM.type, 
    case 'som_map',  M = sM.codebook; 
    case 'som_data', M = sM.data; sM = []; 
   end
 else
   M = sM; 
   sM = []; 
 end
 
 n = size(M,1);
 
 if nargin<2, 
   if isempty(sM), neigh = '10NN'; else neigh = 'N1'; end
 end
 
 if strcmp(neigh(end-1:end),'NN'),
   k  = str2num(neigh(1:end-2));
   kmus = som_bmus(M,M,1:k+1);
   Ne = sparse(n,n);
   for i=1:n, Ne(i,kmus(i,:)) = 1; end
 else
   if ~isstruct(sM), error('Prototypes must be in a map struct.'); end      
   k  = str2num(neigh(2:end));
   N1 = som_unit_neighs(sM);    
   Ne = sparse(som_neighborhood(N1,k)<=k);
 end
 Ne([0:n-1]*n+[1:n]) = 0; % remove self from neighbors
 
 return;