comparison toolboxes/MIRtoolbox1.3.2/somtoolbox/som_neighf.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function H = som_neighf(sMap,radius,neigh,ntype)
+
+%SOM_NEIGHF Return neighborhood function values.
+%
+% H = som_neighf(sMap,[radius],[neigh],[ntype]);
+% 
+%  Input and output arguments ([]'s are optional): 
+%   sMap     (struct) map or topology struct
+%   [radius] (scalar) neighborhood radius (by default, the last used value
+%                     in sMap.trainhist is used, or 1 if that is unavailable)
+%   [neigh]  (string) neighborhood function type (by default, ..., or 
+%                     'gaussian' if that is unavailable)
+%   [ntype]  (string) 'normal' (default), 'probability' or 'mirror'
+%
+%   H        (matrix) [munits x munits] neighborhood function values from 
+%                     each map unit to each other map unit
+%
+% For more help, try 'type som_batchtrain' or check out online documentation.
+% See also  SOM_MAKE, SOM_SEQTRAIN, SOM_TRAIN_STRUCT.
+
+% Copyright (c) 1997-2000 by the SOM toolbox programming team.
+% http://www.cis.hut.fi/projects/somtoolbox/
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% Check arguments 
+
+% defaults
+rdefault = 1; 
+ndefault = 'gaussian';
+tdefault = 'normal';
+
+% map 
+switch sMap.type, 
+ case 'som_map',   
+   sTopol = sMap.topol; 
+   sTrain = sMap.trainhist(end); 
+   if isempty(sTrain.radius_fin) | isnan(sTrain.radius_fin), 
+     rdefault = 1; 
+   else
+     rdefault = sTrain.radius_fin;
+   end
+   if ~isempty(sTrain.neigh) & ~isnan(sTrain.neigh), 
+     ndefault = sTrain.neigh;
+   end
+ case 'som_topol', sTopol = sMap; 
+end
+munits = prod(sTopol.msize); 
+
+% other parameters
+if nargin<2 | isempty(radius), radius = rdefault; end
+if nargin<3 | isempty(neigh), neigh = ndefault; end
+if nargin<4 | isempty(ntype), ntype = tdefault; end
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% initialize
+                                   
+% basic neighborhood 
+Ud = som_unit_dists(sTopol);
+Ud = Ud.^2;
+radius = radius.^2;
+if radius==0, radius = eps; end % zero neighborhood radius may cause div-by-zero error
+
+switch ntype, 
+case 'normal', 
+    H = neighf(neigh,Ud,radius); 
+case 'probability', 
+    H = neighf(neigh,Ud,radius); 
+    for i=1:munits, H(i,:) = H(i,:)/sum(H(i,:)); end
+case 'mirror', % only works for 2-dim grid!!!
+    H  = zeros(munits,munits);
+    Co = som_unit_coords(sTopol); 
+    for i=-1:1,
+        for j=-1:1,
+           Ud = gridmirrordist(Co,i,j);
+           H  = H + neighf(neigh,Ud,radius); 
+        end
+    end    
+end     
+
+return;
+
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%% subfunctions
+
+function H = neighf(neigh,Ud,radius)
+
+ switch neigh, 
+ case 'bubble',   H = (Ud<=radius); 
+ case 'gaussian', H = exp(-Ud/(2*radius)); 
+ case 'cutgauss', H = exp(-Ud/(2*radius)) .* (Ud<=radius);
+ case 'ep',       H = (1-Ud/radius) .* (Ud<=radius);
+ end  
+ return; 
+
+function Ud = gridmirrordist(Co,mirrorx,mirrory)
+
+ [munits,mdim] = size(Co); 
+ if mdim>2, error('Mirrored neighborhood only works for 2-dim map grids.'); end
+   
+ % width and height of the grid
+ dx = max(Co(:,1))-min(Co(:,1));
+ dy = max(Co(:,2))-min(Co(:,2));
+
+ % calculate distance from each location to each other location
+ Ud = zeros(munits,munits);
+ for i=1:munits, 
+   inds = [i:munits]; 
+   coi = Co(i,:); % take hexagonal shift into account
+   coi(1) = coi(1)*(1-2*(mirrorx~=0)) + 2*dx*(mirrorx==1); % +mirrorx * step
+   coi(2) = coi(2)*(1-2*(mirrory~=0)) + 2*dy*(mirrory==1); % +mirrory * step
+   Dco = (Co(inds,:) - coi(ones(munits-i+1,1),:))'; 
+   Ud(i,inds) = sqrt(sum(Dco.^2));
+   Ud(inds,i) = Ud(i,inds)'; 
+ end
+ return; 
+
+