wolffd@0: function sS = som_vs1to2(sS)
wolffd@0: 
wolffd@0: %SOM_VS1TO2 Convert version 1 structure to version 2.
wolffd@0: %
wolffd@0: % sSnew = som_vs1to2(sSold)
wolffd@0: %
wolffd@0: %  sMnew = som_vs1to2(sMold);  
wolffd@0: %  sDnew = som_vs1to2(sDold);  
wolffd@0: %
wolffd@0: %  Input and output arguments: 
wolffd@0: %   sSold   (struct) a SOM Toolbox version 1 structure
wolffd@0: %   sSnew   (struct) a SOM Toolbox version 2 structure
wolffd@0: %
wolffd@0: % For more help, try 'type som_vs1to2' or check out online documentation.
wolffd@0: % See also  SOM_SET, SOM_VS2TO1.
wolffd@0: 
wolffd@0: %%%%%%%%%%%%% DETAILED DESCRIPTION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0: %
wolffd@0: % som_vs1to2
wolffd@0: %
wolffd@0: % PURPOSE
wolffd@0: %
wolffd@0: % Transforms SOM Toolbox 1 version structs from to 2 version structs.
wolffd@0: %
wolffd@0: % SYNTAX
wolffd@0: %
wolffd@0: %  sS2 = som_vs1to2(sS1)
wolffd@0: %
wolffd@0: % DESCRIPTION
wolffd@0: %
wolffd@0: % This function is offered to allow the change of old map and data structs
wolffd@0: % to new ones. There are quite a lot of changes between the versions,
wolffd@0: % especially in the map struct, and this function makes it easy to update 
wolffd@0: % the structs.
wolffd@0: %
wolffd@0: % WARNING!
wolffd@0: %
wolffd@0: % 'som_unit_norm' normalization type is not supported by version 2,
wolffd@0: % so this type of normalization will be lost.
wolffd@0: %
wolffd@0: % REQUIRED INPUT ARGUMENTS
wolffd@0: %
wolffd@0: %  sS1       (struct) any SOM Toolbox version 1 struct (map, data, 
wolffd@0: %                     training or normalization struct)
wolffd@0: %
wolffd@0: % OUTPUT ARGUMENTS
wolffd@0: % 
wolffd@0: %  sS2       (struct) the corresponding SOM Toolbox 2 version struct
wolffd@0: %
wolffd@0: % EXAMPLES
wolffd@0: %
wolffd@0: %  sM = som_vs1to2(sMold);
wolffd@0: %  sD = som_vs1to2(sDold);
wolffd@0: %  sT = som_vs1to2(sMold.train_sequence{1});
wolffd@0: %  sN = som_vs1to2(sDold.normalization); 
wolffd@0: %
wolffd@0: % SEE ALSO
wolffd@0: % 
wolffd@0: %  som_set          Set values and create SOM Toolbox structs.
wolffd@0: %  som_vs2to1       Transform structs from version 2.0 to 1.0.
wolffd@0: 
wolffd@0: % Copyright (c) 1999-2000 by the SOM toolbox programming team.
wolffd@0: % http://www.cis.hut.fi/projects/somtoolbox/
wolffd@0: 
wolffd@0: % Version 2.0beta juuso 101199
wolffd@0: 
wolffd@0: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0: %% check arguments
wolffd@0: 
wolffd@0: error(nargchk(1, 1, nargin));   % check no. of input arguments is correct
wolffd@0: 
wolffd@0: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0: %% set field values
wolffd@0: 
wolffd@0: if isfield(sS,'codebook'), type='som_map'; 
wolffd@0: elseif isfield(sS,'data'), type='som_data'; 
wolffd@0: elseif isfield(sS,'algorithm'), type = 'som_train';
wolffd@0: elseif isfield(sS,'inv_params'), type = 'som_norm'; 
wolffd@0: else
wolffd@0:   error('Unrecognized input struct.'); 
wolffd@0: end
wolffd@0: 
wolffd@0: switch type, 
wolffd@0:  case 'som_map',
wolffd@0:   msize = sS.msize; munits = prod(msize); dim = prod(size(sS.codebook))/munits; 
wolffd@0:   M = reshape(sS.codebook,[munits dim]);
wolffd@0: 
wolffd@0:   % topology
wolffd@0:   if strcmp(sS.shape,'rect'), shape = 'sheet'; else shape = sS.shape; end
wolffd@0:   sTopol = struct('type','som_topol','msize',msize,'lattice',sS.lattice,'shape',shape);
wolffd@0:   
wolffd@0:   % labels
wolffd@0:   labels = cell(munits,1);
wolffd@0:   for i=1:munits, 
wolffd@0:     for j=1:length(sS.labels{i}), labels{i,j} = sS.labels{i}{j}; end
wolffd@0:   end
wolffd@0:   
wolffd@0:   % trainhist
wolffd@0:   tl = length(sS.train_sequence); 
wolffd@0:   if strcmp(sS.init_type,'linear'); alg = 'lininit'; else alg = 'randinit'; end
wolffd@0:   trh = struct('type','som_train');
wolffd@0:   trh.algorithm = alg;
wolffd@0:   trh.neigh = sS.neigh;
wolffd@0:   trh.mask = sS.mask;
wolffd@0:   trh.data_name = sS.data_name; 
wolffd@0:   trh.radius_ini = NaN;
wolffd@0:   trh.radius_fin = NaN;
wolffd@0:   trh.alpha_ini = NaN; 
wolffd@0:   trh.alpha_type = '';
wolffd@0:   trh.trainlen = NaN;
wolffd@0:   trh.time = '';
wolffd@0:   for i=1:tl, 
wolffd@0:     trh(i+1) = som_vs1to2(sS.train_sequence{i});     
wolffd@0:     trh(i+1).mask = sS.mask;
wolffd@0:     trh(i+1).neigh = sS.neigh;
wolffd@0:     trh(i+1).data_name = sS.data_name;
wolffd@0:   end
wolffd@0:   
wolffd@0:   % component normalizations
wolffd@0:   cnorm = som_vs1to2(sS.normalization); 
wolffd@0:   if isempty(cnorm), 
wolffd@0:     cnorm = cell(dim,1);
wolffd@0:   elseif length(cnorm) ~= dim, 
wolffd@0:     warning('Incorrect number of normalizations. Normalizations ignored.\n');	    
wolffd@0:     cnorm = cell(dim,1);
wolffd@0:   else
wolffd@0:     if strcmp(cnorm{1}.method,'histD'),
wolffd@0:       M = redo_hist_norm(M,sS.normalization.inv_params,cnorm);
wolffd@0:     end
wolffd@0:   end     
wolffd@0:   
wolffd@0:   % map
wolffd@0:   sSnew = struct('type','som_map');
wolffd@0:   sSnew.codebook = M;
wolffd@0:   sSnew.topol = sTopol;
wolffd@0:   sSnew.labels = labels;
wolffd@0:   sSnew.neigh = sS.neigh;
wolffd@0:   sSnew.mask = sS.mask;
wolffd@0:   sSnew.trainhist = trh;
wolffd@0:   sSnew.name = sS.name;
wolffd@0:   sSnew.comp_norm = cnorm;
wolffd@0:   sSnew.comp_names = sS.comp_names;
wolffd@0:   
wolffd@0:  case 'som_data',
wolffd@0:   [dlen dim] = size(sS.data);
wolffd@0:   
wolffd@0:   % component normalizations
wolffd@0:   cnorm = som_vs1to2(sS.normalization);
wolffd@0:   if isempty(cnorm), 
wolffd@0:     cnorm = cell(dim,1);
wolffd@0:   elseif length(cnorm) ~= dim, 
wolffd@0:     warning('Incorrect number of normalizations. Normalizations ignored.\n');
wolffd@0:     cnorm = cell(dim,1);
wolffd@0:   else
wolffd@0:     if strcmp(cnorm{1}.method,'histD'),
wolffd@0:       sS.data = redo_hist_norm(sS.data,sS.normalization.inv_params,cnorm);
wolffd@0:     end     
wolffd@0:   end
wolffd@0: 
wolffd@0:   % data
wolffd@0:   sSnew = struct('type','som_data');
wolffd@0:   sSnew.data = sS.data;
wolffd@0:   sSnew.name = sS.name;
wolffd@0:   sSnew.labels = sS.labels;
wolffd@0:   sSnew.comp_names = sS.comp_names;
wolffd@0:   sSnew.comp_norm = cnorm;
wolffd@0:   sSnew.label_names = []; 
wolffd@0:   
wolffd@0:  case 'som_norm',       
wolffd@0:   if isempty(sS.inv_params), 
wolffd@0:     sSnew = []; 
wolffd@0:   else 
wolffd@0:     dim = size(sS.inv_params,2);      
wolffd@0:     sSnew = cell(dim,1);
wolffd@0:     switch sS.name, 
wolffd@0:      case 'som_var_norm',  method = 'var'; 
wolffd@0:      case 'som_lin_norm',  method = 'range'; 
wolffd@0:      case 'som_hist_norm', method = 'histD'; 
wolffd@0:      case 'som_unit_norm', method = '';
wolffd@0:       warning(['Normalization method ''som_unit_norm'' is not available' ...
wolffd@0: 	       ' in version 2 of SOM Toolbox.\n']);
wolffd@0:     end
wolffd@0:     if ~isempty(method), 
wolffd@0:       for i=1:dim, 
wolffd@0: 	sSnew{i} = struct('type','som_norm');
wolffd@0: 	sSnew{i}.method = method;
wolffd@0: 	sSnew{i}.params = [];
wolffd@0: 	sSnew{i}.status = 'done';
wolffd@0: 	switch method, 
wolffd@0: 	 case 'var',   
wolffd@0: 	  me = sS.inv_params(1,i); st = sS.inv_params(2,i);
wolffd@0: 	  sSnew{i}.params = [me, st];
wolffd@0: 	 case 'range', 
wolffd@0: 	  mi = sS.inv_params(1,i); ma = sS.inv_params(2,i); 
wolffd@0: 	  sSnew{i}.params = [mi, ma-mi]; 
wolffd@0: 	 case 'histD',
wolffd@0: 	  vals = sS.inv_params(1:(end-1),i);
wolffd@0: 	  bins = sum(isfinite(vals));
wolffd@0: 	  vals = vals(1:bins);
wolffd@0: 	  sSnew{i}.params = vals;
wolffd@0: 	end	  
wolffd@0:       end
wolffd@0:     end
wolffd@0:   end
wolffd@0:   
wolffd@0:  case 'som_train', 
wolffd@0:   sSnew = struct('type','som_train');
wolffd@0:   sSnew.algorithm = sS.algorithm;
wolffd@0:   sSnew.neigh = 'gaussian';
wolffd@0:   sSnew.mask = [];
wolffd@0:   sSnew.data_name = 'unknown'; 
wolffd@0:   sSnew.radius_ini = sS.radius_ini;
wolffd@0:   sSnew.radius_fin = sS.radius_fin;
wolffd@0:   sSnew.alpha_ini = sS.alpha_ini;
wolffd@0:   sSnew.alpha_type = sS.alpha_type;
wolffd@0:   sSnew.trainlen = sS.trainlen;
wolffd@0:   sSnew.time = sS.time;
wolffd@0:   
wolffd@0:  case 'som_topol', 
wolffd@0:   disp('Version 1.0 of SOM Toolbox did not have topology structure.\n');
wolffd@0:  
wolffd@0:  case {'som_grid','som_vis'}
wolffd@0:   disp('Version 1.0 of SOM Toolbox did not have visualization structs.\n');
wolffd@0:   
wolffd@0:  otherwise, 
wolffd@0:   
wolffd@0:   error('Unrecognized struct.');
wolffd@0: end
wolffd@0: 
wolffd@0: sS = sSnew;
wolffd@0: 
wolffd@0: %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
wolffd@0: %% subfunctions
wolffd@0: 
wolffd@0: function D = redo_hist_norm(D,inv_params,cnorm)
wolffd@0: 
wolffd@0:   dim = size(D,2);
wolffd@0: 
wolffd@0:   % first - undo the old way
wolffd@0:   n_bins = inv_params(end,:);
wolffd@0:   D   = round(D * sparse(diag(n_bins)));
wolffd@0:   for i = 1:dim,
wolffd@0:     if any(isnan(D(:, i))), D(isnan(D(:, i)), i) = n_bins(i); end
wolffd@0:     D(:, i) = inv_params(D(:, i), i);
wolffd@0:   end
wolffd@0:   % then - redo the new way
wolffd@0:   for i=1:dim, 
wolffd@0:     bins = length(cnorm{i}.params);
wolffd@0:     x = D(:,i);
wolffd@0:     inds = find(~isnan(x) & ~isinf(x))';
wolffd@0:     for j = inds, 
wolffd@0:       [dummy ind] = min(abs(x(j) - cnorm{i}.params));
wolffd@0:       if x(j) > cnorm{i}.params(ind) & ind < bins, x(j) = ind + 1;  
wolffd@0:       else x(j) = ind;
wolffd@0:       end
wolffd@0:     end
wolffd@0:     D(:,i) = (x-1)/(bins-1);
wolffd@0:   end
wolffd@0: 
wolffd@0: 
wolffd@0: 
wolffd@0: