comparison util/SMALL_learn.m @ 36:e6191f5bb21b

(none)

 %   Outputs are Learned dictionary and time spent as a part of DL structure
 %%
  
   fprintf('\nStarting Dictionary Learning %s... \n', DL.name);
   start=cputime;
-  
+  tStart=tic;
   if strcmpi(DL.toolbox,'KSVD')
     param=DL.param; 
     param.data=Problem.b;
  
-    D = eval([DL.name,'(param, ''t'', 5);']);
+    D = eval([DL.name,'(param)']);%, ''t'', 5);']);
   elseif strcmpi(DL.toolbox,'KSVDS')
     param=DL.param; 
     param.data=Problem.b;
     
     D = eval([DL.name,'(param, ''t'', 5);']);

     %   unit lenght.
     
     for i = 1: size(D,2)
         D(:,i)=D(:,i)/norm(D(:,i));
     end
+  elseif strcmpi(DL.toolbox,'SMALL')
     
+    X  = Problem.b; 
+    param=DL.param;
+    
+    D = eval([DL.name,'(X, param);']);
+    %   we need to make sure that columns are normalised to
+    %   unit lenght.
+    
+    for i = 1: size(D,2)
+        D(:,i)=D(:,i)/norm(D(:,i));
+    end
+  elseif  strcmpi(DL.toolbox,'mpv2')
+      X = Problem.b(:,1:1:40000);
+      jD0 = mpv2.SimpleMatrix(DL.param.D);
+      jDicLea = mpv2.DictionaryLearning(jD0, 1,1);
+% !!!!! MAYBE lambda is not needed for ILS - NEED TO CHECK!!!!
+      jDicLea.setLambda('L', DL.param.lambda, DL.param.lambda, 1000);
+       jDicLea.setVerbose(2);
+      jDicLea.setORMP(16, 1e-6, DL.param.abs);
+      eval(['jDicLea.',DL.name,'( X(:), DL.param.iternum );']);
+      jD =  jDicLea.getDictionary();
+      
+      D = reshape(jD.getAll(), size(X,1), DL.param.K);
+      
 %   To introduce new dictionary learning technique put the files in
 %   your Matlab path. Next, unique name <TolboxID> for your toolbox needs 
 %   to be defined and also prefferd API for toolbox functions <Preffered_API>
 %   
 % elseif strcmpi(DL.toolbox,'<ToolboxID>')

     return
   end
   
 %%
 %   Dictionary Learning time
-
+tElapsed=toc(tStart);
   DL.time = cputime - start;
   fprintf('\n%s finished task in %2f seconds. \n', DL.name, DL.time);
-
+  fprintf('\n%s finished task in %2f seconds. \n', DL.name, tElapsed);
+DL.time=tElapsed;
 %   If dictionary is given as a sparse matrix change it to full  
 
   DL.D = full(D);
   
 end