comparison util/SMALL_learn.m @ 190:759313488e7b luisf_dev

Added two config files for the 2 step dic and learn scripts; removed 'extra' folder; created init script (initial version).

 if (DL.profile)
   fprintf('\nStarting Dictionary Learning %s... \n', DL.name);
 end
   start=cputime;
   tStart=tic;
-  if strcmpi(DL.toolbox,'KSVD')
-    param=DL.param; 
-    param.data=Problem.b;
- 
-    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);']);
-  elseif strcmpi(DL.toolbox,'SPAMS')
+  % configuration file
+  run([SMALL_path 'config/SMALL_learn_config.m']);
     
-    X  = Problem.b; 
-    param=DL.param;
-    
-    D = eval([DL.name,'(X, param);']);
-    %   As some versions of SPAMS does not produce unit norm column
-    %   dictionaries, 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,'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,'TwoStepDL')
-        
-    DL=SMALL_two_step_DL(Problem, DL);
-    
-    %   we need to make sure that columns are normalised to
-    %   unit lenght.
-    
-    for i = 1: size(DL.D,2)
-        DL.D(:,i)=DL.D(:,i)/norm(DL.D(:,i));
-    end
-    D = DL.D;
-    
-elseif strcmpi(DL.toolbox,'MMbox')
-        
-    DL = wrapper_mm_DL(Problem, DL);
-    
-    %   we need to make sure that columns are normalised to
-    %   unit lenght.
-    
-    for i = 1: size(DL.D,2)
-        DL.D(:,i)=DL.D(:,i)/norm(DL.D(:,i));
-    end
-    D = DL.D; 
-    
-%   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>')
-%     % This is an example of API that can be used:
-%     % - get training set from Problem part of structure
-%     % - assign parameters defined in the main program
-%
-%     X  = Problem.b; 
-%     param=DL.param;
-%
-%     % - Evaluate the function (DL.name - defined in the main) with
-%     %   parameters given above
-%
-%     D = eval([DL.name,'(<Preffered_API>);']);
-
-  else
-    printf('\nToolbox has not been registered. Please change SMALL_learn file.\n');
-    return
-  end
-  
 %%
 %   Dictionary Learning time
 tElapsed=toc(tStart);
 DL.time = cputime - start;
 if (DL.profile)