changeset 126:db5a7fe1a404 ivand_dev

Merge from branch "sup_158_IMG_Processing_toolbox_"

--- a/util/SMALL_learn.m	Wed May 25 15:29:20 2011 +0100
+++ b/util/SMALL_learn.m	Wed May 25 15:30:34 2011 +0100
@@ -1,5 +1,13 @@
 function DL = SMALL_learn(Problem,DL)
-%%% SMALL Dictionary Learning   
+%% SMALL Dictionary Learning   
+%   
+%   Function gets as input Problem and Dictionary Learning (DL) structures 
+%   In Problem structure field b with the training set needs to be defined
+%   In DL fields with name of the toolbox and solver, and parameters file 
+%   for particular dictionary learning technique needs to be present.
+%
+%   Outputs are Learned dictionary and time spent as a part of DL structure
+
 %
 %   Centre for Digital Music, Queen Mary, University of London.
 %   This file copyright 2009 Ivan Damnjanovic.
@@ -9,13 +17,6 @@
 %   published by the Free Software Foundation; either version 2 of the
 %   License, or (at your option) any later version.  See the file
 %   COPYING included with this distribution for more information.
-%   
-%   Function gets as input Problem and Dictionary Learning (DL) structures 
-%   In Problem structure field b with the training set needs to be defined
-%   In DL fields with name of the toolbox and solver, and parameters file 
-%   for particular dictionary learning technique needs to be present.
-%
-%   Outputs are Learned dictionary and time spent as a part of DL structure
 %%
  
   fprintf('\nStarting Dictionary Learning %s... \n', DL.name);
@@ -56,19 +57,7 @@
     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>