changeset 195:d50f5bdbe14c luisf_dev

- Added SMALL_DL_test: simple DL showcase
- Added dico_decorr_symmetric: improved version of INK-SVD decorrelation step
- Debugged SMALL_learn, SMALLBoxInit and SMALL_two_step_DL

--- a/DL/two-step DL/SMALL_two_step_DL.m	Tue Mar 13 17:33:20 2012 +0000
+++ b/DL/two-step DL/SMALL_two_step_DL.m	Wed Mar 14 14:42:52 2012 +0000
@@ -98,6 +98,7 @@
 % want sparse representation of training set, and in Problem.b1 in this
 % version of software we store the signal that needs to be represented
 % (for example the whole image)
+global SMALL_path
 
 tmpTraining = Problem.b1;
 Problem.b1 = sig;
@@ -144,4 +145,4 @@
   Y(blockids) = sum(X(:,blockids).^2);
 end
 
-end
\ No newline at end of file
+end

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/DL/two-step DL/dico_decorr_symetric.m	Wed Mar 14 14:42:52 2012 +0000
@@ -0,0 +1,61 @@
+function dico = dico_decorr_symetric(dico, mu, amp)
+    %DICO_DECORR decorrelate a dictionary
+    %   Parameters:
+    %   dico: the dictionary
+    %   mu: the coherence threshold
+    %   amp: the amplitude coefficients, only used to decide which atom to
+    %   project
+    %
+    %   Result:
+    %   dico: a dictionary close to the input one with coherence mu.
+    
+    eps = 1e-6; % define tolerance for normalisation term alpha
+    
+    % convert mu to the to the mean direction
+    theta = acos(mu)/2;
+    ctheta = cos(theta);
+    stheta = sin(theta);
+    
+    % compute atom weights
+    %     if nargin > 2
+    %         rank = sum(amp.*amp, 2);
+    %     else
+    %         rank = randperm(length(dico));
+    %     end
+    
+    % several decorrelation iterations might be needed to reach global
+    % coherence mu. niter can be adjusted to needs.
+    niter = 1;
+    while max(max(abs(dico'*dico -eye(length(dico))))) > mu + 0.01
+        % find pairs of high correlation atoms
+        colors = dico_color(dico, mu);
+        
+        % iterate on all pairs
+        nbColors = max(colors);
+        for c = 1:nbColors
+            index = find(colors==c);
+            if numel(index) == 2
+                if dico(:,index(1))'*dico(:,index(2)) > 0               
+                    %build the basis vectors
+                    v1 = dico(:,index(1))+dico(:,index(2));
+                    v1 = v1/norm(v1);
+                    v2 = dico(:,index(1))-dico(:,index(2));
+                    v2 = v2/norm(v2);
+                    
+                    dico(:,index(1)) = ctheta*v1+stheta*v2;
+                    dico(:,index(2)) = ctheta*v1-stheta*v2;
+                else
+                    v1 = dico(:,index(1))-dico(:,index(2));
+                    v1 = v1/norm(v1);
+                    v2 = dico(:,index(1))+dico(:,index(2));
+                    v2 = v2/norm(v2);
+                    
+                    dico(:,index(1)) = ctheta*v1+stheta*v2;
+                    dico(:,index(2)) = -ctheta*v1+stheta*v2;
+                end
+            end
+        end
+        niter = niter+1;
+    end
+end
+

--- a/SMALLboxInit.m	Tue Mar 13 17:33:20 2012 +0000
+++ b/SMALLboxInit.m	Wed Mar 14 14:42:52 2012 +0000
@@ -1,5 +1,5 @@
 global SMALL_path;
-SMALL_path=pwd;
+SMALL_path=[fileparts(mfilename('fullpath')) filesep];
 
 % SMALL_p = genpath(SMALL_path);
 % addpath(SMALL_p);

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/examples/SMALL_DL_test.m	Wed Mar 14 14:42:52 2012 +0000
@@ -0,0 +1,76 @@
+function SMALL_DL_test
+clear, clc, close all
+% Create a 2-dimensional dataset of points that are oriented in 3
+% directions on a x/y plane
+
+%
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2012 Daniele Barchiesi.
+%
+%   This program is free software; you can redistribute it and/or
+%   modify it under the terms of the GNU General Public License as
+%   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.
+
+nData = 10000;						%number of data
+theta = [pi/6 pi/3 4*pi/6];			%angles
+nAngles = length(theta);			%number of angles
+Q	  = [cos(theta); sin(theta)];	%rotation matrix
+X	  = Q*randmog(nAngles,nData);	%training data
+
+% find principal directions using PCA
+XXt = X*X';							%cross correlation matrix
+[U ~] = svd(XXt);					%svd of XXt
+
+scale = 3;							%scale factor for plots
+subplot(1,2,1), hold on
+title('Principal Component Analysis')
+scatter(X(1,:), X(2,:),'.');		%scatter training data
+O = zeros(size(U));					%origin
+quiver(O(1,1:2),O(2,1:2),scale*U(1,:),scale*U(2,:),...
+	'LineWidth',2,'Color','k')		%plot atoms
+axis equal							%scale axis
+
+subplot(1,2,2), hold on
+title('K-SVD Dictionary')
+scatter(X(1,:), X(2,:),'.');
+axis equal
+
+nAtoms  = 3;						%number of atoms in the dictionary
+nIter   = 1;						%number of dictionary learning iterations
+initDict = normc(randn(2,nAtoms));	%random initial dictionary
+O = zeros(size(initDict));			%origin
+
+% apply dictionary learning algorithm
+ksvd_params = struct('data',X,...			%training data
+					 'Tdata',1,...			%sparsity level
+					 'dictsize',nAtoms,...	%number of atoms
+					 'initdict',initDict,...%initial dictionary
+					 'iternum',10);			%number of iterations
+DL = SMALL_init_DL('ksvd','ksvd',ksvd_params); %dictionary learning structure
+DL.D = initDict;							%copy initial dictionary in solution variable
+problem = struct('b',X);					%copy training data in problem structure
+
+xdata = DL.D(1,:);
+ydata = DL.D(2,:);
+qPlot = quiver(O(1,:),O(2,:),scale*initDict(1,:),scale*initDict(2,:),...
+	'LineWidth',2,'Color','k','UDataSource','xdata','VDataSource','ydata');
+
+for iIter=1:nIter
+	DL.ksvd_params.initdict = DL.D;
+	pause
+	DL = SMALL_learn(problem,DL);			%learn dictionary
+	xdata = scale*DL.D(1,:);	
+	ydata = scale*DL.D(2,:);
+	refreshdata(gcf,'caller');
+end
+
+
+function X = randmog(m, n)
+% RANDMOG - Generate mixture of Gaussians
+s = [0.2 2];
+% Choose which Gaussian
+G1 = (rand(m, n) < 0.9);
+% Make them
+X = (G1.*s(1) + (1-G1).*s(2)) .* randn(m,n);

--- a/util/SMALL_learn.m	Tue Mar 13 17:33:20 2012 +0000
+++ b/util/SMALL_learn.m	Wed Mar 14 14:42:52 2012 +0000
@@ -18,6 +18,7 @@
 %   License, or (at your option) any later version.  See the file
 %   COPYING included with this distribution for more information.
 %%
+global SMALL_path
 if (DL.profile)
   fprintf('\nStarting Dictionary Learning %s... \n', DL.name);
 end
@@ -41,4 +42,4 @@
   DL.D = full(D);
   
 end
-  
\ No newline at end of file
+