diff toolboxes/wrapper_ALPS_toolbox.m @ 154:0de08f68256b ivand_dev

ALPS toolbox - Algebraic Pursuit added to smallbox

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/wrapper_ALPS_toolbox.m	Fri Aug 12 11:17:47 2011 +0100
@@ -0,0 +1,80 @@
+function [x , numiter, time, x_path] = wrapper_ALPS_toolbox(b, A, param)
+%% SMALL wrapper for ALPS toolbox
+%
+%   Function gets as input
+%       b - measurement vector 
+%       A - dictionary 
+%       K - desired sparsity level
+%       param - structure containing additional parameters
+%   Output:
+%       x - sparse solution
+%       numiter - number of iterations
+%       time - time needed to solve the problem#
+%       x_path - matrix containing x after every iteration
+
+%   Centre for Digital Music, Queen Mary, University of London.
+%   This file copyright 2011 Ivan Damnjanovic.
+%
+%   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.
+%   
+%%
+
+if isfield(param, 'sparsity')
+   sparsity = param.sparsity;
+else
+   printf('\nAlebraic Pursuit algorithms require desired sparsity level.\n("sparsity" field in solver parameters structure)\n ');
+   return
+end
+
+if isfield(param, 'memory')
+    memory = param.memory;
+else
+    memory = 0;
+end
+
+if isfield(param, 'mode')
+    mode = param.mode;
+else
+    mode = 0;
+end
+if isfield(param, 'tolerance')
+    tolerance = param.tolerance;
+else
+    tolerance = 1e-5;
+end
+if isfield(param, 'iternum')
+    iternum = param.iternum;
+else
+    iternum = 300;
+end
+if isfield(param, 'verbose')
+    verbose = param.verbose;
+else
+    verbose = 0;
+end
+if isfield(param, 'tau')
+    tau = param.tau;
+else
+    tau = 1/2;
+end
+if isfield(param, 'useCG')
+    useCG = param.useCG;
+else
+    useCG = 0;
+end
+if isfield(param, 'mu')
+    mu = param.mu;
+else
+    mu = 0;
+end
+training_size = size(b,2);
+x=zeros(size(A,2),training_size);
+for i = 1:training_size
+    [x(:,i), numiter, time, x_path] = AlgebraicPursuit(b(:,i), A, sparsity, 'memory', memory,...
+        'mode', mode, 'tolerance', tolerance, 'ALPSiterations', iternum, ...
+        'verbose', verbose, 'tau', tau, 'useCG', useCG, 'mu', mu);
+end
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