view toolboxes/wrapper_ALPS_toolbox.m @ 212:1d134a1b6f95 luisf_dev

Propagate the change from 'mailhe' to 'opt' in two_step_DL to the examples

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