annotate util/SMALL_learn.m @ 211:0c7c20f3246c luisf_dev

Added comments to ~/DL/Majorization Minimization DL/wrapper_mm_DL.m and ~/DL/Majorization Minimization DL/wrapper_mm_solver.m files.

function DL = SMALL_learn(Problem,DL)
%% 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.
%
%   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.
%%

global SMALL_path

if (isempty(SMALL_path))
    error('SMALL_learn:varChk', '\nSMALL_path variable is not set... Please run SMALLboxInit and try again.\n\nExiting now...\n');
end

if (DL.profile)
    fprintf('\nStarting Dictionary Learning %s... \n', DL.name);
end

start=cputime;
tStart=tic;

% toolboxes configuration file
run(fullfile(SMALL_path, 'config/SMALL_learn_config.m'));

%%
%   Dictionary Learning time
tElapsed=toc(tStart);
DL.time = cputime - start;
if (DL.profile)
    fprintf('\n%s finished task in %2f seconds (cpu time). \n', DL.name, DL.time);
    fprintf('\n%s finished task in %2f seconds (tic-toc time). \n', DL.name, tElapsed);
end
DL.time=tElapsed;
%   If dictionary is given as a sparse matrix change it to full

DL.D = full(D);

end