Mercurial > hg > smallbox
view util/SMALL_solve.m @ 224:fd0b5d36f6ad danieleb
Updated the contents of this branch with the contents of the default branch.
author | luisf <luis.figueira@eecs.qmul.ac.uk> |
---|---|
date | Thu, 12 Apr 2012 13:52:28 +0100 |
parents | 4ea4badb2266 a986ee86651e |
children |
line wrap: on
line source
function solver = SMALL_solve(Problem, solver) %% SMALL sparse solver caller function % % Function gets as input SMALL structure that contains SPARCO problem to % be solved, name of the toolbox and solver, and parameters file for % particular solver. % % Outputs are solution, reconstructed signal and time spent % 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. % %% SMALLboxInit if isa(Problem.A,'float') A = Problem.A; SparseLab_A=Problem.A; m = size(Problem.A,1); % m is the no. of rows. n = size(Problem.A,2); % n is the no. of columns. else A = @(x) Problem.A(x,1); % The operator AT = @(y) Problem.A(y,2); % and its transpose. SparseLab_A =@(mode, m, n, x, I, dim) SL_A(Problem.A, mode, m, n, x, I, dim); m = Problem.sizeA(1); % m is the no. of rows. n = Problem.sizeA(2); % n is the no. of columns. end % if signal that needs to be represented is different then training set for % dictionary learning it should be stored in Problem.b1 matix if isfield(Problem, 'b1') b = Problem.b1; else b = Problem.b; % The right-hand-side vector. end %% if (solver.profile) fprintf('\nStarting solver %s... \n', solver.name); end start=cputime; tStart=tic; % solvers configuration file run(fullfile(SMALL_path, 'config/SMALL_solve_config.m')); %% % Sparse representation time tElapsed=toc(tStart); solver.time = cputime - start; if (solver.profile) fprintf('Solver %s finished task in %2f seconds (cpu time). \n', solver.name, solver.time); fprintf('Solver %s finished task in %2f seconds (tic-toc time). \n', solver.name, tElapsed); end solver.time=tElapsed; % geting around out of memory problem when converting big matrix from % sparse to full... if isfield(Problem, 'sparse')&&(Problem.sparse==1) solver.solution = y; else solver.solution = full(y); end if isfield(Problem,'reconstruct') % Reconstruct the signal from the solution solver.reconstructed = Problem.reconstruct(solver.solution); end end