idamnjanovic@8: function solver = SMALL_solve(Problem, solver)
ivan@161: %% SMALL sparse solver caller function
idamnjanovic@24: %
ivan@85: %   Function gets as input SMALL structure that contains SPARCO problem to
ivan@85: %   be solved, name of the toolbox and solver, and parameters file for
ivan@85: %   particular solver.
ivan@85: %
ivan@85: %   Outputs are solution, reconstructed signal and time spent
ivan@85: 
idamnjanovic@24: %   Centre for Digital Music, Queen Mary, University of London.
idamnjanovic@24: %   This file copyright 2009 Ivan Damnjanovic.
idamnjanovic@24: %
idamnjanovic@24: %   This program is free software; you can redistribute it and/or
idamnjanovic@24: %   modify it under the terms of the GNU General Public License as
idamnjanovic@24: %   published by the Free Software Foundation; either version 2 of the
idamnjanovic@24: %   License, or (at your option) any later version.  See the file
idamnjanovic@24: %   COPYING included with this distribution for more information.
luis@199: %
idamnjanovic@8: %%
idamnjanovic@8: 
luis@216: SMALLboxInit
luis@203: 
idamnjanovic@8: if isa(Problem.A,'float')
idamnjanovic@8:     A = Problem.A;
idamnjanovic@8:     SparseLab_A=Problem.A;
idamnjanovic@8:     m = size(Problem.A,1);      % m is the no. of rows.
idamnjanovic@8:     n = size(Problem.A,2);      % n is the no. of columns.
idamnjanovic@8: else
idamnjanovic@8:     A  = @(x) Problem.A(x,1);  % The operator
idamnjanovic@8:     AT = @(y) Problem.A(y,2);  % and its transpose.
idamnjanovic@8:     SparseLab_A =@(mode, m, n, x, I, dim) SL_A(Problem.A, mode, m, n, x, I, dim);
idamnjanovic@8:     m = Problem.sizeA(1);      % m is the no. of rows.
idamnjanovic@8:     n = Problem.sizeA(2);      % n is the no. of columns.
idamnjanovic@8:     
idamnjanovic@1: end
idamnjanovic@37: % if signal that needs to be represented is different then training set for
idamnjanovic@37: % dictionary learning it should be stored in Problem.b1 matix
idamnjanovic@37: if isfield(Problem, 'b1')
idamnjanovic@37:     b = Problem.b1;
idamnjanovic@37: else
idamnjanovic@37:     b = Problem.b;            % The right-hand-side vector.
idamnjanovic@37: end
idamnjanovic@8: %%
ivan@140: if (solver.profile)
ivan@140:     fprintf('\nStarting solver %s... \n', solver.name);
ivan@140: end
ivan@140: 
idamnjanovic@8: start=cputime;
idamnjanovic@37: tStart=tic;
luis@199: 
luis@228: %% solvers configuration
luis@228: % test if there is a locally modified version of the config
luis@228: % otherwise reads the "default" config file
luis@228: if exist(fullfile(SMALL_path, 'config/SMALL_solve_config_local.m'), 'file') == 2
luis@228:     run(fullfile(SMALL_path, 'config/SMALL_solve_config_local.m'));
luis@228: else
luis@228:     run(fullfile(SMALL_path, 'config/SMALL_solve_config.m'));
luis@228: end
idamnjanovic@8: 
idamnjanovic@8: %%
idamnjanovic@8: %   Sparse representation time
idamnjanovic@37: tElapsed=toc(tStart);
idamnjanovic@8: solver.time = cputime - start;
ivan@140: if (solver.profile)
ivan@140:     fprintf('Solver %s finished task in %2f seconds (cpu time). \n', solver.name, solver.time);
ivan@140:     fprintf('Solver %s finished task in %2f seconds (tic-toc time). \n', solver.name, tElapsed);
ivan@140: end
idamnjanovic@37: solver.time=tElapsed;
idamnjanovic@8: % geting around out of memory problem when converting big matrix from
idamnjanovic@8: % sparse to full...
idamnjanovic@8: 
idamnjanovic@18: if isfield(Problem, 'sparse')&&(Problem.sparse==1)
idamnjanovic@8:     solver.solution = y;
idamnjanovic@8: else
idamnjanovic@8:     solver.solution = full(y);
idamnjanovic@8: end
idamnjanovic@37: if isfield(Problem,'reconstruct')
ivan@140:     %   Reconstruct the signal from the solution
ivan@140:     solver.reconstructed  = Problem.reconstruct(solver.solution);
idamnjanovic@8: end
idamnjanovic@37: end