annotate util/SMALL_solve.m @ 203:f3b6ddd2f04f luisf_dev

checks if the variable SMALL_path exists, and exits otherwise.
author luisf <luis.figueira@eecs.qmul.ac.uk>
date Tue, 20 Mar 2012 15:52:22 +0000
parents 751fa3bddd30
children a986ee86651e
rev   line source
idamnjanovic@8 1 function solver = SMALL_solve(Problem, solver)
ivan@161 2 %% SMALL sparse solver caller function
idamnjanovic@24 3 %
ivan@85 4 % Function gets as input SMALL structure that contains SPARCO problem to
ivan@85 5 % be solved, name of the toolbox and solver, and parameters file for
ivan@85 6 % particular solver.
ivan@85 7 %
ivan@85 8 % Outputs are solution, reconstructed signal and time spent
ivan@85 9
idamnjanovic@24 10 % Centre for Digital Music, Queen Mary, University of London.
idamnjanovic@24 11 % This file copyright 2009 Ivan Damnjanovic.
idamnjanovic@24 12 %
idamnjanovic@24 13 % This program is free software; you can redistribute it and/or
idamnjanovic@24 14 % modify it under the terms of the GNU General Public License as
idamnjanovic@24 15 % published by the Free Software Foundation; either version 2 of the
idamnjanovic@24 16 % License, or (at your option) any later version. See the file
idamnjanovic@24 17 % COPYING included with this distribution for more information.
luis@199 18 %
idamnjanovic@8 19 %%
idamnjanovic@8 20
luis@199 21 global SMALL_path
luis@199 22
luis@203 23 if (isempty(SMALL_path))
luis@203 24 error('SMALL_solve:varChk', '\nSMALL_path variable is not set... Please run SMALLboxInit and try again.\n\nExiting now...\n');
luis@203 25 end
luis@203 26
idamnjanovic@8 27 if isa(Problem.A,'float')
idamnjanovic@8 28 A = Problem.A;
idamnjanovic@8 29 SparseLab_A=Problem.A;
idamnjanovic@8 30 m = size(Problem.A,1); % m is the no. of rows.
idamnjanovic@8 31 n = size(Problem.A,2); % n is the no. of columns.
idamnjanovic@8 32 else
idamnjanovic@8 33 A = @(x) Problem.A(x,1); % The operator
idamnjanovic@8 34 AT = @(y) Problem.A(y,2); % and its transpose.
idamnjanovic@8 35 SparseLab_A =@(mode, m, n, x, I, dim) SL_A(Problem.A, mode, m, n, x, I, dim);
idamnjanovic@8 36 m = Problem.sizeA(1); % m is the no. of rows.
idamnjanovic@8 37 n = Problem.sizeA(2); % n is the no. of columns.
idamnjanovic@8 38
idamnjanovic@1 39 end
idamnjanovic@37 40 % if signal that needs to be represented is different then training set for
idamnjanovic@37 41 % dictionary learning it should be stored in Problem.b1 matix
idamnjanovic@37 42 if isfield(Problem, 'b1')
idamnjanovic@37 43 b = Problem.b1;
idamnjanovic@37 44 else
idamnjanovic@37 45 b = Problem.b; % The right-hand-side vector.
idamnjanovic@37 46 end
idamnjanovic@8 47 %%
ivan@140 48 if (solver.profile)
ivan@140 49 fprintf('\nStarting solver %s... \n', solver.name);
ivan@140 50 end
ivan@140 51
idamnjanovic@8 52 start=cputime;
idamnjanovic@37 53 tStart=tic;
luis@199 54
luis@199 55 % solvers configuration file
luis@199 56 run(fullfile(SMALL_path, 'config/SMALL_solve_config.m'));
idamnjanovic@8 57
idamnjanovic@8 58 %%
idamnjanovic@8 59 % Sparse representation time
idamnjanovic@37 60 tElapsed=toc(tStart);
idamnjanovic@8 61 solver.time = cputime - start;
ivan@140 62 if (solver.profile)
ivan@140 63 fprintf('Solver %s finished task in %2f seconds (cpu time). \n', solver.name, solver.time);
ivan@140 64 fprintf('Solver %s finished task in %2f seconds (tic-toc time). \n', solver.name, tElapsed);
ivan@140 65 end
idamnjanovic@37 66 solver.time=tElapsed;
idamnjanovic@8 67 % geting around out of memory problem when converting big matrix from
idamnjanovic@8 68 % sparse to full...
idamnjanovic@8 69
idamnjanovic@18 70 if isfield(Problem, 'sparse')&&(Problem.sparse==1)
idamnjanovic@8 71 solver.solution = y;
idamnjanovic@8 72 else
idamnjanovic@8 73 solver.solution = full(y);
idamnjanovic@8 74 end
idamnjanovic@37 75 if isfield(Problem,'reconstruct')
ivan@140 76 % Reconstruct the signal from the solution
ivan@140 77 solver.reconstructed = Problem.reconstruct(solver.solution);
idamnjanovic@8 78 end
idamnjanovic@37 79 end