# HG changeset patch # User Maria Jafari # Date 1302536671 -3600 # Node ID f6cc633fd94b80e55d654ac86ec498d5c8182631 # Parent fd1c32cda22c380f0e21430a10b113cd33c44c71 cpu/tic-toc time comments diff -r fd1c32cda22c -r f6cc633fd94b examples/Image Denoising/SMALL_ImgDenoise_DL_test_KSVDvsRLSDLA.m --- a/examples/Image Denoising/SMALL_ImgDenoise_DL_test_KSVDvsRLSDLA.m Tue Apr 05 17:03:26 2011 +0100 +++ b/examples/Image Denoising/SMALL_ImgDenoise_DL_test_KSVDvsRLSDLA.m Mon Apr 11 16:44:31 2011 +0100 @@ -206,7 +206,7 @@ 'dictsize', SMALL.Problem.p,... 'forgettingMode', 'FIX',... 'forgettingFactor', lambda,... - 'show_dict', 500); + 'show_dict', 1000); SMALL.DL(3) = SMALL_learn(SMALL.Problem, SMALL.DL(3)); diff -r fd1c32cda22c -r f6cc633fd94b util/SMALL_learn.m --- a/util/SMALL_learn.m Tue Apr 05 17:03:26 2011 +0100 +++ b/util/SMALL_learn.m Mon Apr 11 16:44:31 2011 +0100 @@ -95,8 +95,8 @@ % Dictionary Learning time tElapsed=toc(tStart); DL.time = cputime - start; - fprintf('\n%s finished task in %2f seconds. \n', DL.name, DL.time); - fprintf('\n%s finished task in %2f seconds. \n', DL.name, tElapsed); + 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); DL.time=tElapsed; % If dictionary is given as a sparse matrix change it to full diff -r fd1c32cda22c -r f6cc633fd94b util/SMALL_solve.m --- a/util/SMALL_solve.m Tue Apr 05 17:03:26 2011 +0100 +++ b/util/SMALL_solve.m Mon Apr 11 16:44:31 2011 +0100 @@ -93,8 +93,8 @@ % Sparse representation time tElapsed=toc(tStart); solver.time = cputime - start; -fprintf('Solver %s finished task in %2f seconds. \n', solver.name, solver.time); -fprintf('Solver %s finished task in %2f seconds. \n', solver.name, tElapsed); +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); solver.time=tElapsed; % geting around out of memory problem when converting big matrix from % sparse to full...