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function test_failed=test_thresh
%-*- texinfo -*-
%@deftypefn {Function} test_thresh
%@verbatim
%TEST_THRESH Compare sparse and full thesholding
%@end verbatim
%@strong{Url}: @url{http://ltfat.github.io/doc/testing/test_thresh.html}
%@end deftypefn
% Copyright (C) 2005-2016 Peter L. Soendergaard <peter@sonderport.dk>.
% This file is part of LTFAT version 2.2.0
%
% 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 3 of the License, or
% (at your option) any later version.
%
% This program is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
% GNU General Public License for more details.
%
% You should have received a copy of the GNU General Public License
% along with this program. If not, see <http://www.gnu.org/licenses/>.
test_failed=0;
disp(' =============== TEST_THRESH ================');
global LTFAT_TEST_TYPE;
if ~strcmpi(LTFAT_TEST_TYPE,'double')
disp(sprintf('Skipping. Cannot work with sparse matrices of type %s.',LTFAT_TEST_TYPE));
return;
end
lambda=0.1;
ttypes={'hard','soft','wiener'};
for ii=1:2
if ii==1
g=tester_rand(3,4);
field='REAL ';
g(2,2)=lambda;
else
g=tester_crand(3,4);
field='CMPLX ';
g(2,2)=lambda;
end;
for jj=1:3
ttype=ttypes{jj};
[xo_full, Nfull] = thresh(g,lambda,ttype,'full');
[xo_sparse, Nsp] = thresh(g,lambda,ttype,'sparse');
res = xo_full-xo_sparse;
res = norm(res(:));
res2 = Nfull-Nsp;
[test_failed,fail]=ltfatdiditfail(res,test_failed);
s=sprintf(['THRESH %s %s %0.5g %s'],field,ttype,res,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res2,test_failed);
s=sprintf(['THRESH N %s %s %0.5g %s'],field,ttype,res2,fail);
disp(s);
% Extend lambda to:
% a) Vector
lambdavec = lambda*ones(numel(g),1);
[xo_full2, Nfull2] = thresh(g,lambdavec,ttype,'full');
[xo_sparse2, Nsp2] = thresh(g,lambdavec,ttype,'sparse');
res_full = xo_full2-xo_full;
res_sparse = xo_sparse2-xo_sparse;
res_full = norm(res_full(:));
res_sparse = norm(res_sparse(:));
res_nfull = Nfull2-Nfull;
res_nsparse = Nfull2-Nfull;
[test_failed,fail]=ltfatdiditfail(res,test_failed);
s=sprintf(['THRESH VEC FULL %s %s %0.5g %s'],field,ttype,res_full,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res,test_failed);
s=sprintf(['THRESH VEC SPARSE %s %s %0.5g %s'],field,ttype,res_sparse,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res2,test_failed);
s=sprintf(['THRESH VEC N FULL %s %s %0.5g %s'],field,ttype,res_nfull,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res2,test_failed);
s=sprintf(['THRESH VEC N SPARSE %s %s %0.5g %s'],field,ttype,res_nsparse,fail);
disp(s);
% b) Same shape as g
lambdamat = lambda*ones(size(g));
[xo_full3, Nfull3] = thresh(g,lambdamat,ttype,'full');
[xo_sparse3, Nsp3] = thresh(g,lambdamat,ttype,'sparse');
res_full = xo_full3-xo_full;
res_sparse = xo_sparse3-xo_sparse;
res_full = norm(res_full(:));
res_sparse = norm(res_sparse(:));
res_nfull = Nfull3-Nfull;
res_nsparse = Nfull3-Nfull;
[test_failed,fail]=ltfatdiditfail(res,test_failed);
s=sprintf(['THRESH MAT FULL %s %s %0.5g %s'],field,ttype,res_full,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res,test_failed);
s=sprintf(['THRESH MAT SPARSE %s %s %0.5g %s'],field,ttype,res_sparse,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res2,test_failed);
s=sprintf(['THRESH MAT N FULL %s %s %0.5g %s'],field,ttype,res_nfull,fail);
disp(s);
[test_failed,fail]=ltfatdiditfail(res2,test_failed);
s=sprintf(['THRESH MAT N SPARSE %s %s %0.5g %s'],field,ttype,res_nsparse,fail);
disp(s);
end;
end;
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