--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/test/test_matrix_linlsqsvd.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,114 @@
+% TEST_MATRIX_LINLSQSVD tests the linlsqsvd method of the AO class.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% L Ferraioli 10-11-2010
+%
+% $Id: test_matrix_linlsqsvd.m,v 1.1 2011/02/18 17:07:35 luigi Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+%% 1) Determine the coefficients of a linear combination of noises and
+%% comapre with lscov:
+%
+% Make some data
+fs    = 10;
+nsecs = 10;
+B1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+B1.setName;
+B2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+B2.setName;
+B3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+B3.setName;
+B4 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+B4.setName;
+
+C1 = matrix(B1,B2,plist('shape',[2,1]));
+C1.setName;
+C2 = matrix(B3,B4,plist('shape',[2,1]));
+C2.setName;
+
+C = matrix([B1 B3;B2 B4]);
+C.setName;
+
+n1  = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+n2  = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+
+n = matrix(n1,n2,plist('shape',[2,1]));
+n.setName;
+
+a = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/T'))];
+A = matrix(a,plist('shape',[2,1]));
+
+% assign output values
+y = C*A + n;
+
+%%% Get a fit with linlsqsvd
+pobj1 = linlsqsvd(C1, C2, y);
+
+% combine results
+for ii=1:numel(pobj1.y)
+  prs(ii) = ao(cdata(pobj1.y(ii)));
+  prs(ii).setYunits(pobj1.yunits(ii));
+end
+Pars = matrix(prs,plist('shape',[numel(prs),1]));
+yfit1 = C*Pars;
+
+%%% do linear combination: using eval
+yfit2 = pobj1.eval;
+
+% Plot (compare data with fit)
+iplot(y.objs(1), yfit1.objs(1), yfit2.objs(1))
+iplot(y.objs(2), yfit1.objs(2), yfit2.objs(2))
+
+%% 2) Determine the coefficients of a linear combination of noises:
+%
+% Make some data
+fs    = 10;
+nsecs = 10;
+x1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+x1.setName;
+x2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+x2.setName;
+x3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T'));
+x3.setName;
+x4 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+x4.setName;
+
+C1 = matrix(x1,x3,plist('shape',[2,1]));
+C1.setName;
+C2 = matrix(x2,x4,plist('shape',[2,1]));
+C2.setName;
+
+C = matrix([x1 x2;x3 x4]);
+C.setName;
+
+n1  = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+n2  = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm'));
+n = matrix(n1,n2,plist('shape',[2,1]));
+n.setName;
+
+a = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/m'))];
+A = matrix(a,plist('shape',[2,1]));
+A.setName;
+
+y = C*A + n;
+
+%%% Get a fit with linlsqsvd
+pobj1 = linlsqsvd(C1, C2, y);
+
+
+% combine results
+for ii=1:numel(pobj1.y)
+  prs(ii) = ao(cdata(pobj1.y(ii)));
+  prs(ii).setYunits(pobj1.yunits(ii));
+end
+Pars = matrix(prs,plist('shape',[numel(prs),1]));
+yfit1 = C*Pars;
+
+%%% do linear combination: using eval
+yfit2 = pobj1.eval;
+
+% Plot (compare data with fit)
+iplot(y.objs(1), yfit1.objs(1), yfit2.objs(1))
+iplot(y.objs(2), yfit1.objs(2), yfit2.objs(2))
+
+