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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% TEST_AO_LSCOV tests the lscov method of the AO class. % % M Hueller 19-03-10 % % $Id: test_ao_lscov.m,v 1.7 2010/03/19 11:25:36 mauro Exp $ % % function test_ao_lscov() %% 1) Determine the coefficients of a linear combination of noises: % % Make some data fs = 10; nsecs = 10; B1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T')); B2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T')); B3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'T')); n = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm')); c = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/T')) ao(3,plist('yunits','m T^-1'))]; y = c(1)*B1 + c(2)*B2 + c(3)*B3 + n; y.simplifyYunits; % Get a fit for c p_s = lscov(B1, B2, B3, y); % do linear combination: using lincom yfit1 = lincom(B1, B2, B3, p_s); yfit1.simplifyYunits; % do linear combination: using eval yfit2 = p_s.eval(B1, B2, B3); % Plot (compare data with fit) iplot(y, yfit1, yfit2, plist('Linestyles', {'-','--'})) %% 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')); x2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm')); x3 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'C')); n = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', nsecs, 'yunits', 'm')); c = [ao(1,plist('yunits','m/T')) ao(2,plist('yunits','m/m')) ao(3,plist('yunits','m C^-1'))]; y = c(1)*x1 + c(2)*x2 + c(3)*x3 + n; y.simplifyYunits; % Get a fit for c p_m = lscov(x1, x2, x3, y); % do linear combination: using lincom yfit1 = lincom(x1, x2, x3, p_m); % do linear combination: using eval pl_split = plist('times', [1 5]); yfit2 = p_m.eval(plist('Xdata', {split(x1, pl_split), split(x2, pl_split), split(x3, pl_split)})); % Plot (compare data with fit) iplot(y, yfit1, yfit2, plist('Linestyles', {'-','--'}))