Mercurial > hg > ltpda
view m-toolbox/test/test_matrix_fromCSD.m @ 8:2f5c9bd7d95d database-connection-manager
Clarify ltpda_uo.retrieve parameters handling
| author | Daniele Nicolodi <nicolodi@science.unitn.it> |
|---|---|
| date | Mon, 05 Dec 2011 16:20:06 +0100 |
| parents | f0afece42f48 |
| children |
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % TEST matrix/fromCSD % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % HISTORY: 23-04-2009 L Ferraioli % Creation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% VERSION '$Id: test_matrix_fromCSD.m,v 1.3 2009/11/06 17:00:30 luigi Exp $'; %% Loading spectra load ..\m-toolbox\test\mpsd.mat % load mpsd.mat first column is f then psd1, csd and psd2 f = mpsd(:,1); psd = mpsd(:,2); fs = 10; % 1dim model mod1D = ao(plist('xvals', f, 'yvals', psd, 'fs', fs, 'dtype', 'fsdata','description','MDC1 IFO CH1')); mod1D.setName; % 2dim model csd11 = ao(plist('xvals', f, 'yvals', mpsd(:,2), 'fs', fs, 'dtype', 'fsdata','description','MDC1 IFO CH1 PSD')); csd11.setName; csd12 = ao(plist('xvals', f, 'yvals', mpsd(:,3), 'fs', fs, 'dtype', 'fsdata','description','MDC1 IFO CH12 CSD')); csd12.setName; csd21 = ao(plist('xvals', f, 'yvals', conj(mpsd(:,3)), 'fs', fs, 'dtype', 'fsdata','description','MDC1 IFO CH21 CSD')); csd21.setName; csd22 = ao(plist('xvals', f, 'yvals', mpsd(:,4), 'fs', fs, 'dtype', 'fsdata','description','MDC1 IFO CH2 PSD')); csd22.setName; mod2D = [csd11 csd12;csd21 csd22]; %% %-------------------------------------------------------------------------- % 1 Dimensional Noisegen Filter %-------------------------------------------------------------------------- %% 1 dim noisegen filter in s domain - double precision All pass % plist for noise generation plns = plist(... 'csd', mod1D, ... 'targetobj', 'parfrac', ... 'Nsecs', 1e4, ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 10, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'off'); na = matrix(plns); %% 1 dim noisegen filter in s domain - symbolic precision All pass % plist for noise generation plns = plist(... 'csd', mod1D, ... 'targetobj', 'parfrac', ... 'Nsecs', 1e4, ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 15, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'on'); na = matrix(plns); %% 1 dim noisegen filter in z domain - double precision All pass % plist for noise generation plns = plist(... 'csd', mod1D, ... 'targetobj', 'miir', ... 'Nsecs', 1e4, ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 10, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'off'); na = matrix(plns); %% 1 dim noisegen filter in z domain - symbolic precision All pass % plist for noise generation plns = plist(... 'csd', mod1D, ... 'targetobj', 'miir', ... 'Nsecs', 1e4, ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 10, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'on'); na = matrix(plns); %% %-------------------------------------------------------------------------- % 2 Dimensional Noisegen Filter %-------------------------------------------------------------------------- %% 2 dim noisegen filter in s domain - double precision All pass % plist for noise generation plns = plist(... 'csd', mod2D, ... 'targetobj', 'parfrac', ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 20, ... 'MaxOrder', 40, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'off'); na = matrix(plns); %% 2 dim noisegen filter in s domain - symbolic precision All pass % plist for noise generation plns = plist(... 'csd', mod2D, ... 'targetobj', 'parfrac', ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 20, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'on'); na = matrix(plns); %% Check response na11 = resp(na.objs(1,1),plist('f',f)); na12 = resp(na.objs(1,2),plist('f',f)); na21 = resp(na.objs(2,1),plist('f',f)); na22 = resp(na.objs(2,2),plist('f',f)); est_csd11 = na11.*conj(na11) + na12.*conj(na12); est_csd11.setName; est_csd12 = na11.*conj(na21) + na12.*conj(na22); est_csd12.setName; est_csd22 = na12.*conj(na12) + na22.*conj(na22); est_csd22.setName; iplot(csd11,est_csd11) iplot(csd12,est_csd12) iplot(csd22,est_csd22) %% 2 dim noisegen filter in z domain - double precision All pass % plist for noise generation plns = plist(... 'csd', mod2D, ... 'targetobj', 'miir', ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 25, ... 'MaxOrder', 30, ... 'Weights', 2, ... 'Plot', true,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-3,... 'UseSym', 'off'); na = matrix(plns); %% 2 dim noisegen filter in z domain - symbolic precision All pass % plist for noise generation plns = plist(... 'csd', mod2D, ... 'targetobj', 'miir', ... 'fs', fs, ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 25, ... 'MaxOrder', 35, ... 'Weights', 2, ... 'Plot', false,... 'MSEVARTOL', 1e-1,... 'FITTOL', 1e-3,... 'UseSym', 'on'); na = matrix(plns); %% Check response na11 = resp(na.objs(1,1).filters,plist('f',f,'bank','parallel')); na12 = resp(na.objs(1,2).filters,plist('f',f,'bank','parallel')); na21 = resp(na.objs(2,1).filters,plist('f',f,'bank','parallel')); na22 = resp(na.objs(2,2).filters,plist('f',f,'bank','parallel')); mna = matrix([na11 na12;na21 na22]); ECSD = mna*conj(transpose(mna)); iplot(csd11,(2/fs).*ECSD.objs(1,1)) iplot(csd12,(2/fs).*ECSD.objs(1,2)) iplot(csd22,(2/fs).*ECSD.objs(2,2))