Mercurial > hg > ltpda
view m-toolbox/test/test_matrix_MultiChannelNoise.m @ 52:daf4eab1a51e database-connection-manager tip
Fix. Default password should be [] not an empty string
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 07 Dec 2011 17:29:47 +0100 |
parents | f0afece42f48 |
children |
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % TEST matrix/MultiChannelNoise % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % HISTORY: 23-04-2009 L Ferraioli % Creation %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% VERSION '$Id: test_matrix_fromCSD.m,v 1.3 2009/04/23 16:03:55 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 - 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 - 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 - symbolic precision All pass % plist for noise generation plns = plist(... 'csd', mod2D, ... 'targetobj', 'parfrac', ... 'MaxIter', 70, ... 'PoleType', 3, ... 'MinOrder', 25, ... 'MaxOrder', 40, ... 'Weights', 2, ... 'Plot', false,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-4,... 'UseSym', 'on'); na = matrix(plns); %% Check response na11 = resp(na.objs(1,1),plist('f',f,'bank','parallel')); na12 = resp(na.objs(1,2),plist('f',f,'bank','parallel')); na21 = resp(na.objs(2,1),plist('f',f,'bank','parallel')); na22 = resp(na.objs(2,2),plist('f',f,'bank','parallel')); mna = matrix([na11 na12;na21 na22]); ECSD = mna*conj(transpose(mna)); iplot(csd11,ECSD.objs(1,1)) iplot(csd12,ECSD.objs(1,2)) iplot(csd22,ECSD.objs(2,2)) %% 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', 40, ... 'Weights', 2, ... 'Plot', false,... 'MSEVARTOL', 1e-1,... 'FITTOL', 1e-4,... '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,ECSD.objs(1,1)) iplot(csd12,ECSD.objs(1,2)) iplot(csd22,ECSD.objs(2,2)) %% %-------------------------------------------------------------------------- % 2 Dimensional Noise Generation %-------------------------------------------------------------------------- plng = plist('model',na,... 'Nsecs',2e5,... 'fs',fs); no = matrix(plng); %% Check psd no1 = no.objs(1); no2 = no.objs(2); no1xx = no1.psd; no2xx = no2.psd; iplot(no1xx,csd11,no2xx,csd22) %% Check cross-coherence coh = csd12./sqrt(csd11.*csd22); rcoh = real(coh); icoh = imag(coh); no12xx = cpsd(no1,no2,plist('nfft',1e4)); no1xx = no1.psd(plist('nfft',1e4)); no2xx = no2.psd(plist('nfft',1e4)); ecoh = no12xx./(sqrt(no1xx.*no2xx)); recoh = real(ecoh); iecoh = imag(ecoh); iplot(recoh,rcoh,plist('Yscales',{'All','lin'})) iplot(iecoh,icoh,plist('Yscales',{'All','lin'}))