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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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% A test script for ao/buildWhitener1D % % M Hewitson 10-11-08 % % $Id: test_ao_buildWhitener1D.m,v 1.1 2010/05/04 07:14:17 mauro Exp $ % %% Make test data fs = 10; a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 10000, 'yunits', 'N')); % filter pzm = pzmodel(1e-2, {0.01}, {0.1}); ft = miir(pzm,plist('fs',fs)); af = filter(a, ft); %% rsp = pzm.resp; rsmm = resp(ft,plist('f',logspace(-4,log10(5),100))); iplot(rsp,rsmm) %% pl_psd = plist('scale', 'PSD', 'order', 1, 'navs', 16); axx = a.psd(pl_psd); afxx = af.psd(pl_psd); iplot(axx,afxx) %% Build whitening filter it with no model pl = plist(... 'MaxIter', 30, ... 'PoleType', 1, ... 'MinOrder', 2, ... 'MaxOrder', 9, ... 'Weights', 2, ... 'Plot', false,... 'Disp', false,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-1); % tolerance on MSE Value awf = buildWhitener1D(af, pl); %% Whiten with a model mdl = (abs(rsp).^2).*(2/fs); % this corresponds to the theoretical psd of the data mdl.setYunits(axx.yunits); pl = plist(... 'fs', fs, ... 'MaxIter', 50, ... 'PoleType', 2, ... 'MinOrder', 2, ... 'MaxOrder', 9, ... 'Weights', 2, ... 'Plot', false,... 'Disp', false,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-2); % tolerancee on MSE Value awmf = buildWhitener1D(mdl, pl); %% aw = filter(af, awf); awm = filter(af, awmf); iplot(aw, awm) %% awxx = aw.psd(pl_psd); awmxx = awm.psd(pl_psd); iplot(axx, afxx, awxx, awmxx); %% Testing flatness svec = [axx.data.y afxx.data.y awxx.data.y awmxx.data.y]; fc = utils.math.spflat(svec); %% Working with multiple inputs %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% fs = 10; a1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 10000, 'yunits', 'V')); a2 = ao(plist('tsfcn', 'randn(size(t)).''', 'fs', fs, 'nsecs', 10000, 'yunits', 'T')); % filter pzm = pzmodel(1e-2, {0.01}, {0.1}); ft = miir(pzm,plist('fs',fs)); af1 = filter(a1, ft); af2 = filter(a2, ft); pl = plist(... 'MaxIter', 30, ... 'PoleType', 2, ... 'MinOrder', 2, ... 'MaxOrder', 9, ... 'Weights', 2, ... 'Plot', false,... 'Disp', false,... 'MSEVARTOL', 1e-2,... 'FITTOL', 1e-2); % tolerance on fit residuals spectral flatness [awf1,awf2] = buildWhitener1D(af1,af2,pl); %% iplot(filter(af1, awf1),filter(af2, awf2)) %% help test % Generate white noise fs = 1; a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', 1e5, 'yunits','m')); % filter ft = miir(plist('type','bandpass','order',3,'gain',1,'fc',[0.03 0.1],'fs',fs)); % coloring white noise af = filter(a, ft); % Whitening colored noise pl = plist(... 'MaxIter', 30, ... 'PoleType', 2, ... 'MinOrder', 9, ... 'MaxOrder', 15, ... 'Weights', 2, ... 'Plot', false,... 'Disp', false,... 'MSEVARTOL', 1e-1,... 'FITTOL', 5e-2); % tolerance on fit residuals spectral flatness aw = buildWhitener1D(af,pl); % Calculate psd of colored and whitened data afxx = af.psd; awxx = af.filter(aw).psd; % plotting iplot(afxx,awxx) % END