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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 for ao/linlsq % % 17-11-2009 L Ferraioli % CREATION % % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % $Id: mdc3_exp3_loop_v3.m,v 1.2 2009/09/24 09:48:12 luigi Exp $ %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Loading data fprintf('===== loading data... =====\n') % laod parnames and values load C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Models\parnames_10perc.mat load C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Models\exp3_2_10perc_nomvalues.mat load C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Models\exp3_2_10perc_truevalues.mat % load C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Models\usedparams_10perc.mat % set ordered used parameters usedparams = {'dH','dsH','dS11','dS1D','dSD1','dSDD',... 'dh2','dsh2','dx1','dx2'}; [nonfitparnms,ia,ib] = setxor(parnames,usedparams); nonfitparvals = exp3_nomvalues(ia); %% get non-linear response model % the model is non-linear in the parameter dependence fprintf('===== Get TF Model... =====\n') H = matrix(plist('built-in','mdc3_ifo2ifo_v2')); %% load input signal % those are the same of exp 1 fprintf('===== Loading input signals... =====\n') oi1 = ao('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\signals_noise\exp1_1_oi1.mat'); oi1.setName; oi1.setYunits('m'); oid = ao('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\signals_noise\exp1_2_oid.mat'); oid.setName; oid.setYunits('m'); %% get signals - true values fprintf('===== get true values... =====\n') % get response with true params for ii = 1:numel(H.objs) H.objs(ii).setParams(parnames,exp3_truevalues); end plfft = plist('Npad',[]); s11 = fftfilt(oi1,H.objs(1,1),plfft); s12 = fftfilt(oid,H.objs(1,2),plfft); s21 = fftfilt(oi1,H.objs(2,1),plfft); s22 = fftfilt(oid,H.objs(2,2),plfft); % get signals for exp 3.1 s1_exp_3_1 = s11; s1_exp_3_1.setName; sd_exp_3_1 = s21; sd_exp_3_1.setName; % get signals for exp 3.2 s1_exp_3_2 = s12; s1_exp_3_2.setName; sd_exp_3_2 = s22; sd_exp_3_2.setName; %% load Coloring filters fprintf('===== loading coloring filters... =====\n') cf11 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_CF11.mat'); cf11.setName; cf12 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_CF12.mat'); cf12.setName; cf21 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_CF21.mat'); cf21.setName; cf22 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_CF22.mat'); cf22.setName; %% load Whitening filters fprintf('===== loading whitening filters... =====\n') wf11 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_WF11.mat'); wf11.setName; wf12 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_WF12.mat'); wf12.setName; wf21 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_WF21.mat'); wf21.setName; wf22 = miir('C:\Users\Luigi\ltp_data_analysis\MDCs\MDC3\lf_analysis\Filters\exp1_WF22.mat'); wf22.setName; %% Adding noise to signals fprintf('===== adding noise to signals... =====\n') % get params Nsecs = s1_exp_3_1.nsecs; fs = s1_exp_3_1.fs; plcf = plist('bank','parallel'); % starting noise generation exp1.1 a1_exp_3_1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs)); a2_exp_3_1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs)); % coloring noise exp 1.1 na1_exp_3_1 = filter(a1_exp_3_1,cf11,plcf) + filter(a2_exp_3_1,cf12,plcf); na2_exp_3_1 = filter(a1_exp_3_1,cf21,plcf) + filter(a2_exp_3_1,cf22,plcf); % starting noise generation exp 1.2 a1_exp_3_2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs)); a2_exp_3_2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs)); % coloring noise exp 1.2 na1_exp_3_2 = filter(a1_exp_3_2,cf11,plcf) + filter(a2_exp_3_2,cf12,plcf); na2_exp_3_2 = filter(a1_exp_3_2,cf21,plcf) + filter(a2_exp_3_2,cf22,plcf); % adding noise to signals o1_exp_3_1 = s1_exp_3_1 + na1_exp_3_1; od_exp_3_1 = sd_exp_3_1 + na2_exp_3_1; o1_exp_3_2 = s1_exp_3_2 + na1_exp_3_2; od_exp_3_2 = sd_exp_3_2 + na2_exp_3_2; % %% % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % %%%%% Test on one dimensional data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % %% Build input collection % % H11 = H.objs(1,1); % H11.setParams(parnames,exp3_nomvalues); % % subs for non fit parameters % H11.subs(plist('Params', nonfitparnms, 'Values',nonfitparvals)); % % linearize % dH11 = linearize(H11); % % H22 = H.objs(2,2); % H22.setParams(parnames,exp3_nomvalues); % % subs for non fit parameters % H22.subs(plist('Params', nonfitparnms, 'Values',nonfitparvals)); % % linearize % dH22 = linearize(H22); % % %% % iC1 = collection(o1_exp_3_1,s1_exp_3_1,H11,dH11,wf11); % iC2 = collection(od_exp_3_1,sd_exp_3_1,H22,dH22,wf22); % % oC = linlsq(iC1,iC2,plist('Nloops',3)); %% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%% Test on two dimensional data %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %% Build input collection % empty ao eao = ao(); % subs for non fit parameters for ii=1:numel(H.objs) H.objs(ii).setParams(parnames,exp3_nomvalues); % subs for non fit parameters H.objs(ii).subs(plist('Params', nonfitparnms, 'Values',nonfitparvals)); end % linearize dH = linearize(H); % whitening filter wf11b = filterbank(plist('filters',wf11,'type','parallel')); wf11b.setName('wf11'); wf12b = filterbank(plist('filters',wf12,'type','parallel')); wf12b.setName('wf12'); wf21b = filterbank(plist('filters',wf21,'type','parallel')); wf21b.setName('wf21'); wf22b = filterbank(plist('filters',wf22,'type','parallel')); wf22b.setName('wf22'); WF = matrix(wf11b,wf21b,wf12b,wf22b,plist('shape',[2 2])); % exp_3_1 os1 = matrix(o1_exp_3_1,od_exp_3_1,plist('shape',[2 1])); is1 = matrix(oi1,eao,plist('shape',[2 1])); % exp_3_2 os2 = matrix(o1_exp_3_2,od_exp_3_2,plist('shape',[2 1])); is2 = matrix(eao,oid,plist('shape',[2 1])); iC1 = collection(os1,is1,H,dH,WF); iC2 = collection(os2,is2,H,dH,WF); %% add on ground experiments dS11 = ao(cdata(0)); dS11.setName; dS11.setDy(1e-4); dS1D = ao(cdata(0)); dS1D.setName; dS1D.setDy(1e-3); dSDD = ao(cdata(0)); dSDD.setName; dSDD.setDy(1e-3); %% do fit oC = linlsq(iC1,iC2,dS11,dS1D,dSDD,plist('Nloops',1,'Npad',[]));