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annotate m-toolbox/test/test_ao_noisegen2D_mdc2.m @ 0:f0afece42f48

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % A test script for ao/noisegen2D
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 % DESCRIPTION: Run noisegen2D with mdc2 models and test procedure accuracy
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % L. Ferraioli 04-02-2009
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % $Id: test_ao_noisegen2D_mdc2.m,v 1.3 2009/02/19 17:46:41 luigi Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 %% General use variables and vectors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 f = logspace(-6,log10(5),300);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 fs = 10;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 Nsecs = 1e5; % number of seconds
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 Nfft = 1e5; % number of samples for the fft
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 pls = plist('Nfft', Nfft,'Order',0); % plist for spectra
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 %% MDC2 Models
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 b = ao(plist('built-in','mdc2r2_fd_ltpnoise','f1',1e-6,'f2',5,'nf',300));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 CSD = [b(1) b(2);conj(b(2)) b(3)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 %% Make white noise
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 a1 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 a2 = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 a1.setYunits('m');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 a2.setYunits('m');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 a = [a1 a2];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 % axx = a.cpsd(pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 %%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 iplot(a)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 %% some ploting
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 iplot(axx)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 iplot(CSD(1,1),CSD(1,2),CSD(2,1),CSD(2,2))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 %% Noise generation
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 pl = plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 'csd11', CSD(1,1), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 'csd12', CSD(1,2), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 'csd21', CSD(2,1), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 'csd22', CSD(2,2), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 'MaxIter', 80, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 'PoleType', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 'MinOrder', 35, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 'MaxOrder', 40, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 'Weights', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 'Plot', false,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 'FitTolerance', 2,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 'RMSEVar', 7,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 'UseSym', 0,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 'Disp', false);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 ac = noisegen2D(a, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 %% Checking results and starting data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 % iplot(a)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 iplot(ac)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 %% Making cross-spectrum
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 acxx = ac.cpsd(pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 acch = ac.cohere(pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 %% Plotting spectra
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 % iplot(acxx);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 iplot(abs(acxx(1,1)),abs(CSD(1,1))) % model data need to be multiplied by 2 because acxx is the onesided cpsd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 iplot(abs(acxx(1,2)),abs(CSD(1,2)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 iplot(abs(acxx(2,2)),abs(CSD(2,2)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 iplot(abs(acxx(1,1)),abs(acxx(1,2)),abs(acxx(2,2)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 %% Plotting coherence
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 iplot(acch(2,1),(abs(CSD(1,2)).^2)./(CSD(1,1).*CSD(2,2)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 %%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 m1=mean(acxx(2,2).data.y(end-10,end)) % calculate average on the tail of channel 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 m2=mean(CSD(2,2).data.y(end-5,end))% calculate average on the tail of channel 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 m1/m2 % verify that the ratio is near 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 %%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 % ************************************************************************
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 % Some more analysis for testing the accuracy of noise generation procedure
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % ************************************************************************
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 %% Extracting filters from data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 Filt11 = find(ac(1).procinfo,'Filt11');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 Filt12 = find(ac(1).procinfo,'Filt12');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 Filt21 = find(ac(2).procinfo,'Filt21');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 Filt22 = find(ac(2).procinfo,'Filt22');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 %% Calculating filters responses
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 tr11 = resp(Filt11,plist('f',f));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 rFilt11 = tr11(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 for ii = 2:numel(tr11)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 rFilt11 = rFilt11 + tr11(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 rFilt11.setName('rFilt11', 'internal');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 tr12 = resp(Filt12,plist('f',f));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 rFilt12 = tr12(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 for ii = 2:numel(tr12)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 rFilt12 = rFilt12 + tr12(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 rFilt12.setName('rFilt12', 'internal');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 tr21 = resp(Filt21,plist('f',f));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 rFilt21 = tr21(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 for ii = 2:numel(tr21)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 rFilt21 = rFilt21 + tr21(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 rFilt21.setName('rFilt21', 'internal');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 tr22 = resp(Filt22,plist('f',f));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 rFilt22 = tr22(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 for ii = 2:numel(tr22)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 rFilt22 = rFilt22 + tr22(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 rFilt22.setName('rFilt22', 'internal');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 %% Obtaining transfer functions
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 % calculating transfer functions from data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 etf = tfe(a,ac,pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 %% Comparing Filters Responses with estimated TFs (e-TFs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 % Comparing filters responses and calculated TFs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 pl = plist('Legends', {'Filter Response','e-TF'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 iplot(rFilt11,etf(1,3),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144 iplot(rFilt12,etf(2,3),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 iplot(rFilt21,etf(1,4),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 iplot(rFilt22,etf(2,4),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 %% Filtering data separately
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150 % This operation is performed internally to the noisegen2D. Output data are
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 % then obtained by b1 = b11 + b12 and b2 = b21 + b22
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 b11 = filter(a1,plist('filter',Filt11,'bank','parallel'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 b12 = filter(a2,plist('filter',Filt12,'bank','parallel'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154 b21 = filter(a1,plist('filter',Filt21,'bank','parallel'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 b22 = filter(a2,plist('filter',Filt22,'bank','parallel'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 %% Extracting transfer functions from separately filtered data se-TFs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 etf11 = tfe(a1,b11,pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 etf12 = tfe(a2,b12,pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
161 etf21 = tfe(a1,b21,pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
162 etf22 = tfe(a2,b22,pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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163
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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164 %% Comparing separately-estimated TFs (se-TFs) with filter responses
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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166 pl = plist('Legends', {'Filter Response','se-TF'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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167 iplot(rFilt11,etf11(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 iplot(rFilt12,etf12(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 iplot(rFilt21,etf21(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 iplot(rFilt22,etf22(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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172 %% Comparing filters with TFs obtained by eigendecomposition
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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173
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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174 % This function output transfer functions as they are obtained by the
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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175 % eigendecomposition process. i.e. before the fitting process
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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176
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177 icsd11 = CSD(1,1).data.y*fs/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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178 icsd12 = CSD(1,2).data.y*fs/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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179 icsd21 = CSD(2,1).data.y*fs/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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180 icsd22 = CSD(2,2).data.y*fs/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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181
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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182 [tf11,tf12,tf21,tf22] = utils.math.eigcsd(icsd11,icsd12,icsd21,icsd22,'USESYM',0,'DIG',50,'OTP','TF');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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183
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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184 % Making AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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185 eigtf11 = ao(fsdata(f,tf11,fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 eigtf12 = ao(fsdata(f,tf12,fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 eigtf21 = ao(fsdata(f,tf21,fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 eigtf22 = ao(fsdata(f,tf22,fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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190 %% Comparing eig-TFs with output filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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191
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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192 % Compare TFs before and after the fitting process
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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193
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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194 pl = plist('Legends', {'eig-TF','Filter Response'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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195 iplot(eigtf11,rFilt11,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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196 iplot(eigtf12,rFilt12,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 iplot(eigtf21,rFilt21,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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198 iplot(eigtf22,rFilt22,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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199
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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200 %% Phase difference between eig-TFs and output filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 % checking that phase differences between TFs are preserved by the fitting
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 % process
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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204 eigph1 = unwrap(angle(eigtf11)-angle(eigtf21));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 eigph1.setYunits('rad')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 filtph1 = unwrap(angle(rFilt11)-angle(rFilt21));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 filtph1.setYunits('rad')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 eigph2 = unwrap(angle(eigtf22)-angle(eigtf12));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 eigph2.setYunits('rad')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 filtph2 = unwrap(angle(rFilt22)-angle(rFilt12));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 filtph2.setYunits('rad')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 pl = plist('Legends',{'eig-TF','Filter'},'YScales',{'All','lin'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 iplot(eigph1+2*pi,filtph1,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 iplot(eigph2,filtph2,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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218 %% Comparing eig-TFs with se-TFs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 % Compare eigendecomposition results with separately estimated TFs (se-TFs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 pl = plist('Legends', {'eig-TF','se-TF'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 iplot(eigtf11,etf11(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 iplot(eigtf12,etf12(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 iplot(eigtf21,etf21(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 iplot(eigtf22,etf22(1,2),pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 %% Phase difference between eig-TFs and se-TFs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 % checking that phase differences between TFs are preserved by the fitting
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 % process also for the filtered data (se-TFs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 eigph1 = unwrap(angle(eigtf11)-angle(eigtf21));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 filtph1 = unwrap(angle(etf11(1,2))-angle(etf21(1,2)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 eigph2 = unwrap(angle(eigtf22)-angle(eigtf12));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 filtph2 = unwrap(angle(etf22(1,2))-angle(etf12(1,2)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 pl = plist('Legends',{'eig-TF \Delta\phi','se-TF \Delta\phi'},'YScales',{'All','lin'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 iplot(eigph1,filtph1,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238 iplot(eigph2,filtph2,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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240 % END