annotate m-toolbox/test/test_ao_zDomainFit_3.m @ 21:8be9deffe989 database-connection-manager

Update ltpda_uo.update
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % Test script for zDomainFit on noisy data
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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 % L. Ferraioli 02-12-08
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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 % $Id: test_ao_zDomainFit_3.m,v 1.3 2009/04/20 14:31:14 luigi Exp $
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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 %
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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 % Smooth psd model
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % We define a smooth psd model and generate colored noise with such a psd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % shape. Then we fit sqrt(psd) of noisy data following two different
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % procedure to decide when the fit is satisfactory and we can exit from the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % fitting routine.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % The first procedure is based on the check of residuals spectral flatness.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % The second procedure is based on the check of residuals log distance to
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % fitted data.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 %% Useful constants
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 fs = 10; % sampling frequency Hz
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 Nsecs = 1e5; % Number of seconds in the data stream
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 Nfft = 1e4; % Number of samples in the fft
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 pls = plist('Nfft', Nfft,'Order',0); % plist for spectra
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 %% Building a frequency response AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % Create a frequency-series AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % pl_data = plist('fsfcn', '0.01./(0.01+f)', 'f1', 1e-6, 'f2', 5, 'nf', 1000);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 pl_data = plist('fsfcn', '(1e-3./(f).^2 + 1e3./(0.001+f) + 1e5.*f.^2).*1e-10', 'f1', 1e-6, 'f2', 5, 'nf', 300);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 mod = ao(pl_data);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 mod.setName('psd model');
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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(mod)
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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 %% Building white noise
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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 a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 a.setName('white noise')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 a.setYunits('m')
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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 %% Calling the noise generator
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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 'model', mod, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 'MaxIter', 50, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 'PoleType', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 'MinOrder', 15, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 'MaxOrder', 25, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 'Weights', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 'Plot', false,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 'Disp', false,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 'RMSEVar', 8,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 'FitTolerance', 2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 ac = noisegen1D(a, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 %% Spetrum and Transfer function
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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 acxx = ac.psd(pls); % spectrum of data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 etf = tfe(a,ac,pls); % calculating transfer functions from data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 iplot(acxx)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 iplot(etf(1,2))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 %% Fitting Sqrt Spectrum - Residuals spectral flatness checking
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 % Fitting parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 pl_fit1 = plist('FS',fs,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 'AutoSearch','on',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 'StartPoles',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 'StartPolesOpt','c2',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 'maxiter',60,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 'minorder',19,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 'maxorder',25,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 'weights',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 'weightparam','abs',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 'ResLogDiff',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 'ResFlat',0.7,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 'RMSE',5,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 'Plot','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 'ForceStability','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 'CheckProgress','on');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 % Do fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 [filt2,bsp1,bspres1,bsprmse1] = zDomainFit(sqrt(acxx./2), pl_fit1); % division by 2 is necessary because acxx is the one-sided psd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 bsp1.setName('Fit1');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 %% Checing spectral flatness
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 % checking the spectral flatness of the normalized residuals in order to be
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 % sure that the procedure works correctly
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 kk = abs(bspres1./bsp1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 rf = utils.math.spflat(kk.data.y);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 iplot(abs(bspres1./bsp1))
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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 %% Fitting Spectrum - Residuals log difference checking
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 % Fitting parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 pl_fit2 = plist('FS',fs,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 'AutoSearch','on',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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101 'StartPoles',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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102 'StartPolesOpt','c2',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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103 'maxiter',60,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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104 'minorder',17,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105 'maxorder',20,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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106 'weights',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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107 'weightparam','abs',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108 'ResLogDiff',0.5,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 'ResFlat',0.7,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 'RMSE',5,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 'Plot','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 'ForceStability','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 'CheckProgress','on');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 % Do fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 [filt2,bsp2,bspres2,bsprmse2] = zDomainFit(sqrt(acxx./2), pl_fit2); % division by 2 is necessary because acxx is the one-sided psd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 bsp2.setName('Fit2');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 %% Model calculated at the same frequencies of the fit AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 % This step is useful in order to compare the results of the two fitting
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 % procedures
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 f = acxx.data.x;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 pl_datar = plist('fsfcn', '(1e-3./(f).^2 + 1e3./(0.001+f) + 1e5.*f.^2).*1e-10', 'f', f);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 modr = ao(pl_datar);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 modr.setName('psd model');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 %% Checking the two fit results
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 % plot the normalized difference between fit results and model data in
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 % order to check the fit accuracy
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 plpl = plist('Legends',{'Fit1','Fit2'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 iplot(abs(bsp1-sqrt(modr))./sqrt(modr),abs(bsp2-sqrt(modr))./sqrt(modr),plpl)
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 % Peaked psd model
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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>
parents:
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139 % We define a psd model with some resonance peaks and generate colored
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 % noise with such a psd shape. Then we fit sqrt(psd) of noisy data
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 % following two different procedure to decide when the fit is satisfactory
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 % and we can exit from the fitting routine.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 % The first procedure is based on the check of residuals spectral flatness.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 % The second procedure is based on the check of residuals log distance to
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 % fitted data.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 %% Building a frequency response AO
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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 % Create a psd model with two peak resonance at 5e-2 and 7e-2 Hz
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 func = '(1e-3./(f).^2 + 1e3./(0.001+f) + 1e5.*f.^2).*1e-10 + 1e-6./((f./7e-2).^2-1).^2 + 1e-5./((f./5e-2).^2-1).^2';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 pl_data = plist('fsfcn', func, 'f1', 1e-6, 'f2', 5, 'nf', 300);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 mod = ao(pl_data);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154 mod.setName('psd model');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 iplot(mod)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 %% Building white noise
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 a = ao(plist('tsfcn', 'randn(size(t))', 'fs', fs, 'nsecs', Nsecs, 'yunits', 'm'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161 a.setName('white noise')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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162
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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163 %% Calling the noise generator
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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164
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165 pl = plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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166 'model', mod, ... % Multiplication by fs needed to preserve energy
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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167 'MaxIter', 70, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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168 'PoleType', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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169 'MinOrder', 30, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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170 'MaxOrder', 45, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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171 'Weights', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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172 'Plot', false,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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173 'Disp', false,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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174 'RMSEVar', 8,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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175 'FitTolerance', 2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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176
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Daniele Nicolodi <nicolodi@science.unitn.it>
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177 ac = noisegen1D(a, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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178
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Daniele Nicolodi <nicolodi@science.unitn.it>
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179 %% Spetrum and Transfer function
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Daniele Nicolodi <nicolodi@science.unitn.it>
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180
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Daniele Nicolodi <nicolodi@science.unitn.it>
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181 acxx = ac.psd(pls); % spectrum of data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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182
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Daniele Nicolodi <nicolodi@science.unitn.it>
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183 iplot(acxx)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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184
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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185 %% Fitting Sqrt Spectrum - Residuals spectral flatness checking
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Daniele Nicolodi <nicolodi@science.unitn.it>
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186
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Daniele Nicolodi <nicolodi@science.unitn.it>
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187 % Fitting parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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188 pl_fit1 = plist('FS',fs,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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189 'AutoSearch','on',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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190 'StartPoles',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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191 'StartPolesOpt','c2',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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192 'maxiter',60,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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193 'minorder',15,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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194 'maxorder',25,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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195 'weights',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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196 'weightparam','abs',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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197 'ResLogDiff',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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198 'ResFlat',0.7,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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199 'RMSE',6,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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200 'Plot','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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201 'ForceStability','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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202 'CheckProgress','on');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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203
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Daniele Nicolodi <nicolodi@science.unitn.it>
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204 % Do fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
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205 [filt1,bsp1,bspres1,bsprmse1] = zDomainFit(sqrt(acxx./2), pl_fit1); % division by 2 is necessary because acxx is the one-sided psd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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206 bsp1.setName('Fit1');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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207
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Daniele Nicolodi <nicolodi@science.unitn.it>
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208 %%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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209
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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210 iplot(sqrt(acxx./2),bsp1)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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211
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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212 %% Checing spectral flatness
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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213 % checking the spectral flatness of the normalized residuals in order to be
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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214 % sure that the procedure works correctly
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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215 kk = abs(bspres1./bsp1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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216 rf = utils.math.spflat(kk.data.y);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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217 iplot(abs(bspres1./bsp1))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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218
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Daniele Nicolodi <nicolodi@science.unitn.it>
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219 %% Fitting Spectrum - Residuals log difference checking
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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220
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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221 % Fitting parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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222 pl_fit2 = plist('FS',fs,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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223 'AutoSearch','on',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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224 'StartPoles',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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225 'StartPolesOpt','c2',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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226 'maxiter',60,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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227 'minorder',15,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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228 'maxorder',25,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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229 'weights',[],...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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230 'weightparam','abs',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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231 'ResLogDiff',0.5,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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232 'ResFlat',0.7,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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233 'RMSE',6,...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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234 'Plot','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235 'ForceStability','off',...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 'CheckProgress','on');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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237
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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238 % Do fit
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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239 [filt2,bsp2,bspres2,bsprmse2] = zDomainFit(sqrt(acxx./2), pl_fit2); % division by 2 is necessary because acxx is the one-sided psd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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240 bsp2.setName('Fit2');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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241
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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242 %%
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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243
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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244 iplot(sqrt(acxx./2),bsp2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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245
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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246 %% Model calculated at the same frequencies of the fit AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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247
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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248 % This step is useful in order to compare the results of the two fitting
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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249 % procedures
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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250 f = acxx.data.x;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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251 func = '(1e-3./(f).^2 + 1e3./(0.001+f) + 1e5.*f.^2).*1e-10 + 1e-6./((f./7e-2).^2-1).^2 + 1e-5./((f./5e-2).^2-1).^2';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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252 pl_datar = plist('fsfcn', func, 'f', f);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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253 modr = ao(pl_datar);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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254 modr.setName('psd model');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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255
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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256 %% Checking the two fit results
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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257 % plot the normalized difference between fit results and model data in
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 % order to check the fit accuracy
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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259 plpl = plist('Legends',{'Fit1','Fit2'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260 iplot(abs(bsp1-sqrt(modr))./sqrt(modr),abs(bsp2-sqrt(modr))./sqrt(modr),plpl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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261