annotate m-toolbox/test/test_ao_smoother.m @ 38:3aef676a1b20 database-connection-manager

Keep backtrace on error
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % TEST_AO_SMOOTHER a test function the AO method smoother.
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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 % M Hewitson 02-03-08
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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_smoother.m,v 1.8 2009/02/02 15:20:38 hewitson 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 function test_ao_smoother
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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 % ------------- Frequency data smoothing ---------------------------------
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % Make some test data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 nsecs = 5000;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 fs = 10;
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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 p1 = pz(0.01, 1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 z1 = pz(0.2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 gain =1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 pzm = pzmodel(gain, p1, z1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % calling the noisegenerator
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 a1 = fngen(pzm, plist('Nsecs', nsecs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 a1.setYunits('V');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 a1.setXunits('s');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 a1.setName('noise');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 a2 = ao(plist('tsfcn', '0.003.*sin(2*pi*0.65*t) + 0.001.*sin(2*pi*3*t)', 'fs', a1.data.fs, 'nsecs', nsecs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 a2.setName('signal');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 a3 = a1 + a2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 % parameter list for lpsd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 pl = plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 'Kdes', 100, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 'Kmin', 2, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 'Jdes', 500, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 'Win', specwin('Kaiser', 10, 150), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 'Order', 1);
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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 % Make spectrum
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 a3xx = psd(a3, plist('Nfft', 1000*fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42
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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 % Median Smooth both
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 pl = plist('width', 100, 'hc', 0.7, 'method', 'median');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 a3s = smoother(a3, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 pl = plist('width', 30, 'hc', 0.8, 'method', 'median');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 a3xxs = smoother(a3xx, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 % Plot
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 pl = plist('Legends', {'', 'median'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 iplot(a3, a3s, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 iplot(a3xx, a3xxs, pl)
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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 % Mean smooth
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 pl = plist('width', 100, 'hc', 0.7, 'method', 'mean');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 a3s = smoother(a3, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 pl = plist('width', 20, 'hc', 0.8, 'method', 'mean');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 a3xxs = smoother(a3xx, pl);
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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 % Plot
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 pl = plist('Legends', {'', 'mean'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 iplot(a3, a3s, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 iplot(a3xx, a3xxs, pl)
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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 % Max smooth
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 pl = plist('width', 1000, 'hc', 0.7, 'method', 'max');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 a3s = smoother(a3, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 pl = plist('width', 20, 'hc', 0.8, 'method', 'max');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 a3xxs = smoother(a3xx, pl);
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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 % Plot
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 pl = plist('Legends', {'', 'max'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 iplot(a3, a3s, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 iplot(a3xx, a3xxs, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 % Min smooth
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 pl = plist('width', 1000, 'hc', 0.7, 'method', 'min');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 a3s = smoother(a3, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 pl = plist('width', 20, 'hc', 0.8, 'method', 'min');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 a3xxs = smoother(a3xx, pl);
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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 % Plot
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 pl = plist('Legends', {'', 'min'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 iplot(a3, a3s, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 iplot(a3xx, a3xxs, pl)
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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 % Mode smooth
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 pl = plist('width', 1000, 'hc', 0.7, 'method', 'mode');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 a3s = smoother(a3, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 pl = plist('width', 20, 'hc', 0.8, 'method', 'mode');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 a3xxs = smoother(a3xx, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 % Plot
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 pl = plist('Legends', {'', 'mode'});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 iplot(a3, a3s, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 iplot(a3xx, a3xxs, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104
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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 end