Mercurial > hg > ltpda

annotate m-toolbox/classes/@ao/bicohere.m @ 21:8be9deffe989 database-connection-manager

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Update ltpda_uo.update
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % BICOHERE computes the bicoherence of two input time-series
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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 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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4 % DESCRIPTION: BICOHERE computes the bicoherence of two input time-series.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % CALL: bs = bicohere(a1,a2,pl)
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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 % INPUTS: aN - input analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % a1,a2 - input analysis objects array
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % pl - input parameter list
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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 % OUTPUTS: bs - xyz data analysis object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % <a href="matlab:utils.helper.displayMethodInfo('bicohere', 'psd')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % VERSION: $Id: psd.m,v 1.59 2010/12/17 17:45:08 ingo Exp $
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 function varargout = bicohere(varargin)
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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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 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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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 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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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 if numel(as) ~= 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 error('bicohere only works with 2 time-series at the moment.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 end
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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 % Get data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 a = as(1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 b = as(2);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 % same fs?
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 if a.data.fs ~= b.data.fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 error('### Two time-series have different sample rates.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 % Same length vectors?
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 if a.len ~= b.len
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 error('### Two time-series must have same length');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 end
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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 % Combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 pl = combine(pl, getDefaultPlist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 usepl = utils.helper.process_spectral_options(pl, 'lin', a.len, a.fs);
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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 win = find(usepl, 'Win');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 nfft = find(usepl, 'Nfft');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 olap = find(usepl, 'Olap')/100;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 Xolap = round(olap*nfft);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 order = find(usepl, 'order');
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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 fs = a.data.fs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 x = {a.data.y; b.data.y};
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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 [x,M,isreal_x,y,Ly,win,winName,winParam,noverlap,k,L,options] = ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 ao.welchparse(x,'',win.win, Xolap, nfft, fs);
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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 select = 1:(nfft+1)/2;
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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 % loop over segments
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 LminusOverlap = L-noverlap;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 xStart = 1:LminusOverlap:k*LminusOverlap;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 xEnd = xStart+L-1;
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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 m = zeros(length(select), length(select));
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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 for i = 1:k
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 if order < 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 Xseg = x(xStart(i):xEnd(i));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 Yseg = x(xStart(i):xEnd(i));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 [Xseg,coeffs] = ltpda_polyreg(x(xStart(i):xEnd(i)), order);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 [Yseg,coeffs] = ltpda_polyreg(y(xStart(i):xEnd(i)), order);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 end
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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 % window
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 xw = Xseg.*win.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 yw = Yseg.*win.';
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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 % FFT
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 xx2s = fft(xw);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 xx = xx2s(select);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 yy2s = fft(yw);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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100 yy = yy2s(select);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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101
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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102 scalex = abs(xx);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 scaley = abs(yy);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 sc = scalex * scaley';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105 m = m + (xx * yy')./sc;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 m = m./k;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 f = psdfreqvec('npts',nfft,'Fs',fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 f = f(select);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 do = xyzdata(f, f, m);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 do.setXunits('Hz');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 do.setYunits('Hz');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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116 do.setZunits(a.yunits*b.yunits);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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117
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 ma = ao(do);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 ma.setName(sprintf('%s, %s', a.name, b.name));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 ma.addHistory(getInfo('None'), usepl, ao_invars, [a.hist b.hist]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 varargout{1} = ma;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 end
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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>
parents:
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127 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 pl = getDefaultPlist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: psd.m,v 1.59 2010/12/17 17:45:08 ingo Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 % General plist for Welch-based, linearly spaced spectral estimators
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 pl = plist.WELCH_PLIST;
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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>
parents:
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158
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 % END
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161