annotate m-toolbox/classes/@ao/whiten2D.m @ 0:f0afece42f48

Import.
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % WHITEN2D whiten the noise for two cross correlated 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>
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4 % DESCRIPTION: whiten2D whitens cross-correlated time-series. Whitening
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % filters are constructed by a fitting procedure to the cross-spectrum
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % models provided.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % Note: The function assumes that the input model corresponds to the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % one-sided csd of the data to be whitened.
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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 % ALGORITHM:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % 1) Fit a set of partial fraction z-domain filters using
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % utils.math.psd2wf
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % 2) Convert to bank of mIIR filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % 3) Filter time-series in parallel
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % The filtering process is:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % b(1) = Filt11(a(1)) + Filt12(a(2))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % b(2) = Filt21(a(1)) + Filt22(a(2))
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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 % CALL: b = whiten2D(a, pl) % returns whitened time-series AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % [b1,b2] = whiten2D(a1, a2, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % [b1,b2,...,bn] = whiten2D(a1,a2,...,an, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % Note: Input AOs must come in couples.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % Note: this method cannot be used as a modifier, the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % call a.whiten2D(pl) is forbidden.
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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 % INPUT:
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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 % - a is a couple of two colored noise time-series AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % OUTPUT:
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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 % - b is a couple of "whitened" time-series AOs. The whitening
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % filters used are stored in the objects procinfo field under
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % the parameters:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % - b(1): 'Filt11' and 'Filt12'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 % - b(2): 'Filt21' and 'Filt22'
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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 href="matlab:utils.helper.displayMethodInfo('ao', 'whiten2D')">Parameters Description</a>
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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 % VERSION: $Id: whiten2D.m,v 1.35 2011/04/08 08:56:16 hewitson Exp $
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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 function varargout = whiten2D(varargin)
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 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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54
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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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 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 [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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61 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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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 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 cs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 inhists = [as.hist];
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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 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 pl = parse(pl, getDefaultPlist());
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 pl.getSetRandState();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 % Extract necessary model parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 csd11 = find(pl, 'csd11');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 csd12 = find(pl, 'csd12');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 csd21 = find(pl, 'csd21');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 csd22 = find(pl, 'csd22');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 error('### noisegen2D cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 end
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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 % Check the number of input AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 if numel(bs)==1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 error('!!! One input AO! The input AOs must come in pairs!');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 % Checks that the input AOs come in pairs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 odc = 0;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 if rem(numel(as),2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 warning('The input AOs must come in pairs! Skipping AO %s during calculation', ao_invars{end});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 odc = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 % Loop over input AOs to check for non time series objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 fsv = zeros(numel(bs),1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 for jj=1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 if ~isa(bs(jj).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 error('!!! %s expects ao/tsdata objects. ', mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 fsv(jj,1) = bs(jj).data.fs; % collecting sampling frequencies
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 % Check that input Aos have the same sampling frequency
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 if any(diff(fsv))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 error('!!! Sampling frequency must be the same for all input objects')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 end
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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 % ------------------- Coloring Noise
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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 % ----------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 % 1) - Fitting the models to identify the innovation filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 % Build input structure for psd2tf
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 params = struct();
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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 params.idtp = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 params.Nmaxiter = find(pl, 'MaxIter');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 params.minorder = find(pl, 'MinOrder');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 params.maxorder = find(pl, 'MaxOrder');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 params.spolesopt = find(pl, 'PoleType');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 params.weightparam = find(pl, 'Weights');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 params.usesym = find(pl, 'UseSym');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 params.spy = find(pl, 'Disp');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 params.keepvar = find(pl, 'keepvar');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 % Tolerance for MSE Value
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 lrscond = find(pl, 'FITTOL');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127 % give an error for strange values of lrscond
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 if lrscond<0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 error('!!! Negative values for FITTOL are not allowed !!!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 % handling data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 lrscond = -1*log10(lrscond);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 % give a warning for strange values of lrscond
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 if lrscond<0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 warning('You are searching for a MSE lower than %s', num2str(10^(-1*lrscond)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 params.lrscond = lrscond;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 % Tolerance for the MSE relative variation
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 msevar = find(pl, 'MSEVARTOL');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 % handling data
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 msevar = -1*log10(msevar);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 % give a warning for strange values of msevar
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 if msevar<0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 warning('You are searching for MSE relative variation lower than %s', num2str(10^(-1*msevar)))
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 params.msevar = msevar;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 if isempty(params.msevar)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 params.ctp = 'chival';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 params.ctp = 'chivar';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 end
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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 if(find(pl, 'plot'))
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 params.plot = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 params.plot = 0;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 params.fs = fsv(1,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
162 params.dterm = 0;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
163
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 % get data variance
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 vars = [1 1];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166 if numel(bs)==2
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167 for ii=1:numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 b = bs(ii).y;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
169 v = var(b);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
170 vars(ii) = v;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
171 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
173 params.vars = vars;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
174
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
175 % call psd2wf
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
176 ostruct = utils.math.psd2wf(csd11.y,csd12.y,csd21.y,csd22.y,csd11.x,params);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
177
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
178 % ----------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
179 % 2) - Convert into MIIR filters
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
180
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
181 fs = fsv(1,1);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 % --- filter 1 ---
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
184 res = ostruct(1).res;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
185 poles = ostruct(1).poles;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 dterm = ostruct(1).dterm;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
187 % construct a struct array of miir filters vectors
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
188 pfilts1 = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189 for kk=1:numel(res)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190 ft = miir(res(kk), [ 1 -poles(kk)], fs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
191 pfilts1 = [pfilts1 ft];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
192 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 % pfilts1 = [pfilts1 miir(dterm, [1 0], fs)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 % --- filter 2 ---
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
196 res = ostruct(2).res;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
197 poles = ostruct(2).poles;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198 dterm = ostruct(2).dterm;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 % construct a struct array of miir filters vectors
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 pfilts2 = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 for kk=1:numel(res)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 ft = miir(res(kk), [ 1 -poles(kk)], fs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 pfilts2 = [pfilts2 ft];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 % pfilts2 = [pfilts2 miir(dterm, [1 0], fs)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 % --- filter 3 ---
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 res = ostruct(3).res;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 poles = ostruct(3).poles;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 dterm = ostruct(3).dterm;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211 % construct a struct array of miir filters vectors
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 pfilts3 = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213 for kk=1:numel(res)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 ft = miir(res(kk), [ 1 -poles(kk)], fs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215 pfilts3 = [pfilts3 ft];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 % pfilts3 = [pfilts3 miir(dterm, [1 0], fs)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 % --- filter 4 ---
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 res = ostruct(4).res;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 poles = ostruct(4).poles;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222 dterm = ostruct(4).dterm;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 % construct a struct array of miir filters vectors
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 pfilts4 = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 for kk=1:numel(res)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 ft = miir(res(kk), [ 1 -poles(kk)], fs);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 pfilts4 = [pfilts4 ft];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 % pfilts4 = [pfilts4 miir(dterm, [1 0], fs)];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 % ----------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 % 3) Filtering data
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 for jj = 1:2:numel(bs)-1-odc
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 bs(jj) = filter(cs(jj), pfilts1) + filter(cs(jj+1), pfilts2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 bs(jj+1) = filter(cs(jj), pfilts3) + filter(cs(jj+1), pfilts4);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 % -----------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 % 4) Output data
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242 % name for this object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 bs(jj).name = sprintf('whiten2D(%s)_c1', [ao_invars{jj} ao_invars{jj+1}]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244 % Collect the filters into procinfo
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
245 bs(jj).procinfo = combine(plist('Filt11', pfilts1,'Filt12', pfilts2),as(jj).procinfo);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
246 % add history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
247 bs(jj).addHistory(getInfo('None'), pl, [ao_invars(:)], [inhists(:)]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
248
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
249 % name for this object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
250 bs(jj+1).name = sprintf('whiten2D(%s)_c2', [ao_invars{jj} ao_invars{jj+1}]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
251 % Collect the filters into procinfo
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
252 bs(jj+1).procinfo = combine(plist('Filt21', pfilts3,'Filt22', pfilts4),as(jj+1).procinfo);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
253 % add history
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
254 bs(jj+1).addHistory(getInfo('None'), pl, [ao_invars(:)], [inhists(:)]);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
255
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
256 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
257
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
258 % clear errors
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
259 bs.clearErrors;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
260
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
261 % Set output
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
262 if nargout == numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
263 % List of outputs
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
264 for ii = 1:numel(bs)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
265 varargout{ii} = bs.index(ii);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
266 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
267 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
268 % Single output
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
269 varargout{1} = bs;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
270 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
271 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
272
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
273 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
274 % Get Info Object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
275 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
276 function ii = getInfo(varargin)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
277 if nargin == 1 && strcmpi(varargin{1}, 'None')
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
278 sets = {};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
279 pl = [];
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
280 else
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
281 sets = {'Default'};
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
282 pl = getDefaultPlist;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
283 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
284 % Build info object
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
285 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: whiten2D.m,v 1.35 2011/04/08 08:56:16 hewitson Exp $', sets, pl);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
286 ii.setArgsmin(2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
287 ii.setOutmin(2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
288 ii.setModifier(false);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
289 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
290
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
291 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
292 % Get Default Plist
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
293 %--------------------------------------------------------------------------
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
294
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
295 function plout = getDefaultPlist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
296 persistent pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
297 if exist('pl', 'var')==0 || isempty(pl)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
298 pl = buildplist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
299 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
300 plout = pl;
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
301 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
302
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
303 function pl = buildplist()
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
304
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
305 pl = plist();
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
306
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
307 % CSD11
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
308 p = param({'csd11', 'A frequency-series AO describing the model csd11'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
309 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
310
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
311 % CSD12
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
312 p = param({'csd12', 'A frequency-series AO describing the model csd12'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
313 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
314
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
315 % CSD21
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
316 p = param({'csd21', 'A frequency-series AO describing the model csd21'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
317 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
318
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
319 % CSD22
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
320 p = param({'csd22', 'A frequency-series AO describing the model csd22'}, paramValue.EMPTY_DOUBLE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
321 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
322
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
323 % MaxIter
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
324 p = param({'MaxIter', 'Maximum number of iterations in fit routine.'}, paramValue.DOUBLE_VALUE(30));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
325 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
326
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
327 % PoleType
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
328 p = param({'PoleType', ['Choose the pole type for fitting:<ol>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
329 '<li>use real starting poles</li>' ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
330 '<li>generates complex conjugate poles of the<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
331 'type <tt>a.*exp(theta*pi*j)</tt><br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
332 'with <tt>theta = linspace(0,pi,N/2+1)</tt></li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
333 '<li>generates complex conjugate poles of the type<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
334 '<tt>a.*exp(theta*pi*j)</tt><br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
335 'with <tt>theta = linspace(0,pi,N/2+2)</tt></li></ol>']}, {3, {1,2,3}, paramValue.SINGLE});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
336 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
337
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
338 % MinOrder
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
339 p = param({'MinOrder', 'Minimum order to fit with.'}, paramValue.DOUBLE_VALUE(2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
340 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
341
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
342 % MaxOrder
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
343 p = param({'MaxOrder', 'Maximum order to fit with.'}, paramValue.DOUBLE_VALUE(25));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
344 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
345
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
346 % Weights
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
347 p = param({'Weights', ['Choose weighting for the fit:<ol>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
348 '<li>equal weights for each point</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
349 '<li>weight with <tt>1/abs(model)</tt></li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
350 '<li>weight with <tt>1/abs(model).^2</tt></li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
351 '<li>weight with inverse of the square mean spread<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
352 'of the model</li></ol>']}, paramValue.DOUBLE_VALUE(3));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
353 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
354
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
355 % Plot
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
356 p = param({'Plot', 'Plot results of each fitting step.'}, paramValue.FALSE_TRUE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
357 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
358
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
359 % Disp
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
360 p = param({'Disp', 'Display the progress of the fitting iteration.'}, paramValue.FALSE_TRUE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
361 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
362
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
363 % MSEVARTOL
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
364 p = param({'MSEVARTOL', ['Mean Squared Error Variation - Check if the<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
365 'realtive variation of the mean squared error is<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
366 'smaller than the value specified. This<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
367 'option is useful for finding the minimum of Chi-squared.']}, ...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
368 paramValue.DOUBLE_VALUE(1e-2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
369 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
370
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
371 % FITTOL
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
372 p = param({'FITTOL', ['Mean Squared Error Value - Check if the mean<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
373 'squared error value is lower than the value<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
374 'specified.']}, paramValue.DOUBLE_VALUE(1e-2));
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
375 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
376
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
377 % UseSym
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
378 p = param({'UseSym', ['Use symbolic calculation in eigen-decomposition.<ul>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
379 '<li>0 - perform double-precision calculation in the<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
380 'eigendecomposition procedure to identify 2-Dim<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
381 'systems and for poles stabilization</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
382 '<li>1 - uses symbolic math toolbox variable precision<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
383 'arithmetic in the eigen-decomposition for 2-Dim<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
384 'system identification and double-precison for<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
385 'poles stabilization</li>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
386 '<li>2 - uses symbolic math toolbox variable precision<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
387 'arithmetic in the eigen-decomposition for 2-Dim<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
388 'system identification and for poles stabilization.']}, {1, {0,1,2}, paramValue.SINGLE});
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
389 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
390
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
391 % Keep var
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
392 p = param({'keepvar', '???'}, paramValue.TRUE_FALSE);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
393 p.val.setValIndex(2);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
394 pl.append(p);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
395
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
396 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
397
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
398
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
399 % PARAMETERS:
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
400 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
401 % 'csd11' - a frequency-series AO describing the model csd11
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
402 % 'csd12' - a frequency-series AO describing the model csd12
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
403 % 'csd21' - a frequency-series AO describing the model csd21
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
404 % 'csd22' - a frequency-series AO describing the model csd22
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
405 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
406 % 'MaxIter' - Maximum number of iterations in fit routine
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
407 % [default: 30]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
408 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
409 % 'PoleType' - Choose the pole type for fitting:
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
410 % 1 - use real starting poles
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
411 % 2 - generates complex conjugate poles of the
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
412 % type a.*exp(theta*pi*j)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
413 % with theta = linspace(0,pi,N/2+1)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
414 % 3 - generates complex conjugate poles of the type
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
415 % a.*exp(theta*pi*j)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
416 % with theta = linspace(0,pi,N/2+2) [default]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
417 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
418 % 'MinOrder' - Minimum order to fit with. [default: 2]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
419 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
420 % 'MaxOrder' - Maximum order to fit with. [default: 25]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
421 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
422 % 'Weights' - choose weighting for the fit: [default: 2]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
423 % 1 - equal weights for each point
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
424 % 2 - weight with 1/abs(model)
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
425 % 3 - weight with 1/sqrt(abs(model))
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
426 % 4 - weight with inverse of the square mean spread
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
427 % of the model
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
428 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
429 % 'Plot' - plot results of each fitting step. [default: false]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
430 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
431 % 'Disp' - Display the progress of the fitting iteration.
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
432 % [default: false]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
433 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
434 % 'FITTOL' - Mean Squared Error Value - Check if the mean
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
435 % squared error value is lower than the value
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
436 % specified. [defalut: 1e-2]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
437 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
438 % 'MSEVARTOL' - Mean Squared Error Variation - Check if the
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
439 % realtive variation of the mean squared error is
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
440 % smaller than the value specified. This
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
441 % option is useful for finding the minimum of Chi
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
442 % squared. [default: 1e-2]]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
443 %
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
444 % 'UseSym' - Use symbolic calculation in eigendecomposition.
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
445 % [default: 0]
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
446 % 0 - perform double-precision calculation in the
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
447 % eigendecomposition procedure to identify 2dim
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
448 % systems and for poles stabilization
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
449 % 1 - uses symbolic math toolbox variable precision
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
450 % arithmetic in the eigendecomposition for 2dim
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
451 % system identification and double-precison for
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
452 % poles stabilization
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
453 % 2 - uses symbolic math toolbox variable precision
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
454 % arithmetic in the eigendecomposition for 2dim
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
455 % system identification and for poles
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
456 % stabilization