annotate m-toolbox/classes/@ao/xspec.m @ 52:daf4eab1a51e database-connection-manager tip

Fix. Default password should be [] not an empty string
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 07 Dec 2011 17:29:47 +0100
parents bc767aaa99a8
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
rev   line source
0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % XSPEC performs cross-spectral analysis of various forms.
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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: XSPEC performs cross-spectral analysis of various forms.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % The function is a helper function for various higher level
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % functions. It is meant to be called from other functions
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % (e.g., tfe).
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % CALL: b = xspec(a, pl, method, iALGO, iVER, invars);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % INPUTS: a - vector of 2 input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % pl - input parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % method - one of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % 'cpsd' - compute cross-spectral density
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % 'tfe' - estimate transfer function between inputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % 'mscohere' - estimate magnitude-squared cross-coherence
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % 'cohere' - estimate complex cross-coherence
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % iALGO - ALGONAME from the calling higher level script
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % iVER - VERSION from the calling higher level script
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % invars - invars variable from the calling higher level script
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % OUTPUTS: b - output AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 %
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bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % VERSION: $Id: xspec.m,v 1.62 2011/12/01 08:51:11 hewitson Exp $
0
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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 % HISTORY: 30-05-2007 M Hewitson
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 % Creation
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 function varargout = xspec(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % unpack inputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 as = varargin{1};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 pl = varargin{2};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 method = varargin{3};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 mi = varargin{4};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 invars = varargin{5};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41
43
bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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42 VERSION = '$Id: xspec.m,v 1.62 2011/12/01 08:51:11 hewitson Exp $';
0
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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 % Set the method version string in the minfo object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 mi.setMversion([VERSION '-->' mi.mversion]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 %----------------- Select all AOs with time-series data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 tsao = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 for ll = 1:numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 if isa(as(ll).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 tsao = [tsao as(ll)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 warning('### xspec requires tsdata (time-series) inputs. Skipping AO %s. \nREMARK: The output doesn''t contain this AO', invars{ll});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 if numel(tsao) ~= 2
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 error('### XSPEC needs two time-series AOs.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 %----------------- Gather the input history objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 inhists = [tsao(:).hist];
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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 %----------------- Check the time range
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 time_range = mfind(pl, 'split', 'times');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 for ll = 1:numel(tsao)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 if ~isempty(time_range)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 switch class(time_range)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 case 'double'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 tsao(ll) = split(tsao(ll), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 'times', time_range));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 case 'timespan'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 tsao(ll) = split(tsao(ll), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 'timespan', time_range));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 case 'time'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 tsao(ll) = split(tsao(ll), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 'start_time', time_range(1), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 'end_time', time_range(2)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 case 'cell'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 tsao(ll) = split(tsao(ll), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 'start_time', time_range{1}, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 'end_time', time_range{2}));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 if tsao(ll).len <= 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 error('### The object is empty! Please revise your settings ...');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 %----------------- Resample all AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 copies = zeros(size(tsao));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 fsmin = ao.findFsMin(tsao);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 fspl = plist(param('fsout', fsmin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 for ll = 1:numel(tsao)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 % Check Fs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 if tsao(ll).data.fs ~= fsmin
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 utils.helper.msg(msg.PROC1, 'resampling AO %s to %f Hz', tsao(ll).name, fsmin);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 % Make a deep copy so we don't
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 % affect the original input data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 tsao(ll) = copy(tsao(ll), 1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 copies(ll) = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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103 resample(tsao(ll), fspl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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104 end
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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 %----------------- Truncate all vectors
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 % Get shortest vector
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 lmin = ao.findShortestVector(tsao);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 nsecs = lmin / fsmin;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 for ll = 1:numel(tsao)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 if len(tsao(ll)) ~= lmin
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 utils.helper.msg(msg.PROC2, 'truncating AO %s to %d secs', tsao(ll).name, nsecs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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115 % do we already have a copy?
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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116 if ~copies(ll)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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117 % Make a deep copy so we don't
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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118 % affect the original input data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 tsao(ll) = copy(tsao(ll), 1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 copies(ll) = 1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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121 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 tsao(ll).select(1:lmin);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126 %----------------- check input parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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127
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 usepl = utils.helper.process_spectral_options(pl, 'lin', lmin, fsmin);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 % Loop over input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 utils.helper.msg(msg.PROC1, 'computing %s(%s -> %s)', method, invars{1}, invars{2});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 % -------- Make Xspec estimate
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 % Compute xspec using welch and always scale to PSD
43
bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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136 if usepl.find('newmethod')
bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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137 [txy, f, info, dev] = ao.wosa(tsao(1), tsao(2), method, usepl.pset('Scale', 'PSD'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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138 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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139 [txy, f, info, dev] = welch(tsao(1), tsao(2), method, usepl.pset('Scale', 'PSD'));
bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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140 end
bc767aaa99a8 CVS Update
Daniele Nicolodi <nicolodi@science.unitn.it>
parents: 0
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141
0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 % Keep the data shape of the first input AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 if size(tsao(1).data.y,1) == 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 txy = txy.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 f = f.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 dev = dev.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 end
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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 % create new output fsdata
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 fsd = fsdata(f, txy, fsmin);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 fsd.setEnbw(info.enbw);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 fsd.setXunits('Hz');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 switch lower(method)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 case 'tfe'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 fsd.setYunits(tsao(2).data.yunits / tsao(1).data.yunits);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 case 'cpsd'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 fsd.setYunits(tsao(2).data.yunits * tsao(1).data.yunits / unit('Hz'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 case {'mscohere','cohere'}
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 fsd.setYunits(unit());
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161 otherwise
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162 error(['### Unknown method:' method]);
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163 end
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164 fsd.setNavs(info.navs);
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165
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166 % set object t0
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167 if eq(tsao(1).t0, tsao(2).t0)
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168 fsd.setT0(tsao(1).t0);
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169 end
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170
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171 % make output analysis object
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172 bs = ao(fsd);
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173 % add variance
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174 bs.data.dy = dev;
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175
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176 % simplify the units in the case of cpsd calculation
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177 if strcmp(method, 'cpsd')
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178 bs.simplifyYunits(...
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179 plist('prefixes', false, 'exceptions', 'Hz'));
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180 end
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181
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Daniele Nicolodi <nicolodi@science.unitn.it>
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182 %----------- Add history
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183
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184 % set name
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185 bs.name = sprintf('%s(%s->%s)', upper(method), invars{1}, invars{2});
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186
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187 % we need to get the input histories in the same order tsao the inputs
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188 % to this function call, not in the order of the input to xspec;
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189 % otherwise the resulting matrix on a 'create from history' will be
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190 % mirrored.
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191 bs.addHistory(mi, usepl, [invars(:)], inhists);
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192
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193 % Propagate 'plotinfo'
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194 if ~isempty(tsao(1).plotinfo) || ~isempty(tsao(2).plotinfo)
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195 bs.plotinfo = combine(tsao(1).plotinfo, tsao(2).plotinfo);
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196 end
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197
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198 % Set output
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199 varargout{1} = bs;
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200 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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201