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annotate m-toolbox/classes/@ao/psd.m @ 41:6def6533cb16 database-connection-manager

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 18:04:34 +0100
parents f0afece42f48
children
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 % PSD makes power spectral density estimates of the time-series objects
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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: PSD makes power spectral density estimates of the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % time-series objects in the input analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % using the Welch Overlap method. PSD is computed
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % using a modified version of MATLAB's welch (>> help welch).
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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: bs = psd(a1,a2,a3,...,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % bs = psd(as,pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % bs = as.psd(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % INPUTS: aN - input analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % as - input analysis objects array
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % pl - input parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % OUTPUTS: bs - array of analysis objects, one for each input
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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 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'psd')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % VERSION: $Id: psd.m,v 1.69 2011/08/24 07:29:02 hewitson Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24
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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 function varargout = psd(varargin)
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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 callerIsMethod = utils.helper.callerIsMethod;
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 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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38
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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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 % Collect all AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 [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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45
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % Apply defaults to plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 usepl = applyDefaults(getDefaultPlist, varargin{:});
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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 inhists = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 % Loop over input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 for jj = 1 : numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 % gather the input history objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 inhists = [inhists bs(jj).hist];
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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 % check input data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 if isa(bs(jj).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % Check the time range.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 time_range = mfind(usepl, 'split', 'times');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 if ~isempty(time_range)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 switch class(time_range)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 case 'double'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 bs(jj) = split(bs(jj), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 'times', time_range));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 case 'timespan'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 bs(jj) = split(bs(jj), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 'timespan', time_range));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 case 'time'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 bs(jj) = split(bs(jj), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 'start_time', time_range(1), ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 'end_time', time_range(2)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 case 'cell'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 bs(jj) = split(bs(jj), plist(...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 'start_time', time_range{1}, ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 'end_time', time_range{2}));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 otherwise
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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 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 % Check the length of the object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 if bs(jj).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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 % Utility to deal with nfft, win, olap etc
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 use_pl = utils.helper.process_spectral_options(usepl, 'lin', len(bs(jj)), bs(jj).fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 % Compute PSD using pwelch
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 [pxx, f, info, dev] = welch(bs(jj), 'psd', use_pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % Keep the data shape of the input AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 if size(bs(jj).data.y,1) == 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 pxx = pxx.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 f = f.';
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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 % create new output fsdata
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 fs = bs(jj).fs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 fsd = fsdata(f, pxx, fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 fsd.setXunits('Hz');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 fsd.setYunits(info.units);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 fsd.setEnbw(info.enbw);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 fsd.setNavs(info.navs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 fsd.setT0(bs(jj).data.t0);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 % update AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 bs(jj).data = fsd;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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110 % add std deviation
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 bs(jj).data.dy = dev;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 % set name: scaling of spectrum
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 scale = upper(find(use_pl, 'Scale'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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114 bs(jj).name = sprintf('%s(%s)', lower(scale), ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 % Add history
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 if ~callerIsMethod
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 bs(jj).addHistory(getInfo('None'), use_pl, ao_invars(jj), inhists(jj));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 warning('### Ignoring input AO number %d (%s); it is not a time-series.', jj, bs(jj).name)
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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 end % loop over analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 varargout = utils.helper.setoutputs(nargout, bs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 end
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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 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 pl = getDefaultPlist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: psd.m,v 1.69 2011/08/24 07:29:02 hewitson Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 if ~exist('pl', 'var') || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156 % General plist for Welch-based, linearly spaced spectral estimators
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 pl = plist.WELCH_PLIST;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 % Scale
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 p = param({'Scale',['The scaling of output. Choose from:<ul>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 '<li>PSD - Power Spectral Density</li>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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162 '<li>ASD - Amplitude (linear) Spectral Density</li>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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163 '<li>PS - Power Spectrum</li>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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164 '<li>AS - Amplitude (linear) Spectrum</li></ul>']}, {1, {'PSD', 'ASD', 'PS', 'AS'}, paramValue.SINGLE});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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165 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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166
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Daniele Nicolodi <nicolodi@science.unitn.it>
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167 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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168