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annotate m-toolbox/classes/@ao/whiten1D.m @ 4:e3c5468b1bfe database-connection-manager

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Integrate with LTPDAPreferences
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Mon, 05 Dec 2011 16:20:06 +0100
parents f0afece42f48
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % WHITEN1D whitens the input time-series.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: WHITEN1D whitens the input time-series. The filter is built
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % by fitting to the model provided. If no model is provided, a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % fit is made to a spectral-density estimate of the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % time-series (made using psd+bin_data or lpsd).
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % Note: The function assumes that the input model corresponds
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % to the one-sided psd of the data to be whitened.
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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 % ALGORITHM:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % 1) If no model provided, make psd+bin_data or lpsd
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % of time-series and take it as a model
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % for the data power spectral density
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 % 2) Fit a set of partial fraction z-domain filters using
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % utils.math.psd2wf. The fit is automatically stopped when
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 % the accuracy tolerance is reached.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % 3) Convert to array of MIIR filters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % 4) Assemble into a parallel filterbank object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % 5) Filter time-series in parallel
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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 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % CALL: b = whiten1D(a, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % [b1,b2,...,bn] = whiten1D(a1,a2,...,an, pl);
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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 % - as are time-series analysis objects or a vector of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 % analysis objects
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 % - pl is a plist with the input parameters
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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 % OUTPUT:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 % - bs "whitened" time-series AOs. The whitening filters used
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 % are stored in the objects procinfo field under the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 % parameter 'Filter'.
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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 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'whiten1D')">Parameters Description</a>
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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 % VERSION: $Id: whiten1D.m,v 1.43 2011/04/08 08:56:12 hewitson Exp $
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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 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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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 function varargout = whiten1D(varargin)
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 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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52
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 [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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59 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 inhists = [as.hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 if isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 model = 'psd';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 model = find(pl, 'model');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 if isempty(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 model = 'psd';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 if ischar(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 pl = parse(pl, getDefaultPlist(model));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 pl = parse(pl, getDefaultPlist('Default'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 pl.getSetRandState();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 scale = find(pl, 'scaleOut');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 flim = find(pl, 'flim');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 % Loop over input AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 for jj = 1:numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 if ~isa(as(jj).data, 'tsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 utils.helper.msg(msg.IMPORTANT, '%s expects ao/tsdata objects. Skipping AO %s', mfilename, ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 else
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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 %-------------- Whiten this AO
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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 % 1) Build whitening filterbank
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 switch class(model)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 case 'char'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 % Model is to be evaluated from data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98 in = as(jj);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 pl.pset('model', model);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 case 'ao'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 % Model was provided as fsdata
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 in = model;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 pl.pset('model', []);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 wf = buildWhitener1D(in, pl);
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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>
parents:
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107 % 1.5) Scale the date if demanded
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 if (scale)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 spsd = lpsd(as(jj));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 freqs = spsd.x;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 if isempty(flim)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 error('Please specify a flim field, to know the analysis band.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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113 elseif (flim(2) < flim(1))
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 error('flim should go from the smaller frequency to the bigger frequency. Please reverse them!')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 index = find((freqs > flim(1)) & (freqs < flim(2)));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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119 v1 = spsd.y(index(1):index(end-1));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 v2 = spsd.y(index(2):index(end));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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121 m = (v1 + v2) /2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122 p = sum(m.* diff(freqs(index(1):index(end))));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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123 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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124
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125 % 2) Filter data and scale it if necessary
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 bs(jj).filter(wf);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127 if (scale)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 bs(jj) = bs(jj) * sqrt(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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132 % 3) Output data
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 % name for this object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 bs(jj).name = sprintf('whiten1D(%s)', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 % Collect the filters into procinfo
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 bs(jj).procinfo = combine(plist('Filter', wf.filters), as(jj).procinfo);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 if(scale)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138 bs(jj).procinfo = combine(plist('ScaleFactor', p, 'Filter', wf.filters), as(jj).procinfo);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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139 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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140 % Make sure that the output yunits are empty
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 if ~eq(bs(jj).yunits, unit(''))
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 utils.helper.msg(msg.PROC1, 'Resetting output yunits to empty');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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143 bs(jj).setYunits(unit(''));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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144 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 % add history
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), inhists(jj));
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 % clear errors
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 bs(jj).clearErrors;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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151 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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152 end
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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
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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 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 if nargout == numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 for ii = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 varargout{ii} = bs(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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162 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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163 % Single output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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164 varargout{1} = bs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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166 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
168 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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169 % Get Info Object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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170 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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171 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
172 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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173 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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174 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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175 elseif nargin == 1 && ~isempty(varargin{1}) && ischar(varargin{1})
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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176 sets{1} = varargin{1};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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177 pl = getDefaultPlist(sets{1});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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178 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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179 sets = SETS();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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180 % get plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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181 pl(size(sets)) = plist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
182 for kk = 1:numel(sets)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
183 pl(kk) = getDefaultPlist(sets{kk});
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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184 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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185 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
186 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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187 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: whiten1D.m,v 1.43 2011/04/08 08:56:12 hewitson Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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188 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
189
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
190
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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191 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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192 % Defintion of Sets
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
193 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
194
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
195 function out = SETS()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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196 out = ao.getInfo('buildWhitener1D').sets;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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197 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
198
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
199 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
200 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
201 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
202 function plout = getDefaultPlist(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
203 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
204 persistent lastset;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
205 if ~exist('pl', 'var') || isempty(pl) || ~strcmp(lastset, set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
206 pl = buildplist(set);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
207 lastset = set;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
208 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
209 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
210 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
211
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
212 function pl = buildplist(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
213
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
214 pl = plist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
215
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
216 % Append sets of parameters according to the chosen spectral estimator
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
217 if ~utils.helper.ismember(lower(SETS), lower(set))
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
218 error('### Unknown set [%s]', set);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
219 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
220 pl = ao.getInfo('buildWhitener1D', lower(set)).plists;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
221 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
222
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
223 switch lower(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
224 case 'default'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
225 % Model
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
226 p = param({'model', ['A frequency-series AO describing the model<br>'...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
227 'response to build the filter from. <br>' ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
228 'As an alternative, the user '...
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
229 'can choose a model estimation technique:<br>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
230 '<li>PSD - using <tt>psd</tt> + <tt>bin_data</tt></li>'...
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
231 '<li>LPSD - using <tt>lpsd</tt></li>']}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
232 pl = combine(plist(p), pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
233 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
234 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
235
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
236 p = param({'scaleOut', ['Scale your output by the inband power']},paramValue.FALSE_TRUE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
237 pl = combine(plist(p), pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
238
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
239 p = param({'flim', ['Band to calculate the scaling power']},[1e-3 30e-3]);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
240 pl = combine(plist(p), pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
241
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
242
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
243 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
244