Mercurial > hg > ltpda

annotate m-toolbox/classes/@ao/fngen.m @ 1:2014ba5b353a database-connection-manager

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Remove old code
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Sat, 03 Dec 2011 18:13:55 +0100
parents f0afece42f48
children
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % FNGEN creates an arbitrarily long time-series based on the input PSD.
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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: FNGEN creates an arbitrarily long time-series based on the input PSD.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 % CALL: b = fngen(axx, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % PARAMETERS:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % 'Nsecs' - The number of seconds to produce
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % [default: inverse of PSD length]
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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11 % 'Win' - The spectral window to use for blending segments
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 % [default: Kaiser -150dB]
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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14 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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15 % NOTE: this function requires the Statistics Toolbox in order to create
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % a chi^2 distributed random variable.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'fngen')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % VERSION: $Id: fngen.m,v 1.33 2011/04/08 08:56:16 hewitson Exp $
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 function varargout = fngen(varargin)
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 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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34
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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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 all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 [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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41 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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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 if nargout == 0
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 error('### fngen cannot be used as a modifier. Please give an output variable.');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 end
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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 % combine plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 pl = parse(pl, getDefaultPlist());
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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 % Extract necessary parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 Nsecs = find(pl, 'Nsecs');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 swin = find(pl, 'win');
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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 bs = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 for j=1:numel(as)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 if ~isa(as(j).data, 'fsdata')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 warning('!!! %s expects ao/fsdata objects. Skipping AO %s', mfilename, as(j).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 % Properties of the input PSD
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 N = 2*(length(as(j).data.y)-1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 fs = as(j).data.x(end)*2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 % Extract Fourier components
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 Ak = sqrt(N*as(j).data.getY*fs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 Ak = [Ak; Ak(end-1:-1:2)]; % make two-sided
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 % redesign input window for this length
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 switch lower(swin.type)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 case 'kaiser'
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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69 swin = specwin('Kaiser', N, swin.psll);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 swin = specwin(swin.type, N);
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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 % Compute time-series segments
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 Olap = 1-swin.rov/100;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 win = [swin.win].';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 segLen = N/fs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 if segLen > Nsecs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 cNsecs = 2*segLen;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 cNsecs = Nsecs;
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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 Nsegs = 1+floor(cNsecs/segLen/Olap);
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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>
parents:
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84 % Prepare for generation
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 rphi = zeros(N,1); % Empty vector for random phases
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 xs = zeros(fs*(cNsecs+segLen), 1); % Large empty vector for new time-series
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 e1 = 1; e2 = segLen*fs; % Indices into large vector
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 step = round(segLen*fs*Olap); % step size between each new segment
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 lxs = length(xs);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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91 % Loop over segments
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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92 for s=1:Nsegs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 % Generate random phase vector
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 rphi(2:N/2) = pi*rand(1,N/2-1); % First half
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 rphi(N/2+1) = pi*round(rand); % mid point
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 rphi(N/2+2:N) = -rphi(N/2:-1:2); % reflected half
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 %---- Compute Fourier amplitudes
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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98 % Use chi^2 distribution to randomize amplitudes.
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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99 % - from Percival and Walden: S_est = S.*chi2rnd(2)/2
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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100 % so A_est = A.*sqrt(chi2rnd(2)/2)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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101 % Here we take the measured input data to be a good estimate of
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 % the underlying power spectrum
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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103 X = (Ak.*sqrt(chi2rnd(2)/2)) .*exp(1i.*rphi);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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104 % Inverse FFT
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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105 x = ifft(X, 'symmetric');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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106 % overlap the segments
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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107 xs(e1:e2) = xs(e1:e2) + win.*x;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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108 % increase step
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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109 e1 = e1 + step;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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110 e2 = e2 + step;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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111 if e2>lxs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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112 break
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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113 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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114 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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115 % Make ao from the segment of data we want
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 e1 = fs*segLen/2;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 e2 = fs*(Nsecs+segLen/2)-1;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 b = ao(tsdata(xs(e1:e2).', fs));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 b.name = sprintf('fngen(%s)', ao_invars{j});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 b.data.setXunits('s');
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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121 % Add history
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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122 b.addHistory(getInfo('None'), pl, ao_invars(j), as(j).hist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 % Add to outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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124 bs = [bs b];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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125 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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126 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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127
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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128 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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129 if nargout == numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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130 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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131 for ii = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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132 varargout{ii} = bs(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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133 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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134 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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135 % Single output
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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136 varargout{1} = bs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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137 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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138
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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
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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141 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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142 % Get Info Object
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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 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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145 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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146 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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147 pl = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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148 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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149 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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150 pl = getDefaultPlist;
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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 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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153 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: fngen.m,v 1.33 2011/04/08 08:56:16 hewitson Exp $', sets, pl);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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154 ii.setModifier(false);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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155 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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156
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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157 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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158 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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159 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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160 function plout = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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161 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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162 if exist('pl', 'var')==0 || isempty(pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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163 pl = buildplist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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164 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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165 plout = pl;
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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:
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167
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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168 function pl = buildplist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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169
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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170 pl = plist();
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Daniele Nicolodi <nicolodi@science.unitn.it>
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171
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Daniele Nicolodi <nicolodi@science.unitn.it>
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172 % Win
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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173 p = param({'Win', 'The spectral window to use for blending data segments.'}, paramValue.WINDOW);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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174 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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175
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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176 % Nsecs
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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177 p = param({'Nsecs', 'The number of seconds of data to produce.'}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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178 pl.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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179
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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180 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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181