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comparison m-toolbox/classes/@ao/delayEstimate.m @ 0:f0afece42f48

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author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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1 % DELAYESTIMATE estimates the delay between two AOs
2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
3 %
4 % DESCRIPTION: DELAYESTIMATE returns an estimate of the delay between the two
5 % input analysis objects. Different weights in frequency
6 % domain can be used.
7 %
8 % CALL: bs = delayEstimate(a1,a2,pl)
9 %
10 % INPUTS: a1 - input analysis objects
11 % a2 - delayed analysis objects
12 % pl - input parameter list
13 %
14 % OUTPUTS: bs - analysis object with the delay (as cdata)
15 %
16 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'delayEstimate')">Parameters Description</a>
17 %
18 % VERSION: $Id: delayEstimate.m,v 1.6 2011/04/08 08:56:15 hewitson Exp $
19 %
20 % HISTORY: 15-10-09 M Nofrarias
21 % Creation
22 %
23 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
24
25
26 function varargout = delayEstimate(varargin)
27
28 % Check if this is a call for parameters
29 if utils.helper.isinfocall(varargin{:})
30 varargout{1} = getInfo(varargin{3});
31 return
32 end
33
34 import utils.const.*
35 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
36
37 % Collect input variable names
38 in_names = cell(size(varargin));
39 for ii = 1:nargin,in_names{ii} = inputname(ii);end
40
41 % Collect all AOs
42 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
43 pl = utils.helper.collect_objects(varargin(:), 'plist', in_names);
44
45 % Decide on a deep copy or a modify
46 bs = copy(as, nargout);
47
48 % Combine plists
49 pl = parse(pl, getDefaultPlist);
50
51 % get frequency weight
52 weight = find(pl, 'weight');
53
54 N = len(bs(1));
55 T = bs(1).x(end);
56 fs = bs(1).fs;
57 % zeropad to avoid circular convolution in ifft
58 bs(1).zeropad;
59 bs(2).zeropad;
60 % compute spectral density, scale applied after to avoid round-off errors
61 scale = fs/N;
62 Gx11 = conj(fft(bs(1).y)).*fft(bs(1).y);
63 Gx11 = Gx11*scale;
64 Gx12 = conj(fft(bs(1).y)).*fft(bs(2).y);
65 Gx12 = Gx12*scale;
66 Gx22 = conj(fft(bs(2).y)).*fft(bs(2).y);
67 Gx22 = Gx22*scale;
68 % frequencies for two-sided spectrum
69 f = linspace(-fs,fs,2*N);
70 % select weight
71 if strcmp(weight,'roth')
72 weight = Gx11;
73 elseif strcmp(weight,'scot')
74 weight = sqrt(Gx11.* Gx22);
75 elseif strcmp(weight,'scc')
76 weight = 1;
77 elseif strcmp(weight,'phat')
78 weight = abs(Gx12);
79 elseif strcmp(weight,'eckart')
80 weight = 1;
81 elseif strcmp(weight,'ML')
82 weight = 1;
83 else
84 error('### Unknown value for ''weight'' parameter ' )
85 end
86 % compute unscaled correlation function
87 Ru = ifft(Gx12./weight);
88 % lag= 0:\deltat*(N-1)
89 % n= 1:N/2-1
90 r = linspace(0,T-1/fs,length(Ru)/2-1);
91 % scaling to correct zeropad bias
92 R = (N./(N-r))'.*Ru(1:length(Ru)/2-1);
93 % get maximum
94 [m,ind] = max(R);
95 del = r(ind);
96 % plot if required
97 plt = find(pl, 'plot');
98 if plt
99 Rxy = ao(xydata(r,R));
100 Rxy.setName(sprintf('Correlation(%s,%s)', ao_invars{1},ao_invars{2}))
101 iplot(Rxy)
102 end
103
104 % create new output cdata
105 cd = cdata(del);
106 % add unitss
107 cd.yunits = 's';
108 % update AO
109 c = ao(cd);
110 % add error
111 % bs(jj).data.dy = dev;
112 % Add name
113 c.name = sprintf('delayEst(%s,%s)', ao_invars{1},ao_invars{2});
114 % Add history
115 c.addHistory(getInfo('None'), pl, [ao_invars(:)], [bs(:).hist]);
116
117 % set output
118 varargout{1} = c;
119
120 end
121
122 %--------------------------------------------------------------------------
123 % Get Info Object
124 %--------------------------------------------------------------------------
125 function ii = getInfo(varargin)
126 if nargin == 1 && strcmpi(varargin{1}, 'None')
127 sets = {};
128 pl = [];
129 else
130 sets = {'Default'};
131 pl = getDefaultPlist;
132 end
133 % Build info object
134 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: delayEstimate.m,v 1.6 2011/04/08 08:56:15 hewitson Exp $', sets, pl);
135 end
136
137 %--------------------------------------------------------------------------
138 % Get Default Plist
139 %--------------------------------------------------------------------------
140
141 function plout = getDefaultPlist()
142 persistent pl;
143 if exist('pl', 'var')==0 || isempty(pl)
144 pl = buildplist();
145 end
146 plout = pl;
147 end
148
149 function pl = buildplist()
150 pl = plist();
151 % method
152 p = param({'weight',['scaling of output. Choose from:<ul>', ...
153 '<li>scc - </li>', ...
154 '<li>roth - </li>', ...
155 '<li>scot - </li>', ...
156 '<li>phat - </li>', ...
157 '<li>eckart - </li>', ...
158 '<li>ML - </li></ul>']}, {1, {'scc','roth', 'scot','phat','eckart','ML'}, paramValue.SINGLE});
159 pl.append(p);
160 % Plot
161 p = param({'Plot', 'Plot the correlation function'}, ...
162 {2, {'true', 'false'}, paramValue.SINGLE});
163 pl.append(p);
164 end
165 % END
166