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author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Mon, 05 Dec 2011 16:20:06 +0100 |
parents | f0afece42f48 |
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% BICOHERE computes the bicoherence of two input time-series %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % % DESCRIPTION: BICOHERE computes the bicoherence of two input time-series. % % CALL: bs = bicohere(a1,a2,pl) % % INPUTS: aN - input analysis objects % a1,a2 - input analysis objects array % pl - input parameter list % % OUTPUTS: bs - xyz data analysis object % % <a href="matlab:utils.helper.displayMethodInfo('bicohere', 'psd')">Parameters Description</a> % % VERSION: $Id: psd.m,v 1.59 2010/12/17 17:45:08 ingo Exp $ % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function varargout = bicohere(varargin) % Check if this is a call for parameters if utils.helper.isinfocall(varargin{:}) varargout{1} = getInfo(varargin{3}); return end import utils.const.* utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename); % Collect input variable names in_names = cell(size(varargin)); for ii = 1:nargin,in_names{ii} = inputname(ii);end % Collect all AOs and plists [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names); pl = utils.helper.collect_objects(varargin(:), 'plist', in_names); if numel(as) ~= 2 error('bicohere only works with 2 time-series at the moment.'); end % Get data a = as(1); b = as(2); % same fs? if a.data.fs ~= b.data.fs error('### Two time-series have different sample rates.'); end % Same length vectors? if a.len ~= b.len error('### Two time-series must have same length'); end % Combine plists pl = combine(pl, getDefaultPlist); usepl = utils.helper.process_spectral_options(pl, 'lin', a.len, a.fs); win = find(usepl, 'Win'); nfft = find(usepl, 'Nfft'); olap = find(usepl, 'Olap')/100; Xolap = round(olap*nfft); order = find(usepl, 'order'); fs = a.data.fs; x = {a.data.y; b.data.y}; [x,M,isreal_x,y,Ly,win,winName,winParam,noverlap,k,L,options] = ... ao.welchparse(x,'',win.win, Xolap, nfft, fs); select = 1:(nfft+1)/2; % loop over segments LminusOverlap = L-noverlap; xStart = 1:LminusOverlap:k*LminusOverlap; xEnd = xStart+L-1; m = zeros(length(select), length(select)); for i = 1:k if order < 0 Xseg = x(xStart(i):xEnd(i)); Yseg = x(xStart(i):xEnd(i)); else [Xseg,coeffs] = ltpda_polyreg(x(xStart(i):xEnd(i)), order); [Yseg,coeffs] = ltpda_polyreg(y(xStart(i):xEnd(i)), order); end % window xw = Xseg.*win.'; yw = Yseg.*win.'; % FFT xx2s = fft(xw); xx = xx2s(select); yy2s = fft(yw); yy = yy2s(select); scalex = abs(xx); scaley = abs(yy); sc = scalex * scaley'; m = m + (xx * yy')./sc; end m = m./k; f = psdfreqvec('npts',nfft,'Fs',fs); f = f(select); do = xyzdata(f, f, m); do.setXunits('Hz'); do.setYunits('Hz'); do.setZunits(a.yunits*b.yunits); ma = ao(do); ma.setName(sprintf('%s, %s', a.name, b.name)); ma.addHistory(getInfo('None'), usepl, ao_invars, [a.hist b.hist]); % Set output varargout{1} = ma; end %-------------------------------------------------------------------------- % Get Info Object %-------------------------------------------------------------------------- function ii = getInfo(varargin) if nargin == 1 && strcmpi(varargin{1}, 'None') sets = {}; pl = []; else sets = {'Default'}; pl = getDefaultPlist; end % Build info object ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: psd.m,v 1.59 2010/12/17 17:45:08 ingo Exp $', sets, pl); end %-------------------------------------------------------------------------- % Get Default Plist %-------------------------------------------------------------------------- function plout = getDefaultPlist() persistent pl; if exist('pl', 'var')==0 || isempty(pl) pl = buildplist(); end plout = pl; end function pl = buildplist() % General plist for Welch-based, linearly spaced spectral estimators pl = plist.WELCH_PLIST; end % END