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- function [Sc,Cmat,Ctot,Cvec,Cent,f]=CrossSpecMat(data,win,params)
- %
- %
- % Multi-taper cross-spectral matrix - another routine, this one allows for multiple trials and channels
- % but does not do confidence intervals. Also this routine always averages over trials - continuous process
- %
- % Usage:
- %
- % [Sc,Cmat,Ctot,Cvec,Cent,f]=CrossSpecMat(data,win,params)
- % Input:
- % Note units have to be consistent. See chronux.m for more information.
- % data (in form samples x channels x trials)
- % win (duration of non-overlapping window)
- % params: structure with fields tapers, pad, Fs, fpass
- % - optional
- % tapers (precalculated tapers from dpss, or in the form [NW K] e.g [3 5]) -- optional.
- % If not specified, use [NW K]=[3 5]
- % pad (padding factor for the FFT) - optional. Defaults to 0.
- % e.g. For N = 500, if PAD = 0, we pad the FFT
- % to 512 points; if PAD = 2, we pad the FFT
- % to 2048 points, etc.
- % Fs (sampling frequency) - optional. Default 1.
- % fpass (frequency band to be used in the calculation in the form
- % [fmin fmax])- optional.
- % Default all frequencies between 0 and Fs/2
- % Output:
- % Sc (cross spectral matrix frequency x channels x channels)
- % Cmat Coherence matrix frequency x channels x channels
- % Ctot Total coherence: SV(1)^2/sum(SV^2) (frequency)
- % Cvec leading Eigenvector (frequency x channels)
- % Cent A different measure of total coherence: GM/AM of SV^2s
- % f (frequencies)
- d=ndims(data);
- if d<2, error('Need multidimensional array'); end
- if d==2, [N,C]=size(data); end;
- if d==3, [N,C,Ntr]=size(data); end;
- if nargin < 3; params=[]; end;
- [tapers,pad,Fs,fpass,err,trialave,params]=getparams(params);
- clear err trialave params
- nwin=round(win*Fs); nfft=2^(nextpow2(nwin)+pad);
- [f,findx]=getfgrid(Fs,nfft,fpass);
- tapers=dpsschk(tapers,nwin,Fs); % check tapers
- Sc=zeros(length(findx),C,C);
- Nwins=floor(N/nwin);
- if d==3, % If there are multiple trials
- for iwin=1:Nwins,
- for i=1:Ntr,
- data1=squeeze(data(1+(iwin-1)*nwin:iwin*nwin,:,i));
- J1=mtfftc(detrend(data1),tapers,nfft,Fs);
- J1=J1(findx,:,:);
- for k=1:C,
- for l=1:C,
- spec=squeeze(mean(conj(J1(:,:,k)).*J1(:,:,l),2));
- Sc(:,k,l)=Sc(:,k,l)+spec;
- end
- end
- end
- end
- Sc=Sc/(Nwins*Ntr);
- end
- if d==2, % only one trial
- for iwin=1:Nwins,
- data1=squeeze(data(1+(iwin-1)*nwin:iwin*nwin,:));
- J1=mtfftc(data1,tapers,nfft,Fs);
- J1=J1(findx,:,:);
- for k=1:C,
- for l=1:C,
- Sc(:,k,l)=Sc(:,k,l)+squeeze(mean(conj(J1(:,:,k)).*J1(:,:,l),2));
- end
- end
- end
- Sc=Sc/Nwins;
- end
- Cmat=Sc;
- Sdiag=zeros(length(findx),C);
- for k=1:C,
- Sdiag(:,k)=squeeze(Sc(:,k,k));
- end
- for k=1:C,
- for l=1:C,
- Cmat(:,k,l)=Sc(:,k,l)./sqrt(abs(Sdiag(:,k).*Sdiag(:,l)));
- end
- end
- Ctot=zeros(length(findx),1); Cent=Ctot;
- Cvec=zeros(length(findx),C);
- for i=1:length(findx),
- [u s]=svd(squeeze(Sc(i,:,:)));s=diag(s);
- Ctot(i)=s(1).^2/sum(s.^2); Cent(i)=exp(mean(log(s.^2)))/mean(s.^2);
- Cvec(i,:)=transpose(u(:,1));
- end
-
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