Home > chronux_1_15 > continuous > coherencysegc.m

coherencysegc

PURPOSE ^

Multi-taper coherency,cross-spectrum and individual spectra computed by segmenting two univariate time series into chunks - continuous process

SYNOPSIS ^

function [C,phi,S12,S1,S2,f,confC,phierr,Cerr]=coherencysegc(data1,data2,win,params)

DESCRIPTION ^

 Multi-taper coherency,cross-spectrum and individual spectra computed by segmenting two univariate time series into chunks - continuous process

 Usage:
 [C,phi,S12,S1,S2,f,confC,phierr,Cerr]=coherencysegc(data1,data2,win,params)
 Input: 
 Note units have to be consistent. See chronux.m for more information.
       data1 (column vector) -- required
       data2 (column vector) -- required
       win   (length of segments) - required
       params: structure with fields tapers, pad, Fs, fpass, err
       - 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
           err  (error calculation [1 p] - Theoretical error bars; [2 p] - Jackknife error bars
                                   [0 p] or 0 - no error bars) - optional. Default 0.
 Output:
       C (magnitude of coherency - frequencies x segments if segave=0; dimension frequencies if segave=1)
       phi (phase of coherency - frequencies x segments if segave=0; dimension frequencies if segave=1)
       S12 (cross spectrum -  frequencies x segments if segave=0; dimension frequencies if segave=1)
       S1 (spectrum 1 - frequencies x segments if segave=0; dimension frequencies if segave=1)
       S2 (spectrum 2 - frequencies x segments if segave=0; dimension frequencies if segave=1)
       f (frequencies)
       confC (confidence level for C at 1-p %) - only for err(1)>=1
       phierr - standard deviation for phi (note that the routine gives phierr as phierr(1,...) and phierr(2,...) 
                in order to incorporate Jackknife (eventually). Currently phierr(1,...)=phierr(2,...). Note that 
                phi + 2 phierr(1,...) and phi -2 phierr(2,...) will give 95% confidence bands for phi - only for err(1)>=1
       Cerr  (Jackknife error bars for C - use only for Jackknife - err(1)=2)

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [C,phi,S12,S1,S2,f,confC,phierr,Cerr]=coherencysegc(data1,data2,win,params)
0002 % Multi-taper coherency,cross-spectrum and individual spectra computed by segmenting two univariate time series into chunks - continuous process
0003 %
0004 % Usage:
0005 % [C,phi,S12,S1,S2,f,confC,phierr,Cerr]=coherencysegc(data1,data2,win,params)
0006 % Input:
0007 % Note units have to be consistent. See chronux.m for more information.
0008 %       data1 (column vector) -- required
0009 %       data2 (column vector) -- required
0010 %       win   (length of segments) - required
0011 %       params: structure with fields tapers, pad, Fs, fpass, err
0012 %       - optional
0013 %           tapers (precalculated tapers from dpss, or in the form [NW K] e.g [3 5]) -- optional. If not
0014 %                                                 specified, use [NW K]=[3 5]
0015 %            pad            (padding factor for the FFT) - optional. Defaults to 0.
0016 %                       e.g. For N = 500, if PAD = 0, we pad the FFT
0017 %                       to 512 points; if PAD = 2, we pad the FFT
0018 %                       to 2048 points, etc.
0019 %           Fs   (sampling frequency) - optional. Default 1.
0020 %           fpass    (frequency band to be used in the calculation in the form
0021 %                                   [fmin fmax])- optional.
0022 %                                   Default all frequencies between 0 and Fs/2
0023 %           err  (error calculation [1 p] - Theoretical error bars; [2 p] - Jackknife error bars
0024 %                                   [0 p] or 0 - no error bars) - optional. Default 0.
0025 % Output:
0026 %       C (magnitude of coherency - frequencies x segments if segave=0; dimension frequencies if segave=1)
0027 %       phi (phase of coherency - frequencies x segments if segave=0; dimension frequencies if segave=1)
0028 %       S12 (cross spectrum -  frequencies x segments if segave=0; dimension frequencies if segave=1)
0029 %       S1 (spectrum 1 - frequencies x segments if segave=0; dimension frequencies if segave=1)
0030 %       S2 (spectrum 2 - frequencies x segments if segave=0; dimension frequencies if segave=1)
0031 %       f (frequencies)
0032 %       confC (confidence level for C at 1-p %) - only for err(1)>=1
0033 %       phierr - standard deviation for phi (note that the routine gives phierr as phierr(1,...) and phierr(2,...)
0034 %                in order to incorporate Jackknife (eventually). Currently phierr(1,...)=phierr(2,...). Note that
0035 %                phi + 2 phierr(1,...) and phi -2 phierr(2,...) will give 95% confidence bands for phi - only for err(1)>=1
0036 %       Cerr  (Jackknife error bars for C - use only for Jackknife - err(1)=2)
0037 
0038 if nargin < 3; error('Need data1 and data2 and size of segment'); end;
0039 if nargin < 4; params=[]; end;
0040 [tapers,pad,Fs,fpass,err,trialave,params]=getparams(params);
0041 clear tapers pad fpass trialave
0042 if nargout > 8 && err(1)~=2; 
0043     error('Cerr computed only for Jackknife. Correct inputs and run again');
0044 end;
0045 if nargout > 6 && err(1)==0;
0046 %   Errors computed only if err(1) is nonzero. Need to change params and run again.
0047     error('When errors are desired, err(1) has to be non-zero.');
0048 end;
0049 if size(data1,2)~=1 || size(data2,2)~=1; error('works for only univariate time series'); end;
0050 
0051 N=check_consistency(data1,data2);
0052 
0053 dt=1/Fs; % sampling interval
0054 T=N*dt; % length of data in seconds
0055 E=0:win:T-win; % fictitious event triggers
0056 win=[0 win]; % use window length to define left and right limits of windows around triggers
0057 data1=createdatamatc(data1,E,Fs,win); % segmented data 1
0058 data2=createdatamatc(data2,E,Fs,win); % segmented data 2
0059 params.trialave=1;
0060 params.trialave=1;
0061 if err==0;
0062    [C,phi,S12,S1,S2,f]=coherencyc(data1,data2,params); % compute coherency for segmented data
0063 elseif err(1)==1;
0064    [C,phi,S12,S1,S2,f,confC,phierr]=coherencyc(data1,data2,params); % compute coherency for segmented data
0065 elseif err(1)==2;
0066    [C,phi,S12,S1,S2,f,confC,phierr,Cerr]=coherencyc(data1,data2,params); % compute coherency for segmented data
0067 end;

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