function [dS,t,f]=mtdspecgrampt(data,movingwin,phi,params) % Multi-taper derivative time-frequency spectrum - point process times % % Usage: % % [dS,t,f]=mtdspecgrampt(data,movingwin,phi,params) % Input: % Note that all times can be in arbitrary units. But the units have to be % consistent. So, if E is in secs, win, t have to be in secs, and Fs has to % be Hz. If E is in samples, so are win and t, and Fs=1. In case of spike % times, the units have to be consistent with the units of data as well. % data (structure array of spike times with dimension channels/trials; % also accepts 1d array of spike times) -- required % movingwin (in the form [window winstep] i.e length of moving % window and step size. % Note that units here have % to be consistent with % units of Fs % phi (angle for evaluation of derivative) -- required. % e.g. phi=[0,pi/2] giving the time and frequency % derivatives % params: structure with fields tapers, pad, Fs, fpass, trialave % -optional % tapers : precalculated tapers from dpss or in the one of the following % forms: % (1) A numeric vector [TW K] where TW is the % time-bandwidth product and K is the number of % tapers to be used (less than or equal to % 2TW-1). % (2) A numeric vector [W T p] where W is the % bandwidth, T is the duration of the data and p % is an integer such that 2TW-p tapers are used. In % this form there is no default i.e. to specify % the bandwidth, you have to specify T and p as % well. Note that the units of W and T have to be % consistent: if W is in Hz, T must be in seconds % and vice versa. Note that these units must also % be consistent with the units of params.Fs: W can % be in Hz if and only if params.Fs is in Hz. % The default is to use form 1 with TW=3 and K=5 % Note that T has to be equal to movingwin(1). % % pad (padding factor for the FFT) - optional (can take values -1,0,1,2...). % -1 corresponds to no padding, 0 corresponds to padding % to the next highest power of 2 etc. % e.g. For N = 500, if PAD = -1, we do not pad; if PAD = 0, we pad the FFT % to 512 points, if pad=1, we pad to 1024 points etc. % Defaults to 0. % 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 % trialave (average over trials when 1, don't average when 0) - % optional. Default 0 % Output: % dS (spectral derivative in form phi x time x frequency x channels/trials if trialave=0; % in form phi x time x frequency if trialave=1) % t (times) % f (frequencies) if nargin < 3; error('Need data, window parameters and angle'); end; if nargin < 4; params=[]; end; if length(params.tapers)==3 & movingwin(1)~=params.tapers(2); error('Duration of data in params.tapers is inconsistent with movingwin(1), modify params.tapers(2) to proceed') end [tapers,pad,Fs,fpass,err,trialave,params]=getparams(params); clear err [mintime,maxtime]=minmaxsptimes(data); tn=(mintime+movingwin(1)/2:movingwin(2):maxtime-movingwin(1)/2); Nwin=round(Fs*movingwin(1)); % number of samples in window % Nstep=round(movingwin(2)*Fs); % number of samples to step through nfft=max(2^(nextpow2(Nwin)+pad),Nwin); f=getfgrid(Fs,nfft,fpass); Nf=length(f); params.tapers=dpsschk(tapers,Nwin,Fs); % check tapers %K=size(params.tapers,2); nw=length(tn); if trialave==0; dS=zeros(length(phi),nw,Nf,C); else dS=zeros(length(phi),nw,Nf); end; for n=1:nw; t=linspace(tn(n)-movingwin(1)/2,tn(n)+movingwin(1)/2,Nwin); datawin=extractdatapt(data,[t(1) t(end)]); [ds,f]=mtdspectrumpt(datawin,phi,params,t); dS(:,n,:,:)=ds; end; sz=size(ds); dS=squeeze(dS); % if length(sz)==3; % dS=permute(dS,[2 1 3 4]); % elseif length(phi)>1 % dS=permute(dS,[2 1 3]); % end; t=tn;