


removes significant sine waves from data (continuous data).
Usage: data=rmlinesc(data,params,p,plt,f0)
Inputs:
Note that units of Fs, fpass have to be consistent.
data (data in [N,C] i.e. time x channels/trials or a single vector) - required.
params structure containing parameters - params has the
following fields: tapers, Fs, fpass, pad
tapers (parameters for calculating tapers [NW,K]) - optional. Defaults to [3 5]
Fs (sampling frequency) -- optional. Defaults to 1.
fpass (frequency band to be used in the calculation in the form
[fmin fmax])- optional.
Default all frequencies between 0 and Fs/2
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.
p (P-value for F-test) - optional. Defaults to 0.05/N
where N is data length. This corresponds to a false detect
probability of approximately 0.05
plt (y/n for plot and no plot respectively)
f0 frequencies at which you want to remove the
lines - if unspecified the program uses the f statistic
to determine appropriate lines.
Outputs:
data (data with significant lines removed)

0001 function data=rmlinesc(data,params,p,plt,f0) 0002 % removes significant sine waves from data (continuous data). 0003 % 0004 % Usage: data=rmlinesc(data,params,p,plt,f0) 0005 % 0006 % Inputs: 0007 % Note that units of Fs, fpass have to be consistent. 0008 % data (data in [N,C] i.e. time x channels/trials or a single vector) - required. 0009 % params structure containing parameters - params has the 0010 % following fields: tapers, Fs, fpass, pad 0011 % tapers (parameters for calculating tapers [NW,K]) - optional. Defaults to [3 5] 0012 % Fs (sampling frequency) -- optional. Defaults to 1. 0013 % fpass (frequency band to be used in the calculation in the form 0014 % [fmin fmax])- optional. 0015 % Default all frequencies between 0 and Fs/2 0016 % pad (padding factor for the FFT) - optional (can take values -1,0,1,2...). 0017 % -1 corresponds to no padding, 0 corresponds to padding 0018 % to the next highest power of 2 etc. 0019 % e.g. For N = 500, if PAD = -1, we do not pad; if PAD = 0, we pad the FFT 0020 % to 512 points, if pad=1, we pad to 1024 points etc. 0021 % Defaults to 0. 0022 % p (P-value for F-test) - optional. Defaults to 0.05/N 0023 % where N is data length. This corresponds to a false detect 0024 % probability of approximately 0.05 0025 % 0026 % plt (y/n for plot and no plot respectively) 0027 % f0 frequencies at which you want to remove the 0028 % lines - if unspecified the program uses the f statistic 0029 % to determine appropriate lines. 0030 % 0031 % Outputs: 0032 % data (data with significant lines removed) 0033 % 0034 data=change_row_to_column(data); 0035 [N,C]=size(data); 0036 if nargin < 2 || isempty(params); params=[]; end; 0037 [tapers,pad,Fs,fpass,err,trialave,params]=getparams(params); 0038 clear pad fpass err trialave 0039 user_specified_pval=0; 0040 if nargin < 3 || isempty(p);p=0.05/N; else; user_specified_pval=1; end; 0041 if nargin < 4 || isempty(plt); plt='n'; end; 0042 if nargin < 5; f0=[]; end; 0043 if isempty(f0) && user_specified_pval==1; p=p/N; end; 0044 [datafit,Amps,freqs,Fval,sig]=fitlinesc(data,params,p,'n',f0); 0045 datan=data-datafit; 0046 %params.tapers=dpsschk(tapers,N,Fs); % calculate the tapers 0047 0048 % [Fval,A,f,sig] = ftestc(data,params,p,'n'); 0049 % fmax=findpeaks(Fval,sig); 0050 % datasine=data; 0051 % for ch=1:C; 0052 % fsig=f(fmax(ch).loc); 0053 % Nf=length(fsig); 0054 % fprintf('The significant lines for channel %d and the amplitudes are \n',ch); 0055 % for nf=1:Nf; 0056 % fprintf('%12.8f\n',fsig(nf)); 0057 % fprintf('%12.8f\n',real(A(fmax(ch).loc(nf),ch))); 0058 % fprintf('%12.8f\n',imag(A(fmax(ch).loc(nf),ch))); 0059 % fprintf('\n'); 0060 % end; 0061 % datasine(:,ch)=exp(i*2*pi*(0:N-1)'*fsig/Fs)*A(fmax(ch).loc,ch)+exp(-i*2*pi*(0:N-1)'*fsig/Fs)*conj(A(fmax(ch).loc,ch)); 0062 % end; 0063 % % subplot(211); plot(data); hold on; plot(datasine,'r'); 0064 % datan=data-datasine; 0065 % subplot(212); plot(datan); 0066 if nargout==0 || strcmp(plt,'y'); 0067 figure; 0068 [S1,f]=mtspectrumc(detrend(data),params); 0069 subplot(321); plot(f,10*log10(S1));xlabel('frequency Hz'); ylabel('Spectrum dB'); title('Original spectrum'); 0070 subplot(323); plot(f,Fval); line(get(gca,'xlim'),[sig sig],'Color','r'); xlabel('frequency Hz');ylabel('F-statistic'); 0071 [S2,f]=mtspectrumc(detrend(datan),params); 0072 subplot(325);plot(f,10*log10(S1),f,10*log10(S2));xlabel('frequency Hz'); ylabel('Spectrum dB'); title('Original and cleaned spectra'); 0073 subplot(322); plot((1:size(data,1))/params.Fs,data); xlabel('time s'); title('Original data'); 0074 subplot(324); plot((1:size(datan,1))/params.Fs,datan);xlabel('time s'); title('Cleaned data'); 0075 end; 0076 data=datan;