Home > NoiseTools > nt_deglitch.m

nt_deglitch

PURPOSE ^

[y,B,A]=nt_deglitch(x,glitchList,filt,nfit) - remove temporally localized glitch

SYNOPSIS ^

function [y,B,A]=nt_deglitch(x,glitchList,nfilt,nfit,advance);

DESCRIPTION ^

[y,B,A]=nt_deglitch(x,glitchList,filt,nfit) - remove temporally localized glitch

  y: clean data
  B,A: filter coefficients for last estimated event

  x: data to clean (time * channels)
  glitchList: list of glitch positions (cell array if x multichannel)
  nfilt: number of filter coefficients to estimate [default: 10, 10]
  nfit: number of samples over which to fit filter [default: 50]
  advance: number of samples to include before event [default: 3]

 If x is multichannel glitchI should be a cell array.
 
 See also nt_detrend.

 NoiseTools.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [y,B,A]=nt_deglitch(x,glitchList,nfilt,nfit,advance);
0002 %[y,B,A]=nt_deglitch(x,glitchList,filt,nfit) - remove temporally localized glitch
0003 %
0004 %  y: clean data
0005 %  B,A: filter coefficients for last estimated event
0006 %
0007 %  x: data to clean (time * channels)
0008 %  glitchList: list of glitch positions (cell array if x multichannel)
0009 %  nfilt: number of filter coefficients to estimate [default: 10, 10]
0010 %  nfit: number of samples over which to fit filter [default: 50]
0011 %  advance: number of samples to include before event [default: 3]
0012 %
0013 % If x is multichannel glitchI should be a cell array.
0014 %
0015 % See also nt_detrend.
0016 %
0017 % NoiseTools.
0018 nt_greetings;
0019 
0020 if nargin<2; error('!'); end
0021 if nargin<3; nfilt=[10,10]; end
0022 if nargin<4||isempty(nfit); nfit=50; end
0023 if nargin<5||isempty(advance); advance=3; end
0024 
0025 if numel(nfilt)==1; nfilt=[nfilt,nfilt]; end
0026 
0027 if ~6==exist('stmcb'); 
0028     error('Need function stmcb from signal toolbox');
0029 end
0030 
0031 
0032 y=x;
0033 
0034 if size(x,2)==1 ~iscell(glitchList)
0035     glitchList={glitchList}; 
0036 end
0037 
0038 for iChan=1:size(x,2)
0039 
0040     events=glitchList{iChan}; 
0041     
0042     for iEvent=1:numel(events)
0043 
0044         iStart=events(iEvent)-advance;
0045         glitch=x(iStart+(1:nfit),iChan);
0046         glitch=glitch-mean(glitch(floor(nfit/2):end));
0047         
0048         %The filter is estimated anew for each event.
0049         try
0050             [B,A]=stmcb([glitch;zeros(size(glitch))],nfilt(1),nfilt(2));            
0051             z=filter(B,A,[1;zeros(nfit-1,1)]);
0052             y(iStart+(1:nfit),iChan)=y(iStart+(1:nfit))-z;
0053         catch
0054             warning('stmcb failed (advance too large?)');
0055         end
0056     end
0057 end
0058 
0059 
0060 if ~nargout
0061     % don't return values, just plot
0062     %disp(['steps at: ', num2str(stepI(2:end-1))]);
0063     figure(1); clf; nt_banner('nt_destep');
0064     xx=[x(:),y(:)];
0065     lim=[min(xx(:)),max(xx(:))]; lim=[lim(1)-0.1*(lim(2)-lim(1)), lim(2)+0.1*(lim(2)-lim(1))];
0066     subplot 211; plot([x,y]); xlabel('samples'); ylim(lim); legend('raw','clean'); legend boxoff
0067     subplot 212;     plot(y,'r'); xlabel('samples'); legend('clean'); legend boxoff
0068     figure(2); clf
0069     plot(filter(B,A,[1;zeros(199,1)]),'.-'); xlabel('samples'); title('estimated impulse response of antialiasing filter (last event)');
0070     clear y B A;
0071 end
0072 
0073 
0074 
0075 % test code
0076 if 0
0077     N=8;
0078     Wn=0.25; % CTF corner frequency is 1/4 of sampling rate
0079     nsamples=100;
0080     [B,A] = butter(N,Wn);
0081     y=filter(B,A,ones(nsamples,1));
0082     BETA0=[1, zeros(1,8), 1, zeros(1,8)];
0083     fun = @(beta,x)(filter([beta(1),beta(2),beta(3),beta(4),beta(5),beta(6),beta(7),beta(8),beta(9)],...
0084         [beta(10),beta(11),beta(12),beta(13),beta(14),beta(15),beta(16),beta(17),beta(18)],x));
0085     x=ones(nsamples,1);
0086     BETA = nlinfit(x,y,fun,BETA0);
0087     BETA=BETA/BETA(10);
0088     BB=BETA(1:9); AA=BETA(10:end);
0089     figure(1); clf;
0090     plot([y,filter(BB,AA,ones(size(y)))])
0091 end
0092 
0093 if 0
0094     N=8;
0095     Wn=0.25; % CTF corner frequency is 1/4 of sampling rate
0096     [B,A] = butter(N,Wn);
0097     x=[zeros(1100,1);ones(2000,1)];
0098     x=filter(B,A,x);
0099     x=x+0.01*randn(size(x));
0100     [y,stepList]=nt_destep(x);
0101     figure(1); clf;
0102     subplot 211;
0103     plot([x,y]); legend('raw','step removed')
0104     subplot 212;
0105     plot([y,nt_deglitch(y,stepList)]); legend('step removed', 'deglitched');
0106 end
0107 if 0
0108     N=8;
0109     Wn=0.25; % CTF corner frequency is 1/4 of sampling rate
0110     [B,A] = butter(N,Wn);
0111     x=[zeros(1100,1);ones(1100,1);2*ones(1100,1);3*ones(1100,1);4*ones(1100,1);0*ones(1100,1)];
0112     %x=filter(B,A,x);
0113     x=x+0.0*randn(size(x));
0114     nt_destep(x);
0115 end
0116 if 0
0117     % this example needs fixing
0118     x=ft_read_data('/data/meg/litvak/phantom090715_BrainampDBS_20150709_18.ds'); x=permute(x,[2,1,3]); x=x(:,33:306,:);
0119     x=x(:,100,1);
0120     [y,stepList]=nt_destep(x,[],[],30);
0121     figure(1); subplot 211; plot(x);
0122     subplot 212; plot(nt_deglitch(y,stepList));
0123 end
0124 
0125

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