matthiasm@8: function [dfout,m] = adapt_thresh(df,pre,post);
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: df = df(:)';
matthiasm@8: % uses juan's adaptive median threshold
matthiasm@8: 
matthiasm@8: alpha = 9;
matthiasm@8: thresh=0.033;
matthiasm@8: fn = @mean;
matthiasm@8: 
matthiasm@8: if(nargin<2)
matthiasm@8:     pre = 8;
matthiasm@8:     post = 7;
matthiasm@8: end
matthiasm@8: 
matthiasm@8: %df = df-min(df);
matthiasm@8: %alpha norm
matthiasm@8: %df = df/real(mean(abs(df+eps).^alpha).^(1/alpha));   
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: 
matthiasm@8: % low pass filtering
matthiasm@8: 
matthiasm@8: %[b,a]=butter(2,0.28);
matthiasm@8: 
matthiasm@8: %b = [0.1600 0.3200 0.1600];
matthiasm@8: %a = [1.0000 -0.5949 0.2348];
matthiasm@8: 
matthiasm@8: 
matthiasm@8: %df=filtfilt(b,a,df);
matthiasm@8: 
matthiasm@8: 
matthiasm@8: % median threshold
matthiasm@8: 
matthiasm@8: N=length(df);
matthiasm@8: 
matthiasm@8: for i=1:min(post,N)
matthiasm@8: 	k=min(i+pre,N);
matthiasm@8: 	m(i)=feval(fn,df(1:k));
matthiasm@8:   %  m2(i) = feval(@mean,df(1:k));
matthiasm@8: end
matthiasm@8: 
matthiasm@8: if N>(post+pre)
matthiasm@8: 	m=[m feval(fn,buffer(df,post+pre+1,post+pre,'nodelay'))];
matthiasm@8: end
matthiasm@8: 
matthiasm@8: % if N>(post+pre)
matthiasm@8: % 	m2=[m2 feval(@mean,buffer(df,post+pre+1,post+pre,'nodelay'))];
matthiasm@8: % end
matthiasm@8: 
matthiasm@8: for i=N+(1-pre:0)
matthiasm@8: 	j=max(i-post,1);
matthiasm@8: 	m(i)=feval(fn,df(j:end));
matthiasm@8: %    m2(i)=feval(@mean,df(j:end));
matthiasm@8: end
matthiasm@8: 
matthiasm@8: %df = (df- m*thresh);
matthiasm@8: df = df-m;
matthiasm@8: 
matthiasm@8: dfout = (df>0).*df;
matthiasm@8: %dfout = df;