% function np=interpoint(y,de,tau,bins,nref,nt)%% calculate the number of interpoint distances of the time series y% embedded in dimension de (can be a vector) with lag tau (must be% a scalar) in the bins specified by bins. % I.e.%  np(k) is *approximately* the number of pairs of points x(:,i)%  and x(:,j) (with |j-i|>nt) such that%                bins(k-1)<||x(:,i)-x(:,j)||<bins(k)           %  [assuming bins(0)=0]%% If nref>0 then do the calculation only for nref randomly chosen % *pairs* of points (x(:,i),x(:,j)).% If nref==0 then do the calculation for all the embedded data%% de vector of embedding dimensions% embedding lag% nt is the Theiler window (default nt=0)% nref is the number of (randomly chosen) pairs (x(:,i),x(:,j))% bins are the k bin sizes (must be ascending)% y is a 1-by-n vector: the (unembedded) time series%% NOTE: because all the computations are done at once, we save some% time, but the length of the data available for lower dimensional% embeddings is reduced (as a matter of convenience) to be the same% as the highest dimensional embedding.% NOTE: If nt=0 then exclude nothing (include i=j), if nt=1 exclude% *only* i=j. Hence, if nt=0 and nref=0 the lowest bin will always have% at least n-de+1 occupants!%% see also interbin and interbinref%%% For more info, read README%% Michael Small% ensmall@polyu.edu.hk% 30/4/02