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track.m
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track.m
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function tracks = track(xyzs,maxdisp,param)
%;
% ; see http://glinda.lrsm.upenn.edu/~weeks/idl
% ; for more information
% ;
% ;+
% ; NAME:
% ; track
% ; PURPOSE:
% ; Constructs n-dimensional trajectories from a scrambled list of
% ; particle coordinates determined at discrete times (e.g. in
% ; consecutive video frames).
% ; CATEGORY:
% ; Image Processing
% ; CALLING SEQUENCE:
% ; result = track( positionlist, maxdisp, param )
% ; set all keywords in the space below
% ; INPUTS:
% ; positionlist: an array listing the scrambled coordinates and data
% ; of the different particles at different times, such that:
% ; positionlist(0:d-1,*): contains the d coordinates and
% ; data for all the particles, at the different times. must be positve
% ; positionlist(d,*): contains the time t that the position
% ; was determined, must be integers (e.g. frame number. These values must
% ; be monotonically increasing and uniformly gridded in time.
% ; maxdisp: an estimate of the maximum distance that a particle
% ; would move in a single time interval.(see Restrictions)
% OPTIONAL INPUT:
% param: a structure containing a few tracking parameters that are
% needed for many applications. If param is not included in the
% function call, then default values are used. If you set one value
% make sure you set them all:
% ; param.mem: this is the number of time steps that a particle can be
% ; 'lost' and then recovered again. If the particle reappears
% ; after this number of frames has elapsed, it will be
% ; tracked as a new particle. The default setting is zero.
% ; this is useful if particles occasionally 'drop out' of
% ; the data.
% ; param.dim: if the user would like to unscramble non-coordinate data
% ; for the particles (e.g. apparent radius of gyration for
% ; the particle images), then positionlist should
% ; contain the position data in positionlist(0:param.dim-1,*)
% ; and the extra data in positionlist(param.dim:d-1,*). It is then
% ; necessary to set dim equal to the dimensionality of the
% ; coordinate data to so that the track knows to ignore the
% ; non-coordinate data in the construction of the
% ; trajectories. The default value is two.
% ; param.good: set this keyword to eliminate all trajectories with
% ; fewer than param.good valid positions. This is useful
% ; for eliminating very short, mostly 'lost' trajectories
% ; due to blinking 'noise' particles in the data stream.
%; param.quiet: set this keyword to 1 if you don't want any text
% ; OUTPUTS:
% ; result: a list containing the original data rows sorted
% ; into a series of trajectories. To the original input
% ; data structure there is appended an additional column
% ; containing a unique 'id number' for each identified
% ; particle trajectory. The result array is sorted so
% ; rows with corresponding id numbers are in contiguous
% ; blocks, with the time variable a monotonically
% ; increasing function inside each block. For example:
% ;
% ; For the input data structure (positionlist):
% ; (x) (y) (t)
% ; pos = 3.60000 5.00000 0.00000
% ; 15.1000 22.6000 0.00000
% ; 4.10000 5.50000 1.00000
% ; 15.9000 20.7000 2.00000
% ; 6.20000 4.30000 2.00000
% ;
% ; IDL> res = track(pos,5,mem=2)
% ;
% ; track will return the result 'res'
% ; (x) (y) (t) (id)
% ; res = 3.60000 5.00000 0.00000 0.00000
% ; 4.10000 5.50000 1.00000 0.00000
% ; 6.20000 4.30000 2.00000 0.00000
% ; 15.1000 22.6000 0.00000 1.00000
% ; 15.9000 20.7000 2.00000 1.00000
% ;
% ; NB: for t=1 in the example above, one particle temporarily
% ; vanished. As a result, the trajectory id=1 has one time
% ; missing, i.e. particle loss can cause time gaps to occur
% ; in the corresponding trajectory list. In contrast:
% ;
% ; IDL> res = track(pos,5)
% ;
% ; track will return the result 'res'
% ; (x) (y) (t) (id)
% ; res = 15.1000 22.6000 0.00000 0.00000
% ; 3.60000 5.00000 0.00000 1.00000
% ; 4.10000 5.50000 1.00000 1.00000
% ; 6.20000 4.30000 2.00000 1.00000
% ; 15.9000 20.7000 2.00000 2.00000
% ;
% ; where the reappeared 'particle' will be labelled as new
% ; rather than as a continuation of an old particle since
% ; mem=0. It is up to the user to decide what setting of
% ; 'mem' will yeild the highest fidelity .
% ;
% ; SIDE EFFECTS:
% ; Produces informational messages. Can be memory intensive for
% ; extremely large data sets.
% ; RESTRICTIONS:
% ; maxdisp should be set to a value somewhat less than the mean
% ; spacing between the particles. As maxdisp approaches the mean
% ; spacing the runtime will increase significantly. The function
% ; will produce an error message: "Excessive Combinatorics!" if
% ; the run time would be too long, and the user should respond
% ; by re-executing the function with a smaller value of maxdisp.
% ; Obviously, if the particles being tracked are frequently moving
% ; as much as their mean separation in a single time step, this
% ; function will not return acceptable trajectories.
% ; PROCEDURE:
% ; Given the positions for n particles at time t(i), and m possible
% ; new positions at time t(i+1), this function considers all possible
% ; identifications of the n old positions with the m new positions,
% ; and chooses that identification which results in the minimal total
% ; squared displacement. Those identifications which don't associate
% ; a new position within maxdisp of an old position ( particle loss )
% ; penalize the total squared displacement by maxdisp^2. For non-
% ; interacting Brownian particles with the same diffusivity, this
% ; algorithm will produce the most probable set of identifications
% ; ( provided maxdisp >> RMS displacement between frames ).
% ; In practice it works reasonably well for systems with oscillatory,
% ; ballistic, correlated and random hopping motion, so long as single
% ; time step displacements are reasonably small. NB: multidimensional
% ; functionality is intended to facilitate tracking when additional
% ; information regarding target identity is available (e.g. size or
% ; color). At present, this information should be rescaled by the
% ; user to have a comparable or smaller (measurement) variance than
% ; the spatial displacements.
% ;
% ; MODIFICATION HISTORY:
% ; 2/93 Written by John C. Crocker, University of Chicago (JFI).
% ; 7/93 JCC fixed bug causing particle loss and improved performance
% ; for large numbers of (>100) particles.
% ; 11/93 JCC improved speed and memory performance for large
% ; numbers of (>1000) particles (added subnetwork code).
% ; 3/94 JCC optimized run time for trivial bonds and d<7. (Added
% ; d-dimensional raster metric code.)
% ; 8/94 JCC added functionality to unscramble non-position data
% ; along with position data.
% ; 9/94 JCC rewrote subnetwork code and wrote new, more efficient
% ; permutation code.
% ; 5/95 JCC debugged subnetwork and excessive combinatorics code.
% ; 12/95 JCC added memory keyword, and enabled the tracking of
% ; newly appeared particles.
% ; 3/96 JCC made inipos a keyword, and disabled the adding of 'new'
% ; particles when inipos was set.
% ; 3/97 JCC added 'add' keyword, since Chicago users didn't like
% ; having particle addition be the default.
% ; 9/97 JCC added 'goodenough' keyword to improve memory efficiency
% ; when using the 'add' keyword and to filter out bad tracks.
% ; 10/97 JCC streamlined data structure to speed runtime for >200
% ; timesteps. Changed 'quiet' keyword to 'verbose'. Made
% ; time labelling more flexible (uniform and sorted is ok).
% ; 9/98 JCC switched trajectory data structure to a 'list' form,
% ; resolving memory issue for large, noisy datasets.
% ; 2/99 JCC added Eric Weeks's 'uberize' code to post-facto
% ; rationalize the particle id numbers, removed 'add' keyword.
% ; 1/05 Transmuted to MATLAB by D. Blair
% ; 5/05 ERD Added the param structure to simplify calling.
% 6/05 ERD Added quiet to param structure
% 7/05 DLB Fixed slight bug in trivial bond code
% 3/07 DLB Fixed bug with max disp pointed out by Helene Delanoe-Ayari
%
% ; This code 'track.pro' is copyright 1999, by John C. Crocker.
% ; It should be considered 'freeware'- and may be distributed freely
% ; (outside of the military-industrial complex) in its original form
% ; when properly attributed.
% ;
% ;-
dd = length(xyzs(1,:));
%use default parameters if none given
if nargin==2
%default values
memory_b=0; % if mem is not needed set to zero
goodenough = 0; % if goodenough is not wanted set to zero
dim = dd - 1;
quiet=0;
else
memory_b = param.mem;
goodenough = param.good;
dim = param.dim;
quiet = param.quiet;
end
% checking the input time vector
t = xyzs(:,dd);
st = circshift(t,1);
st = t(2:end) - st(2:end);
if sum(st(find(st < 0))) ~= 0
disp('The time vectors is not in order')
return
end
info = 1;
w = find(st > 0);
z = length(w);
z = z +1;
if isempty(w)
disp('All positions are at the same time... go back!')
return
end
% partitioning the data with unique times
%res = unq(t);
% implanting unq directly
indices = find(t ~= circshift(t,-1));
count = length(indices);
if count > 0
res = indices;
else
res = length(t) -1;
end
%%%%%%%%%%%%%%%%%%%%%%%
res = [1,res',length(t)];
ngood = res(2) - res(1) + 1;
eyes = 1:ngood;
pos = xyzs(eyes,1:dim);
istart = 2;
n = ngood;
zspan = 50;
if n > 200
zspan = 20;
end
if n > 500
zspan = 10;
end
resx = zeros(zspan,n) - 1;
bigresx = zeros(z,n) - 1;
mem = zeros(n,1);
% whos resx
% whos bigresx
uniqid = 1:n;
maxid = n;
olist = [0.,0.];
if goodenough > 0
dumphash = zeros(n,1);
nvalid = ones(n,1);
end
% whos eyes;
resx(1,:) = eyes;
% setting up constants
maxdisq = maxdisp^2;
% John calls this the setup for "fancy code" ???
notnsqrd = (sqrt(n*ngood) > 200) & (dim < 7);
notnsqrd = notnsqrd(1);
if notnsqrd
%; construct the vertices of a 3x3x3... d-dimensional hypercube
cube = zeros(3^dim,dim);
for d=0:dim-1,
numb = 0;
for j=0:(3^d):(3^dim)-1,
cube(j+1:j+(3^(d)),d+1) = numb;
numb = mod(numb+1,3);
end
end
% calculate a blocksize which may be greater than maxdisp, but which
% keeps nblocks reasonably small.
volume = 1;
for d = 0:dim-1
minn = min(xyzs(w,d+1));
maxx = max(xyzs(w,d+1));
volume = volume * (maxx-minn);
end
volume;
blocksize = max( [maxdisp,((volume)/(20*ngood))^(1.0/dim)] );
end
% Start the main loop over the frames.
for i=istart:z
ispan = mod(i-1,zspan)+1;
%disp(ispan)
% get new particle positions
m = res(i+1) - res(i);
res(i);
eyes = 1:m;
eyes = eyes + res(i);
if m > 0
xyi = xyzs(eyes,1:dim);
found = zeros(m,1);
% THE TRIVIAL BOND CODE BEGINS
if notnsqrd
%Use the raster metric code to do trivial bonds
% construct "s", a one dimensional parameterization of the space
% which consists of the d-dimensional raster scan of the volume.)
abi = fix(xyi./blocksize);
abpos = fix(pos./blocksize);
si = zeros(m,1);
spos = zeros(n,1);
dimm = zeros(dim,1);
coff = 1.;
for j=1:dim
minn = min([abi(:,j);abpos(:,j)]);
maxx = max([abi(:,j);abpos(:,j)]);
abi(:,j) = abi(:,j) - minn;
abpos(:,j) = abpos(:,j) - minn;
dimm(j) = maxx-minn + 1;
si = si + abi(:,j).*coff;
spos = spos + abpos(:,j).*coff;
coff = dimm(j).*coff;
end
nblocks = coff;
% trim down (intersect) the hypercube if its too big to fit in the
% particle volume. (i.e. if dimm(j) lt 3)
cub = cube;
deg = find( dimm < 3);
if ~isempty(deg)
for j = 0:length(deg)-1
cub = cub(find(cub(:,deg(j+1)) < dimm(deg(j+1))),:);
end
end
% calculate the "s" coordinates of hypercube (with a corner @ the origin)
scube = zeros(length(cub(:,1)),1);
coff = 1;
for j=1:dim
scube = scube + cub(:,j).*coff;
coff = coff*dimm(j);
end
% shift the hypercube "s" coordinates to be centered around the origin
coff = 1;
for j=1:dim
if dimm(j) > 3
scube = scube - coff;
end
coff = dimm(j).* coff;
end
scube = mod((scube + nblocks),nblocks);
% get the sorting for the particles by their "s" positions.
[ed,isort] = sort(si);
% make a hash table which will allow us to know which new particles
% are at a given si.
strt = zeros(nblocks,1) -1;
fnsh = zeros(nblocks,1);
h = find(si == 0);
lh = length(h);
if lh > 0
si(h) = 1;
end
for j=1:m
if strt(si(isort(j))) == -1
strt(si(isort(j))) = j;
fnsh(si(isort(j))) = j;
else
fnsh(si(isort(j))) = j;
end
end
if lh > 0
si(h) = 0;
end
coltot = zeros(m,1);
rowtot = zeros(n,1);
which1 = zeros(n,1);
for j=1:n
map = fix(-1);
scub_spos = scube + spos(j);
s = mod(scub_spos,nblocks);
whzero = find(s == 0 );
if ~isempty(whzero)
nfk = find(s ~=0);
s = s(nfk);
end
w = find(strt(s) ~= -1);
ngood = length(w);
ltmax=0;
if ngood ~= 0
s = s(w);
for k=1:ngood
map = [map;isort( strt(s(k)):fnsh(s(k)))];
end
map = map(2:end);
% if length(map) == 2
% if (map(1) - map(2)) == 0
% map = unique(map);
% end
% end
% map = map(umap);
%end
% find those trival bonds
distq = zeros(length(map),1);
for d=1:dim
distq = distq + (xyi(map,d) - pos(j,d)).^2;
end
ltmax = distq < maxdisq;
rowtot(j) = sum(ltmax);
if rowtot(j) >= 1
w = find(ltmax == 1);
coltot( map(w) ) = coltot( map(w)) +1;
which1(j) = map( w(1) );
end
end
end
ntrk = fix(n - sum(rowtot == 0));
w = find( rowtot == 1);
ngood = length(w);
if ngood ~= 0
ww = find(coltot( which1(w) ) == 1);
ngood = length(ww);
if ngood ~= 0
%disp(size(w(ww)))
resx(ispan,w(ww)) = eyes( which1(w(ww)));
found( which1( w(ww))) = 1;
rowtot( w(ww)) = 0;
coltot( which1(w(ww))) = 0;
end
end
labely = find( rowtot > 0);
ngood = length(labely);
if ngood ~= 0
labelx = find( coltot > 0);
nontrivial = 1;
else
nontrivial = 0;
end
else
% or: Use simple N^2 time routine to calculate trivial bonds
% let's try a nice, loopless way!
% don't bother tracking perm. lost guys.
wh = find( pos(:,1) >= 0);
ntrack = length(wh);
if ntrack == 0
'There are no valid particles to track idiot!'
break
end
xmat = zeros(ntrack,m);
count = 0;
for kk=1:ntrack
for ll=1:m
xmat(kk,ll) = count;
count = count+1;
end
end
count = 0;
for kk=1:m
for ll=1:ntrack
ymat(kk,ll) = count;
count = count+1;
end
end
xmat = (mod(xmat,m) + 1);
ymat = (mod(ymat,ntrack) +1)';
[lenxn,lenxm] = size(xmat);
% whos ymat
% whos xmat
% disp(m)
for d=1:dim
x = xyi(:,d);
y = pos(wh,d);
xm = x(xmat);
ym = y(ymat(1:lenxn,1:lenxm));
if size(xm) ~= size(ym)
xm = xm';
end
if d == 1
dq = (xm -ym).^2;
%dq = (x(xmat)-y(ymat(1:lenxn,1:lenxm))).^2;
else
dq = dq + (xm-ym).^2;
%dq = dq + (x(xmat)-y(ymat(1:lenxn,1:lenxm)) ).^2;
end
end
ltmax = dq < maxdisq;
% figure out which trivial bonds go with which
rowtot = zeros(n,1);
rowtot(wh) = sum(ltmax,2);
if ntrack > 1
coltot = sum(ltmax,1);
else
coltot = ltmax;
end
which1 = zeros(n,1);
for j=1:ntrack
[mx, w] = max(ltmax(j,:));
which1(wh(j)) = w;
end
ntrk = fix( n - sum(rowtot == 0));
w= find( rowtot == 1) ;
ngood = length(w);
if ngood ~= 0
ww = find(coltot(which1(w)) == 1);
ngood = length(ww);
if ngood ~= 0
resx( ispan, w(ww) ) = eyes( which1( w(ww)));
found(which1( w(ww))) = 1;
rowtot(w(ww)) = 0;
coltot(which1(w(ww))) = 0;
end
end
labely = find( rowtot > 0);
ngood = length(labely);
if ngood ~= 0
labelx = find( coltot > 0);
nontrivial = 1;
else
nontrivial = 0;
end
end
%THE TRIVIAL BOND CODE ENDS
if nontrivial
xdim = length(labelx);
ydim = length(labely);
% make a list of the non-trivial bonds
bonds = zeros(1,2);
bondlen = 0;
for j=1:ydim
distq = zeros(xdim,1);
for d=1:dim
%distq
distq = distq + (xyi(labelx,d) - pos(labely(j),d)).^2;
%distq
end
w= find(distq < maxdisq)' - 1;
ngood = length(w);
newb = [w;(zeros(1,ngood)+j)];
bonds = [bonds;newb'];
bondlen = [ bondlen;distq( w + 1) ];
end
bonds = bonds(2:end,:);
bondlen = bondlen(2:end);
numbonds = length(bonds(:,1));
mbonds = bonds;
max([xdim,ydim]);
if max([xdim,ydim]) < 4
nclust = 1;
maxsz = 0;
mxsz = xdim;
mysz = ydim;
bmap = zeros(length(bonds(:,1)+1),1) - 1;
else
% THE SUBNETWORK CODE BEGINS
lista = zeros(numbonds,1);
listb = zeros(numbonds,1);
nclust = 0;
maxsz = 0;
thru = xdim;
while thru ~= 0
% the following code extracts connected
% sub-networks of the non-trivial
% bonds. NB: lista/b can have redundant entries due to
% multiple-connected subnetworks
w = find(bonds(:,2) >= 0);
% size(w)
lista(1) = bonds(w(1),2);
listb(1) = bonds(w(1),1);
bonds(w(1),:) = -(nclust+1);
bonds;
adda = 1;
addb = 1;
donea = 0;
doneb = 0;
if (donea ~= adda) | (doneb ~= addb)
true = 0;
else
true = 1;
end
while ~true
if (donea ~= adda)
w = find(bonds(:,2) == lista(donea+1));
ngood = length(w);
if ngood ~= 0
listb(addb+1:addb+ngood,1) = bonds(w,1);
bonds(w,:) = -(nclust+1);
addb = addb+ngood;
end
donea = donea+1;
end
if (doneb ~= addb)
w = find(bonds(:,1) == listb(doneb+1));
ngood = length(w);
if ngood ~= 0
lista(adda+1:adda+ngood,1) = bonds(w,2);
bonds(w,:) = -(nclust+1);
adda = adda+ngood;
end
doneb = doneb+1;
end
if (donea ~= adda) | (doneb ~= addb)
true = 0;
else
true = 1;
end
end
[pp,pqx] = sort(listb(1:doneb));
%unx = unq(listb(1:doneb),pqx);
%implanting unq directly
arr = listb(1:doneb);
q = arr(pqx);
indices = find(q ~= circshift(q,-1));
count = length(indices);
if count > 0
unx = pqx(indices);
else
unx = length(q) -1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
xsz = length(unx);
[pp,pqy] = sort(lista(1:donea));
%uny = unq(lista(1:donea),pqy);
%implanting unq directly
arr = lista(1:donea);
q = arr(pqy);
indices = find(q ~= circshift(q,-1));
count = length(indices);
if count > 0
uny = pqy(indices);
else
uny = length(q) -1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ysz = length(uny);
if xsz*ysz > maxsz
maxsz = xsz*ysz;
mxsz = xsz;
mysz = ysz;
end
thru = thru -xsz;
nclust = nclust + 1;
end
bmap = bonds(:,2);
end
% THE SUBNETWORK CODE ENDS
% put verbose in for Jaci
% THE PERMUTATION CODE BEGINS
for nc =1:nclust
w = find( bmap == -1*(nc));
nbonds = length(w);
bonds = mbonds(w,:);
lensq = bondlen(w);
[pq,st] = sort( bonds(:,1));
%un = unq(bonds(:,1),st);
%implanting unq directly
arr = bonds(:,1);
q = arr(st);
indices = find(q ~= circshift(q,-1));
count = length(indices);
if count > 0
un = st(indices);
else
un = length(q) -1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
uold = bonds(un,1);
nold = length(uold);
%un = unq(bonds(:,2));
%implanting unq directly
indices = find(bonds(:,2) ~= circshift(bonds(:,2),-1));
count = length(indices);
if count > 0
un = indices;
else
un = length(bonds(:,2)) -1;
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
unew = bonds(un,2);
nnew = length(unew);
if nnew > 5
rnsteps = 1;
for ii =1:nnew
rnsteps = rnsteps * length( find(bonds(:,2) == ...
unew(ii)));
if rnsteps > 5.e+4
disp('Warning: difficult combinatorics encountered.')
end
if rnsteps > 2.e+5
disp(['Excessive Combinitorics you FOOL LOOK WHAT YOU HAVE' ...
' DONE TO ME!!!'])
return
end
end
end
st = zeros(nnew,1);
fi = zeros(nnew,1);
h = zeros(nbonds,1);
ok = ones(nold,1);
nlost = (nnew - nold) > 0;
for ii=1:nold
h(find(bonds(:,1) == uold(ii))) = ii;
end
st(1) = 1 ;
fi(nnew) = nbonds; % check this later
if nnew > 1
sb = bonds(:,2);
sbr = circshift(sb,1);
sbl = circshift(sb,-1);
st(2:end) = find( sb(2:end) ~= sbr(2:end)) + 1;
fi(1:nnew-1) = find( sb(1:nbonds-1) ~= sbl(1:nbonds-1));
end
% if i-1 == 13
% hi
% end
checkflag = 0;
while checkflag ~= 2
pt = st -1;
lost = zeros(nnew,1);
who = 0;
losttot = 0;
mndisq = nnew*maxdisq;
while who ~= -1
if pt(who+1) ~= fi(who+1)
w = find( ok( h( pt( who+1 )+1:fi( who+1 ) ) ) ); % check this -1
ngood = length(w);
if ngood > 0
if pt(who+1) ~= st(who+1)-1
ok(h(pt(who+1))) = 1;
end
pt(who+1) = pt(who+1) + w(1);
ok(h(pt(who+1))) = 0;
if who == nnew -1
ww = find( lost == 0);
dsq = sum(lensq(pt(ww))) + losttot*maxdisq;
if dsq < mndisq
minbonds = pt(ww);
mndisq = dsq;
end
else
who = who+1;
end
else
if ~lost(who+1) & (losttot ~= nlost)
lost(who+1) = 1;
losttot = losttot + 1;
if pt(who+1) ~= st(who+1) -1;
ok(h(pt(who+1))) = 1;
end
if who == nnew-1
ww = find( lost == 0);
dsq = sum(lensq(pt(ww))) + losttot*maxdisq;
if dsq < mndisq
minbonds = pt(ww);
mndisq = dsq;
end
else
who = who + 1;
end
else
if pt(who+1) ~= (st(who+1) -1)
ok(h(pt(who+1))) = 1;
end
pt(who+1) = st(who+1) -1;
if lost(who+1)
lost(who+1) = 0;
losttot = losttot -1;
end
who = who -1;
end
end
else
if ~lost(who+1) & (losttot ~= nlost)
lost(who+1) = 1;
losttot = losttot + 1;
if pt(who+1) ~= st(who+1)-1
ok(h(pt(who+1))) = 1;
end
if who == nnew -1
ww = find( lost == 0);
dsq = sum(lensq(pt(ww))) + losttot*maxdisq;
if dsq < mndisq
minbonds = pt(ww);
mndisq = dsq;
end
else
who = who + 1;
end
else
if pt(who+1) ~= st(who+1) -1
ok(h(pt(who+1))) = 1;
end
pt(who+1) = st(who+1) -1;
if lost(who+1)
lost(who+1) = 0;
losttot = losttot -1;
end
who = who -1;
end
end
end
checkflag = checkflag + 1;
if checkflag == 1
plost = min([fix(mndisq/maxdisq) , (nnew -1)]);
if plost > nlost
nlost = plost;
else
checkflag = 2;
end
end
end
% update resx using the minimum bond configuration
resx(ispan,labely(bonds(minbonds,2))) = eyes(labelx(bonds(minbonds,1)+1));
found(labelx(bonds(minbonds,1)+1)) = 1;
end
% THE PERMUTATION CODE ENDS
end
w = find(resx(ispan,:) >= 0);
nww = length(w);
if nww > 0
pos(w,:) = xyzs( resx(ispan,w) , 1:dim);
if goodenough > 0
nvalid(w) = nvalid(w) + 1;
end
end %go back and add goodenough keyword thing
newguys = find(found == 0);
nnew = length(newguys);
if (nnew > 0) % & another keyword to workout inipos
newarr = zeros(zspan,nnew) -1;
resx = [resx,newarr];
resx(ispan,n+1:end) = eyes(newguys);
pos = [[pos];[xyzs(eyes(newguys),1:dim)]];
nmem = zeros(nnew,1);
mem = [mem;nmem];
nun = 1:nnew;
uniqid = [uniqid,((nun) + maxid)];
maxid = maxid + nnew;
if goodenough > 0
dumphash = [dumphash;zeros(1,nnew)'];
nvalid = [nvalid;zeros(1,nnew)'+1];
end
% put in goodenough
n = n + nnew;
end
else
' Warning- No positions found for t='
end
w = find( resx(ispan,:) ~= -1);
nok = length(w);
if nok ~= 0
mem(w) =0;
end
mem = mem + (resx(ispan,:)' == -1);
wlost = find(mem == memory_b+1);
nlost =length(wlost);
if nlost > 0
pos(wlost,:) = -maxdisp;
if goodenough > 0
wdump = find(nvalid(wlost) < goodenough);
ndump = length(wdump);
if ndump > 0
dumphash(wlost(wdump)) = 1;
end
end
% put in goodenough keyword stuff if
end
if (ispan == zspan) | (i == z)
nold = length(bigresx(1,:));
nnew = n-nold;
if nnew > 0
newarr = zeros(z,nnew) -1;
bigresx = [bigresx,newarr];
end
if goodenough > 0
if (sum(dumphash)) > 0
wkeep = find(dumphash == 0);
nkeep = length(wkeep);
resx = resx(:,wkeep);
bigresx = bigresx(:,wkeep);
pos = pos(wkeep,:);
mem = mem(wkeep);
uniqid = uniqid(wkeep);
nvalid = nvalid(wkeep);
n = nkeep;
dumphash = zeros(nkeep,1);
end
end
% again goodenough keyword
if quiet~=1
disp(strcat(num2str(i), ' of ' ,num2str(z), ' done. Tracking ',num2str(ntrk),' particles ', num2str(n),' tracks total'));
end
bigresx(i-(ispan)+1:i,:) = resx(1:ispan,:);
resx = zeros(zspan,n) - 1;