Declaration of the operator that performs the reconstruction. 
   82       const double STANDARD_DEVIATIONS       = 3.0;
 
  105       copy(dataL1.begin(), dataL1.end(), back_inserter(dataL0));
 
  107       for (buffer_type::const_iterator i = buffer.begin(); i != buffer.end(); ++i) {
 
  109         if (find_if(dataL1.begin(), dataL1.end(), match_t(*i, 
TMaxLocal_ns)) == dataL1.end()) {
 
  110           dataL0.push_back(*i); 
 
  114       for (buffer_type::const_iterator 
root = dataL1.begin(); 
root != dataL1.end(); ++
root) {
 
  116         buffer_type data(1, *
root);
 
  120         for (buffer_type::const_iterator i = dataL0.begin(); i != dataL0.end(); ++i) {
 
  122           if(( 
root->getModuleIdentifier() != i->getModuleIdentifier() ) && matching(*i)){
 
  127         buffer_type::iterator __end1 = 
clusterizeWeight(data.begin() + 1, data.end(), match3G);
 
  132         double    chi2 = numeric_limits<double>::max();
 
  133         int       NDF  = 
distance(data.begin(), __end1) - JEstimator_t::NUMBER_OF_PARAMETERS;
 
  138           double ymin = numeric_limits<double>::max();
 
  140           buffer_type::iterator __end2 = __end1;
 
  143                  JEstimator_t::NUMBER_OF_PARAMETERS; ++
n, --__end2) {
 
  145             sort(data.begin() + 1, __end1, compare);
 
  150                 fit(data.begin(), __end2);
 
  158                   NDF  = 
distance(data.begin(), __end2) - JEstimator_t::NUMBER_OF_PARAMETERS;
 
  166             ymin -= STANDARD_DEVIATIONS * STANDARD_DEVIATIONS;
 
  171           const int number_of_outliers = 
distance(data.begin(), __end1) - JEstimator_t::NUMBER_OF_PARAMETERS - 1;
 
  173           buffer_type::iterator __end2 = __end1;
 
  175           for (
int n = 0; n <= number_of_outliers; ++
n) {         
 
  179               fit(data.begin(), __end2);
 
  182               NDF  = 
distance(data.begin(), __end2) - JEstimator_t::NUMBER_OF_PARAMETERS;
 
  189             buffer_type::iterator imax = __end2;
 
  191             for (buffer_type::iterator i = data.begin() + 1; i != __end2; ++i) {
 
  201             if (ymax > STANDARD_DEVIATIONS * STANDARD_DEVIATIONS) {     
 
  203               swap(*imax, *__end2);       
 
  210         if (NDF >= 0 && chi2 > numeric_limits<double>::lowest()) {
 
  216           out.rbegin()->setW(13, chi2);
 
  217           out.rbegin()->setW(14, N);           
 
JBinder2nd< JHit_t > JBind2nd(const JMatch< JHit_t > &match, const JHit_t &second)
Auxiliary method to create JBinder2nd object. 
 
Linear fit of bright point (position and time) between hits (objects with position and time)...
 
std::vector< T >::difference_type distance(typename std::vector< T >::const_iterator first, typename PhysicsEvent::const_iterator< T > second)
Specialisation of STL distance. 
 
Data structure for vertex fit. 
 
then JPlot1D f $WORKDIR postfit[prefit\] root
 
Auxiliary class to convert binary JMatch operator and given hit to unary match operator. 
 
double getQuality(const double chi2, const int N, const int NDF)
Get quality of fit. 
 
static const int JSHOWERPREFIT
 
const JModuleRouter & router
 
Data structure for L2 parameters. 
 
JFit getFit(const JHistory &history, const JTrack3D &track, const double Q, const int NDF, const double energy=0.0, const int status=0)
Get fit. 
 
Auxiliary class for permutations of L1 hits. 
 
alias put_queue eval echo n
 
int getCount(const T &hit)
Get hit count. 
 
void copy(const Head &from, JHead &to)
Copy header from from to to. 
 
Reduced data structure for L1 hit. 
 
static struct JTRIGGER::@78 clusterizeWeight
Anonymous struct for weighed clustering of hits. 
 
double getChi2(const double P)
Get chi2 corresponding to given probability. 
 
Data structure for normalised vector in positive z-direction. 
 
then usage $script[input file[working directory[option]]] nWhere option can be N