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);       
 
  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. 
 
static struct JTRIGGER::@76 clusterizeWeight
Anonymous struct for weighed clustering of hits. 
 
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. 
 
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