PositiveSideGhostTrackFitter.cc

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#include <cmath>
#include <vector>

#include "FWCore/MessageLogger/interface/MessageLogger.h"
#include "DataFormats/GeometryVector/interface/GlobalVector.h"
#include "DataFormats/GeometryVector/interface/GlobalPoint.h"

#include "RecoVertex/GhostTrackFitter/interface/GhostTrackState.h"
#include "RecoVertex/GhostTrackFitter/interface/GhostTrackPrediction.h"

#include "RecoVertex/GhostTrackFitter/interface/PositiveSideGhostTrackFitter.h"

using namespace reco;

GhostTrackPrediction PositiveSideGhostTrackFitter::fit(const GhostTrackFitter::PredictionUpdater &updater,
                                                       const GhostTrackPrediction &prior,
                                                       std::vector<GhostTrackState> &states,
                                                       double &ndof,
                                                       double &chi2) {
  double rho = prior.rho();
  for (unsigned int i = 0; i < states.size(); i++) {
    GhostTrackState &state = states[i];
    state.linearize(prior, true, .5 / rho);
  }

  GhostTrackPrediction pred = actualFitter_->fit(updater, prior, states, ndof, chi2);

  double origin = pred.lambda(origin_);
  bool done = true;
  for (unsigned int i = 0; i < states.size(); i++) {
    GhostTrackState &state = states[i];
    double lambda = state.lambda();
    if (lambda < origin && (origin - lambda) < 3.5) {
      GhostTrackState testState = state;
      testState.linearize(pred, 2. * origin - lambda);
      double ndof, chi2;

      if (testState.isValid()) {
        updater.contribution(prior, testState, ndof, chi2, true);
        if (ndof > 0. && chi2 < 10.) {
          state = testState;
          if (state.weight() != 1.)
            state.setWeight(3.);
          done = false;
        }
      } else {
        edm::LogError("InvalidGhostTrackState") << "Invalid GhostTrackState encountered!";
      }
    }
  }

  if (!done) {
    for (unsigned int i = 0; i < states.size(); i++) {
      GhostTrackState &state = states[i];
      double lambda = state.lambda();
      if (state.weight() != 1. && lambda < origin) {
        double weight = std::exp(10. * (origin - lambda) - .1);
        state.setWeight(std::min(state.weight(), weight));
      }
    }

    pred = actualFitter_->fit(updater, prior, states, ndof, chi2);
  }

  return pred;
}