#include <KalmanGhostTrackUpdater.h>
Public Member Functions | |
virtual KalmanGhostTrackUpdater * | clone () const |
void | contribution (const GhostTrackPrediction &pred, const GhostTrackState &state, double &ndof, double &chi2, bool withPredError=false) const |
GhostTrackPrediction | update (const GhostTrackPrediction &pred, const GhostTrackState &state, double &ndof, double &chi2) const |
virtual | ~KalmanGhostTrackUpdater () |
Definition at line 11 of file KalmanGhostTrackUpdater.h.
virtual reco::KalmanGhostTrackUpdater::~KalmanGhostTrackUpdater | ( | ) | [inline, virtual] |
Definition at line 13 of file KalmanGhostTrackUpdater.h.
{}
virtual KalmanGhostTrackUpdater* reco::KalmanGhostTrackUpdater::clone | ( | void | ) | const [inline, virtual] |
Implements reco::GhostTrackFitter::PredictionUpdater.
Definition at line 15 of file KalmanGhostTrackUpdater.h.
{ return new KalmanGhostTrackUpdater(*this); }
void KalmanGhostTrackUpdater::contribution | ( | const GhostTrackPrediction & | pred, |
const GhostTrackState & | state, | ||
double & | ndof, | ||
double & | chi2, | ||
bool | withPredError = false |
||
) | const [virtual] |
Implements reco::GhostTrackFitter::PredictionUpdater.
Definition at line 128 of file KalmanGhostTrackUpdater.cc.
{ using namespace ROOT::Math; KalmanState kalmanState(pred, state); // this is called on the full predicted state, // so the residual is already with respect to the filtered state // inverted error Matrix2S invErr = kalmanState.measErr; if (withPredError) invErr += kalmanState.measPredErr; if (!invErr.Invert()) { ndof = 0.; chi2 = 0.; } ndof = 2.; chi2 = Similarity(kalmanState.residual, invErr); }
GhostTrackPrediction KalmanGhostTrackUpdater::update | ( | const GhostTrackPrediction & | pred, |
const GhostTrackState & | state, | ||
double & | ndof, | ||
double & | chi2 | ||
) | const [virtual] |
Implements reco::GhostTrackFitter::PredictionUpdater.
Definition at line 86 of file KalmanGhostTrackUpdater.cc.
References reco::GhostTrackPrediction::covariance(), reco::GhostTrackPrediction::prediction(), and reco::GhostTrackState::weight().
{ using namespace ROOT::Math; KalmanState kalmanState(pred, state); if (state.weight() < 1.0e-3) return pred; // inverted combined error Matrix2S invErr = kalmanState.measPredErr + (1.0 / state.weight()) * kalmanState.measErr; if (!invErr.Invert()) return pred; // gain Matrix42 gain = pred.covariance() * Transpose(kalmanState.h) * invErr; // new prediction Vector4 newPred = pred.prediction() + (gain * kalmanState.residual); Matrix44 tmp44 = SMatrixIdentity(); tmp44 = (tmp44 - gain * kalmanState.h) * pred.covariance(); Matrix4S newError(tmp44.LowerBlock()); // filtered residuals Matrix22 tmp22 = SMatrixIdentity(); tmp22 = tmp22 - kalmanState.h * gain; Vector2 filtRes = tmp22 * kalmanState.residual; tmp22 *= kalmanState.measErr; Matrix2S filtResErr(tmp22.LowerBlock()); if (!filtResErr.Invert()) return pred; ndof += state.weight() * 2.; chi2 += state.weight() * Similarity(filtRes, filtResErr); return GhostTrackPrediction(newPred, newError); }