reco::KalmanGhostTrackUpdater Class Reference

#include <KalmanGhostTrackUpdater.h>

Inheritance diagram for reco::KalmanGhostTrackUpdater:

Public Member Functions
KalmanGhostTrackUpdater *	clone () const override
void	contribution (const GhostTrackPrediction &pred, const GhostTrackState &state, double &ndof, double &chi2, bool withPredError=false) const override
GhostTrackPrediction	update (const GhostTrackPrediction &pred, const GhostTrackState &state, double &ndof, double &chi2) const override
	~KalmanGhostTrackUpdater () override
Public Member Functions inherited from reco::GhostTrackFitter::PredictionUpdater
virtual	~PredictionUpdater ()

Detailed Description

Definition at line 11 of file KalmanGhostTrackUpdater.h.

Constructor & Destructor Documentation

~KalmanGhostTrackUpdater()

reco::KalmanGhostTrackUpdater::~KalmanGhostTrackUpdater ( )

inlineoverride

Definition at line 13 of file KalmanGhostTrackUpdater.h.

{}

Member Function Documentation

clone()

KalmanGhostTrackUpdater* reco::KalmanGhostTrackUpdater::clone ( void  ) const

inlineoverridevirtual

Implements reco::GhostTrackFitter::PredictionUpdater.

Definition at line 15 of file KalmanGhostTrackUpdater.h.

{ return new KalmanGhostTrackUpdater(*this); }

contribution()

void KalmanGhostTrackUpdater::contribution ( const GhostTrackPrediction &  pred, const GhostTrackState &  state, double &  ndof, double &  chi2, bool  withPredError = false  ) const

overridevirtual

Implements reco::GhostTrackFitter::PredictionUpdater.

Definition at line 124 of file KalmanGhostTrackUpdater.cc.

References nano_mu_local_reco_cff::chi2, and ndof.

                                                                     {
  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);
}

update()

GhostTrackPrediction KalmanGhostTrackUpdater::update ( const GhostTrackPrediction &  pred, const GhostTrackState &  state, double &  ndof, double &  chi2  ) const

overridevirtual

Implements reco::GhostTrackFitter::PredictionUpdater.

Definition at line 84 of file KalmanGhostTrackUpdater.cc.

References nano_mu_local_reco_cff::chi2, reco::GhostTrackPrediction::covariance(), PedestalClient_cfi::gain, caHitNtupletGeneratorKernels::if(), ndof, and reco::GhostTrackPrediction::prediction().

Referenced by progressbar.ProgressBar::__next__(), MatrixUtil.Matrix::__setitem__(), MatrixUtil.Steps::__setitem__(), progressbar.ProgressBar::finish(), and MatrixUtil.Steps::overwrite().

                                                                         {
  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);
}