KarimakisMethod Class Reference

Class implementing the Karimaki fit for two dimensional trajectory circle. More...

#include <KarimakisMethod.h>

Inheritance diagram for KarimakisMethod:

Public Member Functions
	KarimakisMethod ()
	Constructor setting the default constraints.
void	update (CDCTrajectory2D &trajectory2D, CDCObservations2D &observations2D) const
	Executes the fit and updates the trajectory parameters. This may render the information in the observation object.
bool	isLineConstrained () const
	Getter for the indictor that lines should be fitted by this fitter.
void	setLineConstrained (bool constrained=true)
	Indicator if this fitter is setup to fit lines.

Private Member Functions
UncertainPerigeeCircle	fitInternal (CDCObservations2D &observations2D) const
	Internal method doing the heavy work.

Private Attributes
bool	m_lineConstrained
	Memory for the flag indicating that lines should be fitted.

Detailed Description

Class implementing the Karimaki fit for two dimensional trajectory circle.

Definition at line 21 of file KarimakisMethod.h.

Constructor & Destructor Documentation

KarimakisMethod()

KarimakisMethod

(

)

Constructor setting the default constraints.

Definition at line 24 of file KarimakisMethod.cc.

  : m_lineConstrained(false)
{
}

Member Function Documentation

fitInternal()

UncertainPerigeeCircle fitInternal ( CDCObservations2D &  observations2D ) const

private

Internal method doing the heavy work.

Definition at line 214 of file KarimakisMethod.cc.

{
  // Matrix of weighted sums
  Eigen::Matrix< double, 4, 4> sNoL = getWXYRSumMatrix(observations2D);
 
  // Matrix of averages
  Eigen::Matrix<double, 4, 4> aNoL = sNoL / sNoL(iW);
 
  // Measurement means
  Eigen::Matrix<double, 4, 1> meansNoL = aNoL.row(iW);
 
  // Covariance matrix
  Eigen::Matrix<double, 4, 4> cNoL = aNoL - meansNoL * meansNoL.transpose();
 
  // Determine NDF : Circle fit eats up to 3 degrees of freedom debpending on the constraints
  size_t ndf = observations2D.size() - 2;
 
  if (not isLineConstrained()) {
    --ndf;
  }
 
  // Parameters to be fitted
  UncertainPerigeeCircle resultCircle = fitKarimaki(sNoL(iW), meansNoL, cNoL, isLineConstrained());
  double chi2 = calcChi2Karimaki(resultCircle, sNoL(iW), cNoL);
 
  PerigeePrecision perigeePrecision = calcPrecisionKarimaki(resultCircle, sNoL, isLineConstrained());
 
  // Use in pivotingin caset the matrix is not full rank as is for the constrained cases-
  PerigeeCovariance perigeeCovariance = PerigeeUtil::covarianceFromPrecision(perigeePrecision);
 
  resultCircle.setChi2(chi2);
  resultCircle.setNDF(ndf);
  resultCircle.setPerigeeCovariance(perigeeCovariance);
  return resultCircle;
}

isLineConstrained()

bool isLineConstrained ( ) const

inline

Getter for the indictor that lines should be fitted by this fitter.

Definition at line 36 of file KarimakisMethod.h.

      {
        return m_lineConstrained;
      }

setLineConstrained()

void setLineConstrained ( bool  constrained = true )

inline

Indicator if this fitter is setup to fit lines.

Definition at line 42 of file KarimakisMethod.h.

      {
        m_lineConstrained = constrained;
      }

update()

void update	(	CDCTrajectory2D &	trajectory2D,
		CDCObservations2D &	observations2D
	)		const

Executes the fit and updates the trajectory parameters. This may render the information in the observation object.

Definition at line 29 of file KarimakisMethod.cc.

{
  size_t nObservations = observations2D.size();
  trajectory2D.clear();
  if (not nObservations) return;
 
  Vector2D ref = observations2D.getCentralPoint();
  observations2D.passiveMoveBy(ref);
 
  UncertainPerigeeCircle perigeeCircle = fitInternal(observations2D);
 
  double frontX = observations2D.getX(0);
  double frontY = observations2D.getY(0);
  Vector2D frontPos(frontX, frontY);
 
  double backX = observations2D.getX(nObservations - 1);
  double backY = observations2D.getY(nObservations - 1);
  Vector2D backPos(backX, backY);
 
  Vector2D overPos(0, 0);
  double totalPerps = (perigeeCircle->arcLengthBetween(frontPos, overPos) +
                       perigeeCircle->arcLengthBetween(overPos, backPos));
 
  if (totalPerps < 0) {
    perigeeCircle.reverse();
  }
 
  trajectory2D.setLocalOrigin(ref);
  trajectory2D.setLocalCircle(perigeeCircle);
}

Member Data Documentation

m_lineConstrained

bool m_lineConstrained

private

Memory for the flag indicating that lines should be fitted.

Definition at line 49 of file KarimakisMethod.h.

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The documentation for this class was generated from the following files:

• tracking/trackFindingCDC/fitting/include/KarimakisMethod.h
• tracking/trackFindingCDC/fitting/src/KarimakisMethod.cc