 |
Belle II Software
release-05-01-25
|
10 #include <tracking/trackFindingCDC/geometry/UncertainPerigeeCircle.h>
12 #include <tracking/trackFindingCDC/geometry/PerigeeCircle.h>
13 #include <tracking/trackFindingCDC/geometry/PerigeeParameters.h>
18 using namespace TrackFindingCDC;
20 UncertainPerigeeCircle
43 return output <<
"UncertainPerigeeCircle("
44 <<
"curvature=" << circle->
curvature() <<
","
45 <<
"phi0=" << circle->
phi0() <<
","
46 <<
"impact=" << circle->
impact() <<
")";
static double average(const PerigeeUtil::ParameterVector &fromPar, const PerigeeUtil::CovarianceMatrix &fromCov, const PerigeeUtil::ParameterVector &toPar, const PerigeeUtil::CovarianceMatrix &toCov, PerigeeUtil::ParameterVector &avgPar, PerigeeUtil::CovarianceMatrix &avgCov)
Calculates the weighted average between two perigee parameter sets with their respective covariance m...
std::ostream & operator<<(std::ostream &output, const IntervalOfValidity &iov)
const PerigeeCovariance & perigeeCovariance() const
Getter for the whole covariance matrix of the perigee parameters.
std::size_t ndf() const
Getter for the number of degrees of freediom used in the circle fit.
double impact() const
Getter for the signed distance of the origin to the circle.
Adds an uncertainty matrix to the circle in perigee parameterisation.
double chi2() const
Getter for the chi square value of the circle fit.
Abstract base class for different kinds of events.
double phi0() const
Getter for the azimuth angle of the direction of flight at the perigee.
UncertainPerigeeCircle()
Default constructor for ROOT compatibility.
A matrix implementation to be used as an interface typ through out the track finder.
double curvature() const
Getter for the signed curvature.
PerigeeParameters perigeeParameters() const
Getter for the perigee parameters in the order defined by EPerigeeParameter.h.
static UncertainPerigeeCircle average(const UncertainPerigeeCircle &fromPerigeeCircle, const UncertainPerigeeCircle &toPerigeeCircle)
Average the parameters of the two given perigee circles properly considering their covariance matrix.