TrackFitterLikelihoodProcessor : This class takes post-amplified data from a readout pad and reconstructs the track based on the location of each signal. More...
#include <TrackFitterLikelihoodProcessor.h>
Public Member Functions | |
| TrackFitterLikelihoodProcessor () | |
| Default constructor. | |
| ~TrackFitterLikelihoodProcessor () | |
| Destructor. | |
| marlin::Processor * | newProcessor () |
| Return a new instance of this processor. | |
| void | init () |
| Called at the begin of the job before anything is read. | |
| void | processRunHeader (lcio::LCRunHeader *run) |
| Called once per run to process the event's header. | |
| virtual void | processEvent (lcio::LCEvent *evt) |
| Called for every event - the working horse. | |
| virtual double | operator() (const std::vector< double > &x) const |
| The meaning of the vector of parameters is of course defined by the user, who uses the values of those parameters to calculate his function value. More... | |
| virtual double | Up () const |
| Error definition of the function. More... | |
| virtual void | check (lcio::LCEvent *evt) |
| Called for every event - right after processEvent() has been called for all processors. | |
| virtual void | end () |
| Called after data processing for clean up in the inverse order of the init() method so that resources allocated in the first processor also will be available for all following processors. | |
Detailed Description
TrackFitterLikelihoodProcessor : This class takes post-amplified data from a readout pad and reconstructs the track based on the location of each signal.
The algorithm was developed by Dean Karlen at UVic
Member Function Documentation
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virtual |
The meaning of the vector of parameters is of course defined by the user, who uses the values of those parameters to calculate his function value.
The order and the position of these parameters is strictly the one specified by the user when supplying the starting values for minimization. The starting values must be specified by the user, either via an std::vector<double> or the MnUserParameters supplied as input to the MINUIT minimizers such as VariableMetricMinimizer or MnMigrad. Later values are determined by MINUIT as it searches for the minimum or performs whatever analysis is requested by the user.
- Parameters
-
par function parameters as defined by the user.
- Returns
- the value of the function.
- See Also
- MnUserParameters
- VariableMetricMinimizer
- MnMigrad
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virtual |
Error definition of the function.
MINUIT defines parameter errors as the change in parameter value required to change the function value by up. Normally, for chisquared fits it is 1, and for negative log likelihood, its value is 0.5. If the user wants instead the 2-sigma errors for chisquared fits, it becomes 4, as Chi2(x+n*sigma) = Chi2(x) + n*n.
- Todo:
- Comment a little bit better with links!!!!!!!!!!!!!!!!! Idem for errorDef()
The documentation for this class was generated from the following files:
- TrackFitterLikelihoodProcessor.h
- TrackFitterLikelihoodProcessor.cc
