PyLikelihoodFit Class Reference

EW: As LikelihoodFit is an abstract base class we have to do some gymnastics to get it to get it into python. More...

Inheritance diagram for PyLikelihoodFit:

Collaboration diagram for PyLikelihoodFit:

Public Member Functions
void	RunMCMC () override
	Implementation of fitting algorithm.
	LikelihoodFit (manager *const fitMan)
	Constructor.
Public Member Functions inherited from LikelihoodFit
	LikelihoodFit (manager *const fitMan)
	Constructor.
virtual	~LikelihoodFit ()
	Destructor.
virtual double	CalcChi2 (const double *x)
	Chi2 calculation over all included samples and syst objects.
int	GetNPars ()
	Get total number of params, this sums over all covariance objects.
virtual void	RunMCMC ()=0
	Implementation of fitting algorithm.
virtual std::string	GetName () const
	Get name of class.
Public Member Functions inherited from FitterBase
	FitterBase (manager *const fitMan)
	Constructor.
virtual	~FitterBase ()
	Destructor for the FitterBase class.
void	AddSampleHandler (SampleHandlerBase *sample)
	This function adds a sample PDF object to the analysis framework. The sample PDF object will be utilized in fitting procedures or likelihood scans.
void	AddSystObj (ParameterHandlerBase *cov)
	This function adds a Covariance object to the analysis framework. The Covariance object will be utilized in fitting procedures or likelihood scans.
virtual void	RunMCMC ()=0
	The specific fitting algorithm implemented in this function depends on the derived class. It could be Markov Chain Monte Carlo (MCMC), MinuitFit, or another algorithm.
void	DragRace (const int NLaps=100)
	Calculates the required time for each sample or covariance object in a drag race simulation. Inspired by Dan's feature.
void	RunLLHScan ()
	Perform a 1D likelihood scan.
void	GetStepScaleBasedOnLLHScan ()
	LLH scan is good first estimate of step scale.
void	Run2DLLHScan ()
	Perform a 2D likelihood scan.
void	RunSigmaVar ()
	Perform a 2D and 1D sigma var for all samples.
virtual void	StartFromPreviousFit (const std::string &FitName)
	Allow to start from previous fit/chain.
virtual std::string	GetName () const
	Get name of class.

Additional Inherited Members
Protected Member Functions inherited from LikelihoodFit
void	PrepareFit ()
	prepare output and perform sanity checks
Protected Member Functions inherited from FitterBase
void	ProcessMCMC ()
	Process MCMC output.
void	PrepareOutput ()
	Prepare the output file.
void	SaveOutput ()
	Save output and close files.
void	SanitiseInputs ()
	Remove obsolete memory and make other checks before fit starts.
void	SaveSettings ()
	Save the settings that the MCMC was run with.
bool	GetScaneRange (std::map< std::string, std::vector< double > > &scanRanges)
	YSP: Set up a mapping to store parameters with user-specified ranges, suggested by D. Barrow.
bool	CheckSkipParameter (const std::vector< std::string > &SkipVector, const std::string &ParamName) const
	KS: Check whether we want to skip parameter using skip vector.
Protected Attributes inherited from LikelihoodFit
int	NPars
	Number of all parameters from all covariances.
int	NParsPCA
	Number of all parameters from all covariances in PCA base.
bool	fMirroring
	Flag telling if mirroring is used or not.
Protected Attributes inherited from FitterBase
manager *	fitMan
	The manager.
unsigned int	step
	current state
double	logLCurr
	current likelihood
double	logLProp
	proposed likelihood
double	accProb
	current acceptance prob
int	accCount
	counts accepted steps
int	stepStart
	step start if restarting
std::vector< double >	sample_llh
	store the llh breakdowns
std::vector< double >	syst_llh
	systematic llh breakdowns
std::vector< SampleHandlerBase * >	samples
	Sample holder.
unsigned int	TotalNSamples
	Total number of samples used.
std::vector< ParameterHandlerBase * >	systematics
	Systematic holder.
std::unique_ptr< TStopwatch >	clock
	tells global time how long fit took
std::unique_ptr< TStopwatch >	stepClock
	tells how long single step/fit iteration took
double	stepTime
	Time of single step.
std::unique_ptr< TRandom3 >	random
	Random number.
TFile *	outputFile
	Output.
TDirectory *	CovFolder
	Output cov folder.
TDirectory *	SampleFolder
	Output sample folder.
TTree *	outTree
	Output tree with posteriors.
int	auto_save
	auto save every N steps
bool	fTestLikelihood
	Necessary for some fitting algorithms like PSO.
bool	FileSaved
	Checks if file saved not repeat some operations.
bool	SettingsSaved
	Checks if setting saved not repeat some operations.
bool	OutputPrepared
	Checks if output prepared not repeat some operations.

Detailed Description

EW: As LikelihoodFit is an abstract base class we have to do some gymnastics to get it to get it into python.

Definition at line 39 of file fitters.cpp.

Member Function Documentation

LikelihoodFit()

LikelihoodFit::LikelihoodFit

(

manager *const

fitMan

)

Constructor.

Definition at line 9 of file LikelihoodFit.cpp.

                                         : FitterBase(man) {
// *******************
  NPars = 0;
  NParsPCA = 0;
  fMirroring = GetFromManager<bool>(fitMan->raw()["General"]["Fitter"]["Mirroring"], false);
  if(fMirroring) MACH3LOG_INFO("Mirroring enabled");
}

RunMCMC()

void PyLikelihoodFit::RunMCMC ( )

inlineoverridevirtual

Implementation of fitting algorithm.

Implements LikelihoodFit.

Definition at line 45 of file fitters.cpp.

                            {
        PYBIND11_OVERRIDE_PURE_NAME(
            void,        /* Return type */
            LikelihoodFit,/* Parent class */
            "run",       /* Python name*/
            RunMCMC      /* Name of function in C++ (must match Python name) */
        );
    }

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

• python/fitters.cpp