ToyMCSampler is an implementation of the TestStatSampler interface.

It generates Toy Monte Carlo for a given parameter point and evaluates a TestStatistic.

For parallel runs, ToyMCSampler can be given an instance of ProofConfig and then run in parallel using proof or proof-lite. Internally, it uses ToyMCStudy with the RooStudyManager.

Definition at line 67 of file ToyMCSampler.h.

Public Member Functions
	ToyMCSampler ()
	Proof constructor. Do not use.

	ToyMCSampler (TestStatistic &ts, Int_t ntoys)

	~ToyMCSampler () override

virtual void	AddTestStatistic (TestStatistic *t=nullptr)
	The pdf can be nullptr in which case the density from SetPdf() is used.

virtual SamplingDistribution *	AppendSamplingDistribution (RooArgSet &allParameters, SamplingDistribution *last, Int_t additionalMC)
	Extended interface to append to sampling distribution more samples.

bool	CheckConfig (void)
	Checks for sufficient information to do a GetSamplingDistribution(...).

double	ConfidenceLevel () const override
	Get the Confidence level for the test.

virtual RooArgList *	EvaluateAllTestStatistics (RooAbsData &data, const RooArgSet &poi)
	Evaluate all test statistics, returning result and any detailed output.

double	EvaluateTestStatistic (RooAbsData &data, RooArgSet &nullPOI) override
	Main interface to evaluate the test statistic on a dataset.

virtual double	EvaluateTestStatistic (RooAbsData &data, RooArgSet &nullPOI, int i)
	Main interface to evaluate the test statistic on a dataset.

virtual void	GenerateGlobalObservables (RooAbsPdf &pdf) const
	generate global observables

virtual RooAbsData *	GenerateToyData (RooArgSet &paramPoint) const

virtual RooAbsData *	GenerateToyData (RooArgSet &paramPoint, double &weight) const

virtual RooAbsData *	GenerateToyData (RooArgSet &paramPoint, double &weight, RooAbsPdf &pdf) const
	generates toy data with weight

virtual RooAbsData *	GenerateToyData (RooArgSet &paramPoint, RooAbsPdf &pdf) const
	generates toy data without weight

virtual Int_t	GetNToys (void)

std::string	GetSamplingDistName (void)

SamplingDistribution *	GetSamplingDistribution (RooArgSet &paramPoint) override
	main interface

virtual RooDataSet *	GetSamplingDistributions (RooArgSet &paramPoint)
	Use for serial and parallel runs.

virtual RooDataSet *	GetSamplingDistributionsSingleWorker (RooArgSet &paramPoint)
	This is the main function for serial runs.

virtual TestStatistic *	GetTestStatistic (unsigned int i) const

TestStatistic *	GetTestStatistic (void) const override
	Get the TestStatistic.

void	Initialize (RooAbsArg &, RooArgSet &, RooArgSet &) override
	Common Initialization.

TClass *	IsA () const override

virtual void	SetAsimovNuisancePar (bool i=true)

void	SetConfidenceLevel (double cl) override
	set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)

virtual void	SetExpectedNuisancePar (bool i=true)

void	SetGenerateAutoBinned (bool autoBinned=true)
	set auto binned generation (=> see RooFit::AutoBinned() option)

void	SetGenerateBinned (bool binned=true)
	control to use bin data generation (=> see RooFit::AllBinned() option)

void	SetGenerateBinnedTag (const char *binnedTag="")
	name of the tag for individual components to be generated binned (=> see RooFit::GenBinned() option)

void	SetGlobalObservables (const RooArgSet &o) override
	specify the conditional observables

void	SetMaxToys (double t)
	This option forces a maximum number of total toys.

virtual void	SetNEventsPerToy (const Int_t nevents)
	Forces the generation of exactly `n` events even for extended PDFs.

virtual void	SetNToys (const Int_t ntoy)

void	SetNuisanceParameters (const RooArgSet &np) override
	specify the nuisance parameters (eg. the rest of the parameters)

void	SetObservables (const RooArgSet &o) override
	specify the observables in the dataset (needed to evaluate the test statistic)

void	SetParametersForTestStat (const RooArgSet &nullpoi) override
	Set the Pdf, add to the workspace if not already there.

void	SetPdf (RooAbsPdf &pdf) override
	Set the Pdf, add to the workspace if not already there.

void	SetPriorNuisance (RooAbsPdf *pdf) override
	How to randomize the prior. Set to nullptr to deactivate randomization.

void	SetProofConfig (ProofConfig *pc=nullptr)
	calling with argument or nullptr deactivates proof

void	SetProtoData (const RooDataSet *d)

void	SetSamplingDistName (const char *name) override
	Set the name of the sampling distribution used for plotting.

void	SetTestSize (double size) override
	set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)

void	SetTestStatistic (TestStatistic *t) override
	Set the TestStatistic (want the argument to be a function of the data & parameter points.

virtual void	SetTestStatistic (TestStatistic *testStatistic, unsigned int i)
	Set the TestStatistic (want the argument to be a function of the data & parameter points.

void	SetToysBothTails (double toys, double low_threshold, double high_threshold)

void	SetToysLeftTail (double toys, double threshold)

void	SetToysRightTail (double toys, double threshold)

void	SetUseMultiGen (bool flag)

void	Streamer (TBuffer &) override

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Public Member Functions inherited from RooStats::TestStatSampler
virtual	~TestStatSampler ()

void	StreamerNVirtual (TBuffer &ClassDef_StreamerNVirtual_b)

Static Public Member Functions
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

static void	SetAlwaysUseMultiGen (bool flag)

Static Public Member Functions inherited from RooStats::TestStatSampler
static TClass *	Class ()

static const char *	Class_Name ()

static constexpr Version_t	Class_Version ()

static const char *	DeclFileName ()

Protected Member Functions
virtual void	ClearCache ()
	helper method for clearing the cache

const RooArgList *	EvaluateAllTestStatistics (RooAbsData &data, const RooArgSet &poi, DetailedOutputAggregator &detOutAgg)

std::unique_ptr< RooAbsData >	Generate (RooAbsPdf &pdf, RooArgSet &observables, const RooDataSet *protoData=nullptr, int forceEvents=0) const
	helper for GenerateToyData

Protected Attributes
std::unique_ptr< RooArgSet >	_allVars
	!

std::unique_ptr< RooAbsPdf::GenSpec >	_gs1
	! GenSpec #1

std::unique_ptr< RooAbsPdf::GenSpec >	_gs2
	! GenSpec #2

std::unique_ptr< RooAbsPdf::GenSpec >	_gs3
	! GenSpec #3

std::unique_ptr< RooAbsPdf::GenSpec >	_gs4
	! GenSpec #4

std::vector< std::unique_ptr< RooAbsPdf::GenSpec > >	_gsList
	!

std::vector< std::unique_ptr< RooArgSet > >	_obsList
	!

std::vector< RooAbsPdf * >	_pdfList
	! We don't own those objects

double	fAdaptiveHighLimit

double	fAdaptiveLowLimit
	tails

bool	fExpectedNuisancePar
	whether to use expectation values for nuisance parameters (ie Asimov data set)

bool	fGenerateAutoBinned = true

bool	fGenerateBinned = false

TString	fGenerateBinnedTag = ""

const RooArgSet *	fGlobalObservables = nullptr

double	fMaxToys
	maximum no of toys (taking weights into account, therefore double)

Int_t	fNEvents = 0
	number of events per toy (may be ignored depending on settings)

Int_t	fNToys
	number of toys to generate

NuisanceParametersSampler *	fNuisanceParametersSampler = nullptr
	!

const RooArgSet *	fNuisancePars = nullptr

const RooArgSet *	fObservables = nullptr

std::unique_ptr< const RooArgSet >	fParametersForTestStat

RooAbsPdf *	fPdf = nullptr
	densities, snapshots, and test statistics to reweight to

RooAbsPdf *	fPriorNuisance = nullptr
	prior pdf for nuisance parameters

ProofConfig *	fProofConfig = nullptr
	!

const RooDataSet *	fProtoData = nullptr
	in dev

std::string	fSamplingDistName
	name of the model

double	fSize = 0.05

std::vector< TestStatistic * >	fTestStatistics

double	fToysInTails = 0.0
	minimum no of toys in tails for adaptive sampling (taking weights into account, therefore double) Default: 0.0 which means no adaptive sampling

bool	fUseMultiGen = false
	Use PrepareMultiGen?

Static Protected Attributes
static bool	fgAlwaysUseMultiGen = false
	Use PrepareMultiGen always.

#include <RooStats/ToyMCSampler.h>

Inheritance diagram for RooStats::ToyMCSampler:

[legend]

Constructor & Destructor Documentation

◆ ToyMCSampler() [1/2]

RooStats::ToyMCSampler::ToyMCSampler ( )

Proof constructor. Do not use.

Definition at line 149 of file ToyMCSampler.cxx.

◆ ToyMCSampler() [2/2]

RooStats::ToyMCSampler::ToyMCSampler	(	TestStatistic &	ts,
		Int_t	ntoys
	)

Definition at line 162 of file ToyMCSampler.cxx.

◆ ~ToyMCSampler()

RooStats::ToyMCSampler::~ToyMCSampler ( )

override

Definition at line 178 of file ToyMCSampler.cxx.

Member Function Documentation

◆ AddTestStatistic()

virtual void RooStats::ToyMCSampler::AddTestStatistic ( TestStatistic * t = nullptr )

inlinevirtual

The pdf can be nullptr in which case the density from SetPdf() is used.

The snapshot and TestStatistic is also optional.

Definition at line 93 of file ToyMCSampler.h.

◆ AppendSamplingDistribution()

SamplingDistribution * RooStats::ToyMCSampler::AppendSamplingDistribution	(	RooArgSet &	allParameters,
		SamplingDistribution *	last,
		Int_t	additionalMC
	)

virtual

Extended interface to append to sampling distribution more samples.

Definition at line 621 of file ToyMCSampler.cxx.

◆ CheckConfig()

bool RooStats::ToyMCSampler::CheckConfig ( void )

Checks for sufficient information to do a GetSamplingDistribution(...).

only checks, no guessing/determination (do this in calculators, e.g.

using ModelConfig::GuessObsAndNuisance(...))

Definition at line 188 of file ToyMCSampler.cxx.

◆ Class()

static TClass * RooStats::ToyMCSampler::Class ( )

static

Returns: TClass describing this class

◆ Class_Name()

static const char * RooStats::ToyMCSampler::Class_Name ( )

static

Returns: Name of this class

◆ Class_Version()

static constexpr Version_t RooStats::ToyMCSampler::Class_Version ( )

inlinestaticconstexpr

Returns: Version of this class

Definition at line 295 of file ToyMCSampler.h.

◆ ClearCache()

void RooStats::ToyMCSampler::ClearCache ( void )

protectedvirtual

helper method for clearing the cache

clear the cache obtained from the pdf used for speeding the toy and global observables generation needs to be called every time the model pdf (fPdf) changes

Reimplemented in RooStats::ToyMCImportanceSampler.

Definition at line 644 of file ToyMCSampler.cxx.

◆ ConfidenceLevel()

double RooStats::ToyMCSampler::ConfidenceLevel ( ) const

inlineoverridevirtual

Get the Confidence level for the test.

Implements RooStats::TestStatSampler.

Definition at line 133 of file ToyMCSampler.h.

◆ DeclFileName()

static const char * RooStats::ToyMCSampler::DeclFileName ( )

inlinestatic

Returns: Name of the file containing the class declaration

Definition at line 295 of file ToyMCSampler.h.

◆ EvaluateAllTestStatistics() [1/2]

RooArgList * RooStats::ToyMCSampler::EvaluateAllTestStatistics	(	RooAbsData &	data,
		const RooArgSet &	poi
	)

virtual

Evaluate all test statistics, returning result and any detailed output.

PDF parameter values are saved in case they are modified by TestStatistic::Evaluate (eg. SimpleLikelihoodRatioTestStat).

Definition at line 204 of file ToyMCSampler.cxx.

◆ EvaluateAllTestStatistics() [2/2]

const RooArgList * RooStats::ToyMCSampler::EvaluateAllTestStatistics	(	RooAbsData &	data,
		const RooArgSet &	poi,
		DetailedOutputAggregator &	detOutAgg
	)

protected

Definition at line 214 of file ToyMCSampler.cxx.

◆ EvaluateTestStatistic() [1/2]

double RooStats::ToyMCSampler::EvaluateTestStatistic	(	RooAbsData &	data,
		RooArgSet &	paramsOfInterest
	)

inlineoverridevirtual

Main interface to evaluate the test statistic on a dataset.

Implements RooStats::TestStatSampler.

Definition at line 123 of file ToyMCSampler.h.

◆ EvaluateTestStatistic() [2/2]

virtual double RooStats::ToyMCSampler::EvaluateTestStatistic	(	RooAbsData &	data,
		RooArgSet &	nullPOI,
		int	i
	)

inlinevirtual

Main interface to evaluate the test statistic on a dataset.

Definition at line 120 of file ToyMCSampler.h.

◆ Generate()

std::unique_ptr< RooAbsData > RooStats::ToyMCSampler::Generate	(	RooAbsPdf &	pdf,
		RooArgSet &	observables,
		const RooDataSet *	protoData = `nullptr`,
		int	forceEvents = `0`
	)		const

protected

helper for GenerateToyData

This is the generate function to use in the context of the ToyMCSampler instead of the standard RooAbsPdf::generate(...).

It takes into account whether the number of events is given explicitly or whether it should use the expected number of events. It also takes into account the option to generate a binned data set (i.e. RooDataHist).

Definition at line 550 of file ToyMCSampler.cxx.

◆ GenerateGlobalObservables()

void RooStats::ToyMCSampler::GenerateGlobalObservables ( RooAbsPdf & pdf ) const

virtual

generate global observables

Definition at line 417 of file ToyMCSampler.cxx.

◆ GenerateToyData() [1/4]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData ( RooArgSet & paramPoint ) const

inlinevirtual

Reimplemented in RooStats::ToyMCImportanceSampler.

Definition at line 109 of file ToyMCSampler.h.

◆ GenerateToyData() [2/4]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData	(	RooArgSet &	paramPoint,
		double &	weight
	)		const

inlinevirtual

Reimplemented in RooStats::ToyMCImportanceSampler, and RooStats::ToyMCImportanceSampler.

Definition at line 113 of file ToyMCSampler.h.

◆ GenerateToyData() [3/4]

RooAbsData * RooStats::ToyMCSampler::GenerateToyData	(	RooArgSet &	paramPoint,
		double &	weight,
		RooAbsPdf &	pdf
	)		const

virtual

generates toy data with weight

This method generates a toy data set for the given parameter point taking global observables into account.

The values of the generated global observables remain in the pdf's variables. They have to have those values for the subsequent evaluation of the test statistics.

Reimplemented in RooStats::ToyMCImportanceSampler.

Definition at line 483 of file ToyMCSampler.cxx.

◆ GenerateToyData() [4/4]

virtual RooAbsData * RooStats::ToyMCSampler::GenerateToyData	(	RooArgSet &	paramPoint,
		RooAbsPdf &	pdf
	)		const

inlinevirtual

generates toy data without weight

Reimplemented in RooStats::ToyMCImportanceSampler.

Definition at line 104 of file ToyMCSampler.h.

◆ GetNToys()

virtual Int_t RooStats::ToyMCSampler::GetNToys ( void )

inlinevirtual

Definition at line 140 of file ToyMCSampler.h.

◆ GetSamplingDistName()

std::string RooStats::ToyMCSampler::GetSamplingDistName ( void )

inline

Definition at line 208 of file ToyMCSampler.h.

◆ GetSamplingDistribution()

SamplingDistribution * RooStats::ToyMCSampler::GetSamplingDistribution ( RooArgSet & paramPoint )

overridevirtual

main interface

Implements RooStats::TestStatSampler.

Definition at line 246 of file ToyMCSampler.cxx.

◆ GetSamplingDistributions()

RooDataSet * RooStats::ToyMCSampler::GetSamplingDistributions ( RooArgSet & paramPoint )

virtual

Use for serial and parallel runs.

Definition at line 266 of file ToyMCSampler.cxx.

◆ GetSamplingDistributionsSingleWorker()

RooDataSet * RooStats::ToyMCSampler::GetSamplingDistributionsSingleWorker ( RooArgSet & paramPointIn )

virtual

This is the main function for serial runs.

It is called automatically from inside GetSamplingDistribution when no ProofConfig is given. You should not call this function yourself. This function should be used by ToyMCStudy on the workers (ie. when you explicitly want a serial run although ProofConfig is present).

Reimplemented in RooStats::ToyMCImportanceSampler.

Definition at line 321 of file ToyMCSampler.cxx.

◆ GetTestStatistic() [1/2]

virtual TestStatistic * RooStats::ToyMCSampler::GetTestStatistic ( unsigned int i ) const

inlinevirtual

Definition at line 127 of file ToyMCSampler.h.

◆ GetTestStatistic() [2/2]

TestStatistic * RooStats::ToyMCSampler::GetTestStatistic ( void ) const

inlineoverridevirtual

Get the TestStatistic.

Implements RooStats::TestStatSampler.

Definition at line 131 of file ToyMCSampler.h.

◆ Initialize()

void RooStats::ToyMCSampler::Initialize	(	RooAbsArg &	testStatistic,
		RooArgSet &	paramsOfInterest,
		RooArgSet &	nuisanceParameters
	)

inlineoverridevirtual

Common Initialization.

Implements RooStats::TestStatSampler.

Definition at line 134 of file ToyMCSampler.h.

◆ IsA()

TClass * RooStats::ToyMCSampler::IsA ( ) const

inlineoverridevirtual

Returns: TClass describing current object

Reimplemented from RooStats::TestStatSampler.

Definition at line 295 of file ToyMCSampler.h.

◆ SetAlwaysUseMultiGen()

void RooStats::ToyMCSampler::SetAlwaysUseMultiGen ( bool flag )

static

Definition at line 144 of file ToyMCSampler.cxx.

◆ SetAsimovNuisancePar()

virtual void RooStats::ToyMCSampler::SetAsimovNuisancePar ( bool i = true )

inlinevirtual

Definition at line 194 of file ToyMCSampler.h.

◆ SetConfidenceLevel()

void RooStats::ToyMCSampler::SetConfidenceLevel ( double cl )

inlineoverridevirtual

set the confidence level for the interval (eg. 0.95 for a 95% Confidence Interval)

Implements RooStats::TestStatSampler.

Definition at line 177 of file ToyMCSampler.h.

◆ SetExpectedNuisancePar()

virtual void RooStats::ToyMCSampler::SetExpectedNuisancePar ( bool i = true )

inlinevirtual

Definition at line 193 of file ToyMCSampler.h.

◆ SetGenerateAutoBinned()

void RooStats::ToyMCSampler::SetGenerateAutoBinned ( bool autoBinned = true )

inline

set auto binned generation (=> see RooFit::AutoBinned() option)

Definition at line 204 of file ToyMCSampler.h.

◆ SetGenerateBinned()

void RooStats::ToyMCSampler::SetGenerateBinned ( bool binned = true )

inline

control to use bin data generation (=> see RooFit::AllBinned() option)

Definition at line 200 of file ToyMCSampler.h.

◆ SetGenerateBinnedTag()

void RooStats::ToyMCSampler::SetGenerateBinnedTag ( const char * binnedTag = "" )

inline

name of the tag for individual components to be generated binned (=> see RooFit::GenBinned() option)

Definition at line 202 of file ToyMCSampler.h.

◆ SetGlobalObservables()

void RooStats::ToyMCSampler::SetGlobalObservables ( const RooArgSet & o )

inlineoverridevirtual

specify the conditional observables

Implements RooStats::TestStatSampler.

Definition at line 171 of file ToyMCSampler.h.

◆ SetMaxToys()

void RooStats::ToyMCSampler::SetMaxToys ( double t )

inline

This option forces a maximum number of total toys.

Definition at line 211 of file ToyMCSampler.h.

◆ SetNEventsPerToy()

virtual void RooStats::ToyMCSampler::SetNEventsPerToy ( const Int_t nevents )

inlinevirtual

Forces the generation of exactly n events even for extended PDFs.

Set to 0 to use the Poisson-distributed events from the extended PDF.

Definition at line 144 of file ToyMCSampler.h.

◆ SetNToys()

virtual void RooStats::ToyMCSampler::SetNToys ( const Int_t ntoy )

inlinevirtual

Definition at line 141 of file ToyMCSampler.h.

◆ SetNuisanceParameters()

void RooStats::ToyMCSampler::SetNuisanceParameters ( const RooArgSet & np )

inlineoverridevirtual

specify the nuisance parameters (eg. the rest of the parameters)

Implements RooStats::TestStatSampler.

Definition at line 167 of file ToyMCSampler.h.

◆ SetObservables()

void RooStats::ToyMCSampler::SetObservables ( const RooArgSet & o )

inlineoverridevirtual

specify the observables in the dataset (needed to evaluate the test statistic)

Implements RooStats::TestStatSampler.

Definition at line 169 of file ToyMCSampler.h.

◆ SetParametersForTestStat()

void RooStats::ToyMCSampler::SetParametersForTestStat ( const RooArgSet & nullpoi )

inlineoverridevirtual

Set the Pdf, add to the workspace if not already there.

Implements RooStats::TestStatSampler.

Definition at line 150 of file ToyMCSampler.h.

◆ SetPdf()

void RooStats::ToyMCSampler::SetPdf ( RooAbsPdf & )

inlineoverridevirtual

Set the Pdf, add to the workspace if not already there.

Implements RooStats::TestStatSampler.

Definition at line 156 of file ToyMCSampler.h.

◆ SetPriorNuisance()

void RooStats::ToyMCSampler::SetPriorNuisance ( RooAbsPdf * pdf )

inlineoverridevirtual

How to randomize the prior. Set to nullptr to deactivate randomization.

Implements RooStats::TestStatSampler.

Definition at line 159 of file ToyMCSampler.h.

◆ SetProofConfig()

void RooStats::ToyMCSampler::SetProofConfig ( ProofConfig * pc = nullptr )

inline

calling with argument or nullptr deactivates proof

Definition at line 230 of file ToyMCSampler.h.

◆ SetProtoData()

void RooStats::ToyMCSampler::SetProtoData ( const RooDataSet * d )

inline

Definition at line 232 of file ToyMCSampler.h.

◆ SetSamplingDistName()

void RooStats::ToyMCSampler::SetSamplingDistName ( const char * name )

inlineoverridevirtual

Set the name of the sampling distribution used for plotting.

Implements RooStats::TestStatSampler.

Definition at line 207 of file ToyMCSampler.h.

◆ SetTestSize()

void RooStats::ToyMCSampler::SetTestSize ( double size )

inlineoverridevirtual

set the size of the test (rate of Type I error) ( Eg. 0.05 for a 95% Confidence Interval)

Implements RooStats::TestStatSampler.

Definition at line 175 of file ToyMCSampler.h.

◆ SetTestStatistic() [1/2]

void RooStats::ToyMCSampler::SetTestStatistic ( TestStatistic * testStatistic )

inlineoverridevirtual

Set the TestStatistic (want the argument to be a function of the data & parameter points.

Implements RooStats::TestStatSampler.

Definition at line 191 of file ToyMCSampler.h.

◆ SetTestStatistic() [2/2]

virtual void RooStats::ToyMCSampler::SetTestStatistic	(	TestStatistic *	testStatistic,
		unsigned int	i
	)

inlinevirtual

Set the TestStatistic (want the argument to be a function of the data & parameter points.

Definition at line 180 of file ToyMCSampler.h.

◆ SetToysBothTails()

void RooStats::ToyMCSampler::SetToysBothTails	(	double	toys,
		double	low_threshold,
		double	high_threshold
	)

inline

Definition at line 223 of file ToyMCSampler.h.

◆ SetToysLeftTail()

void RooStats::ToyMCSampler::SetToysLeftTail	(	double	toys,
		double	threshold
	)

inline

Definition at line 213 of file ToyMCSampler.h.

◆ SetToysRightTail()

void RooStats::ToyMCSampler::SetToysRightTail	(	double	toys,
		double	threshold
	)

inline

Definition at line 218 of file ToyMCSampler.h.

◆ SetUseMultiGen()

void RooStats::ToyMCSampler::SetUseMultiGen ( bool flag )

inline

Definition at line 77 of file ToyMCSampler.h.

◆ Streamer()

void RooStats::ToyMCSampler::Streamer ( TBuffer & )

overridevirtual

Reimplemented from RooStats::TestStatSampler.

◆ StreamerNVirtual()

void RooStats::ToyMCSampler::StreamerNVirtual ( TBuffer & ClassDef_StreamerNVirtual_b )

inline

Definition at line 295 of file ToyMCSampler.h.

Member Data Documentation

◆ _allVars

std::unique_ptr<RooArgSet> RooStats::ToyMCSampler::_allVars

mutableprotected

!

Definition at line 282 of file ToyMCSampler.h.

◆ _gs1

std::unique_ptr<RooAbsPdf::GenSpec> RooStats::ToyMCSampler::_gs1

mutableprotected

! GenSpec #1

Definition at line 286 of file ToyMCSampler.h.

◆ _gs2

std::unique_ptr<RooAbsPdf::GenSpec> RooStats::ToyMCSampler::_gs2

mutableprotected

! GenSpec #2

Definition at line 287 of file ToyMCSampler.h.

◆ _gs3

std::unique_ptr<RooAbsPdf::GenSpec> RooStats::ToyMCSampler::_gs3

mutableprotected

! GenSpec #3

Definition at line 288 of file ToyMCSampler.h.

◆ _gs4

std::unique_ptr<RooAbsPdf::GenSpec> RooStats::ToyMCSampler::_gs4

mutableprotected

! GenSpec #4

Definition at line 289 of file ToyMCSampler.h.

◆ _gsList

std::vector<std::unique_ptr<RooAbsPdf::GenSpec> > RooStats::ToyMCSampler::_gsList

mutableprotected

!

Definition at line 285 of file ToyMCSampler.h.

◆ _obsList

std::vector<std::unique_ptr<RooArgSet> > RooStats::ToyMCSampler::_obsList

mutableprotected

!

Definition at line 284 of file ToyMCSampler.h.

◆ _pdfList

std::vector<RooAbsPdf*> RooStats::ToyMCSampler::_pdfList

mutableprotected

! We don't own those objects

Definition at line 283 of file ToyMCSampler.h.

◆ fAdaptiveHighLimit

double RooStats::ToyMCSampler::fAdaptiveHighLimit

protected

Definition at line 273 of file ToyMCSampler.h.

◆ fAdaptiveLowLimit

double RooStats::ToyMCSampler::fAdaptiveLowLimit

protected

tails

Definition at line 272 of file ToyMCSampler.h.

◆ fExpectedNuisancePar

bool RooStats::ToyMCSampler::fExpectedNuisancePar

protected

Initial value:

=

false

whether to use expectation values for nuisance parameters (ie Asimov data set)

Definition at line 258 of file ToyMCSampler.h.

◆ fgAlwaysUseMultiGen

bool RooStats::ToyMCSampler::fgAlwaysUseMultiGen = false

staticprotected

Use PrepareMultiGen always.

Definition at line 291 of file ToyMCSampler.h.

◆ fGenerateAutoBinned

bool RooStats::ToyMCSampler::fGenerateAutoBinned = true

protected

Definition at line 262 of file ToyMCSampler.h.

◆ fGenerateBinned

bool RooStats::ToyMCSampler::fGenerateBinned = false

protected

Definition at line 260 of file ToyMCSampler.h.

◆ fGenerateBinnedTag

TString RooStats::ToyMCSampler::fGenerateBinnedTag = ""

protected

Definition at line 261 of file ToyMCSampler.h.

◆ fGlobalObservables

const RooArgSet* RooStats::ToyMCSampler::fGlobalObservables = nullptr

protected

Definition at line 254 of file ToyMCSampler.h.

◆ fMaxToys

double RooStats::ToyMCSampler::fMaxToys

protected

maximum no of toys (taking weights into account, therefore double)

Definition at line 270 of file ToyMCSampler.h.

◆ fNEvents

Int_t RooStats::ToyMCSampler::fNEvents = 0

protected

number of events per toy (may be ignored depending on settings)

Definition at line 256 of file ToyMCSampler.h.

◆ fNToys

Int_t RooStats::ToyMCSampler::fNToys

protected

number of toys to generate

Definition at line 255 of file ToyMCSampler.h.

◆ fNuisanceParametersSampler

NuisanceParametersSampler* RooStats::ToyMCSampler::fNuisanceParametersSampler = nullptr

mutableprotected

!

Definition at line 279 of file ToyMCSampler.h.

◆ fNuisancePars

const RooArgSet* RooStats::ToyMCSampler::fNuisancePars = nullptr

protected

Definition at line 252 of file ToyMCSampler.h.

◆ fObservables

const RooArgSet* RooStats::ToyMCSampler::fObservables = nullptr

protected

Definition at line 253 of file ToyMCSampler.h.

◆ fParametersForTestStat

std::unique_ptr<const RooArgSet> RooStats::ToyMCSampler::fParametersForTestStat

protected

Definition at line 247 of file ToyMCSampler.h.

◆ fPdf

RooAbsPdf* RooStats::ToyMCSampler::fPdf = nullptr

protected

densities, snapshots, and test statistics to reweight to

model (can be alt or null)

Definition at line 246 of file ToyMCSampler.h.

◆ fPriorNuisance

RooAbsPdf* RooStats::ToyMCSampler::fPriorNuisance = nullptr

protected

prior pdf for nuisance parameters

Definition at line 251 of file ToyMCSampler.h.

◆ fProofConfig

ProofConfig* RooStats::ToyMCSampler::fProofConfig = nullptr

protected

!

Definition at line 277 of file ToyMCSampler.h.

◆ fProtoData

const RooDataSet* RooStats::ToyMCSampler::fProtoData = nullptr

protected

in dev

Definition at line 275 of file ToyMCSampler.h.

◆ fSamplingDistName

std::string RooStats::ToyMCSampler::fSamplingDistName

protected

name of the model

Definition at line 250 of file ToyMCSampler.h.

◆ fSize

double RooStats::ToyMCSampler::fSize = 0.05

protected

Definition at line 257 of file ToyMCSampler.h.

◆ fTestStatistics

std::vector<TestStatistic*> RooStats::ToyMCSampler::fTestStatistics

protected

Definition at line 248 of file ToyMCSampler.h.

◆ fToysInTails

double RooStats::ToyMCSampler::fToysInTails = 0.0

protected

minimum no of toys in tails for adaptive sampling (taking weights into account, therefore double) Default: 0.0 which means no adaptive sampling

Definition at line 267 of file ToyMCSampler.h.

◆ fUseMultiGen

bool RooStats::ToyMCSampler::fUseMultiGen = false

protected

Use PrepareMultiGen?

Definition at line 292 of file ToyMCSampler.h.

Libraries for RooStats::ToyMCSampler:

[legend]

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

roofit/roostats/inc/RooStats/ToyMCSampler.h
roofit/roostats/src/ToyMCSampler.cxx

Public Member Functions

Static Public Member Functions

Protected Member Functions

Protected Attributes

Static Protected Attributes

Constructor & Destructor Documentation

◆ ToyMCSampler() [1/2]

◆ ToyMCSampler() [2/2]

◆ ~ToyMCSampler()

Member Function Documentation

◆ AddTestStatistic()

◆ AppendSamplingDistribution()

◆ CheckConfig()

◆ Class()

◆ Class_Name()

◆ Class_Version()

◆ ClearCache()

◆ ConfidenceLevel()

◆ DeclFileName()

◆ EvaluateAllTestStatistics() [1/2]

◆ EvaluateAllTestStatistics() [2/2]

◆ EvaluateTestStatistic() [1/2]

◆ EvaluateTestStatistic() [2/2]

◆ Generate()

◆ GenerateGlobalObservables()

◆ GenerateToyData() [1/4]

◆ GenerateToyData() [2/4]

◆ GenerateToyData() [3/4]

◆ GenerateToyData() [4/4]

◆ GetNToys()

◆ GetSamplingDistName()

◆ GetSamplingDistribution()

◆ GetSamplingDistributions()

◆ GetSamplingDistributionsSingleWorker()

◆ GetTestStatistic() [1/2]

◆ GetTestStatistic() [2/2]

◆ Initialize()

◆ IsA()

◆ SetAlwaysUseMultiGen()

◆ SetAsimovNuisancePar()

◆ SetConfidenceLevel()

◆ SetExpectedNuisancePar()

◆ SetGenerateAutoBinned()

◆ SetGenerateBinned()

◆ SetGenerateBinnedTag()

◆ SetGlobalObservables()

◆ SetMaxToys()

◆ SetNEventsPerToy()

◆ SetNToys()

◆ SetNuisanceParameters()

◆ SetObservables()

◆ SetParametersForTestStat()

◆ SetPdf()

◆ SetPriorNuisance()

◆ SetProofConfig()

◆ SetProtoData()

◆ SetSamplingDistName()

◆ SetTestSize()

◆ SetTestStatistic() [1/2]

◆ SetTestStatistic() [2/2]

◆ SetToysBothTails()

◆ SetToysLeftTail()

◆ SetToysRightTail()

◆ SetUseMultiGen()

◆ Streamer()

◆ StreamerNVirtual()

Member Data Documentation

◆ _allVars

◆ _gs1

◆ _gs2

◆ _gs3

◆ _gs4

◆ _gsList

◆ _obsList

◆ _pdfList

◆ fAdaptiveHighLimit

◆ fAdaptiveLowLimit

◆ fExpectedNuisancePar

◆ fgAlwaysUseMultiGen

◆ fGenerateAutoBinned