ROOT » ROOFIT » ROOSTATS » RooStats::ToyMCImportanceSampler

class RooStats::ToyMCImportanceSampler: public RooStats::ToyMCSampler

Function Members (Methods)

public:
virtual~ToyMCImportanceSampler()
voidAddImportanceDensity(RooAbsPdf* p, const RooArgSet* s)
voidAddNullDensity(RooAbsPdf* p, const RooArgSet* s = __null)
virtual voidRooStats::ToyMCSampler::AddTestStatistic(RooStats::TestStatistic* t = __null)
virtual RooStats::SamplingDistribution*RooStats::ToyMCSampler::AppendSamplingDistribution(RooArgSet& allParameters, RooStats::SamplingDistribution* last, Int_t additionalMC)
Bool_tRooStats::ToyMCSampler::CheckConfig()
static TClass*Class()
virtual Double_tRooStats::ToyMCSampler::ConfidenceLevel() const
intCreateImpDensitiesForOnePOIAdaptively(RooAbsPdf& pdf, const RooArgSet& allPOI, RooRealVar& poi, double nStdDevOverlap = 0.5, double poiValueForBackground = 0.)
intCreateNImpDensitiesForOnePOI(RooAbsPdf& pdf, const RooArgSet& allPOI, RooRealVar& poi, int n, double poiValueForBackground = 0.)
virtual RooArgList*RooStats::ToyMCSampler::EvaluateAllTestStatistics(RooAbsData& data, const RooArgSet& poi)
virtual Double_tRooStats::ToyMCSampler::EvaluateTestStatistic(RooAbsData& data, RooArgSet& nullPOI)
virtual Double_tRooStats::ToyMCSampler::EvaluateTestStatistic(RooAbsData& data, RooArgSet& nullPOI, int i)
virtual voidRooStats::ToyMCSampler::GenerateGlobalObservables(RooAbsPdf& pdf) const
virtual RooAbsData*GenerateToyData(vector<double>& weights) const
virtual RooAbsData*GenerateToyData(RooArgSet& paramPoint, double& weight) const
virtual RooAbsData*GenerateToyData(vector<double>& weights, vector<double>& nullNLLs, vector<double>& impNLLs) const
virtual RooAbsData*GenerateToyData(RooArgSet& paramPoint, double& weight, vector<double>& impNLLs, double& nullNLL) const
virtual Int_tRooStats::ToyMCSampler::GetNToys()
stringRooStats::ToyMCSampler::GetSamplingDistName()
virtual RooStats::SamplingDistribution*RooStats::ToyMCSampler::GetSamplingDistribution(RooArgSet& paramPoint)
virtual RooDataSet*RooStats::ToyMCSampler::GetSamplingDistributions(RooArgSet& paramPoint)
virtual RooDataSet*GetSamplingDistributionsSingleWorker(RooArgSet& paramPoint)
virtual RooStats::TestStatistic*RooStats::ToyMCSampler::GetTestStatistic() const
virtual RooStats::TestStatistic*RooStats::ToyMCSampler::GetTestStatistic(unsigned int i) const
virtual voidRooStats::ToyMCSampler::Initialize(RooAbsArg&, RooArgSet&, RooArgSet&)
virtual TClass*IsA() const
RooStats::ToyMCImportanceSampler&operator=(const RooStats::ToyMCImportanceSampler&)
static voidRooStats::ToyMCSampler::SetAlwaysUseMultiGen(Bool_t flag)
voidSetApplyVeto(bool b = true)
virtual voidRooStats::ToyMCSampler::SetAsimovNuisancePar(Bool_t i = kTRUE)
virtual voidSetConditionalObservables(const RooArgSet& set)
virtual voidRooStats::ToyMCSampler::SetConfidenceLevel(Double_t cl)
voidSetDensityToGenerateFromByIndex(unsigned int i, bool fromNull = false)
voidSetEqualNumToysPerDensity()
virtual voidRooStats::ToyMCSampler::SetExpectedNuisancePar(Bool_t i = kTRUE)
voidSetExpIncreasingNumToysPerDensity()
voidRooStats::ToyMCSampler::SetGenerateAutoBinned(Bool_t autoBinned = kTRUE)
voidRooStats::ToyMCSampler::SetGenerateBinned(bool binned = true)
voidRooStats::ToyMCSampler::SetGenerateBinnedTag(const char* binnedTag = "")
virtual voidRooStats::ToyMCSampler::SetGlobalObservables(const RooArgSet& o)
voidRooStats::ToyMCSampler::SetMaxToys(Double_t t)
virtual voidRooStats::ToyMCSampler::SetNEventsPerToy(const Int_t nevents)
virtual voidRooStats::ToyMCSampler::SetNToys(const Int_t ntoy)
virtual voidRooStats::ToyMCSampler::SetNuisanceParameters(const RooArgSet& np)
virtual voidRooStats::ToyMCSampler::SetObservables(const RooArgSet& o)
virtual voidSetParametersForTestStat(const RooArgSet& nullpoi)
virtual voidSetPdf(RooAbsPdf& pdf)
virtual voidRooStats::ToyMCSampler::SetPriorNuisance(RooAbsPdf* pdf)
voidRooStats::ToyMCSampler::SetProofConfig(RooStats::ProofConfig* pc = __null)
voidRooStats::ToyMCSampler::SetProtoData(const RooDataSet* d)
voidSetReuseNLL(bool r = true)
virtual voidRooStats::ToyMCSampler::SetSamplingDistName(const char* name)
virtual voidRooStats::ToyMCSampler::SetTestSize(Double_t size)
virtual voidRooStats::ToyMCSampler::SetTestStatistic(RooStats::TestStatistic* t)
virtual voidRooStats::ToyMCSampler::SetTestStatistic(RooStats::TestStatistic* testStatistic, unsigned int i)
voidRooStats::ToyMCSampler::SetToysBothTails(Double_t toys, Double_t low_threshold, Double_t high_threshold)
voidRooStats::ToyMCSampler::SetToysLeftTail(Double_t toys, Double_t threshold)
voidRooStats::ToyMCSampler::SetToysRightTail(Double_t toys, Double_t threshold)
voidRooStats::ToyMCSampler::SetUseMultiGen(Bool_t flag)
virtual voidShowMembers(TMemberInspector& insp) const
virtual voidStreamer(TBuffer&)
voidStreamerNVirtual(TBuffer& ClassDef_StreamerNVirtual_b)
RooStats::TestStatSamplerRooStats::TestStatSampler::TestStatSampler()
RooStats::TestStatSamplerRooStats::TestStatSampler::TestStatSampler(const RooStats::TestStatSampler&)
RooStats::ToyMCImportanceSamplerToyMCImportanceSampler()
RooStats::ToyMCImportanceSamplerToyMCImportanceSampler(const RooStats::ToyMCImportanceSampler&)
RooStats::ToyMCImportanceSamplerToyMCImportanceSampler(RooStats::TestStatistic& ts, Int_t ntoys)
RooStats::ToyMCSamplerRooStats::ToyMCSampler::ToyMCSampler()
RooStats::ToyMCSamplerRooStats::ToyMCSampler::ToyMCSampler(const RooStats::ToyMCSampler&)
RooStats::ToyMCSamplerRooStats::ToyMCSampler::ToyMCSampler(RooStats::TestStatistic& ts, Int_t ntoys)
protected:
virtual voidClearCache()
const RooArgList*RooStats::ToyMCSampler::EvaluateAllTestStatistics(RooAbsData& data, const RooArgSet& poi, RooStats::DetailedOutputAggregator& detOutAgg)
RooAbsData*RooStats::ToyMCSampler::Generate(RooAbsPdf& pdf, RooArgSet& observables, const RooDataSet* protoData = __null, int forceEvents = 0) const

Data Members

protected:
RooArgSet*RooStats::ToyMCSampler::_allVars!
RooAbsPdf::GenSpec*RooStats::ToyMCSampler::_gs1! GenSpec #1
RooAbsPdf::GenSpec*RooStats::ToyMCSampler::_gs2! GenSpec #2
RooAbsPdf::GenSpec*RooStats::ToyMCSampler::_gs3! GenSpec #3
RooAbsPdf::GenSpec*RooStats::ToyMCSampler::_gs4! GenSpec #4
list<RooAbsPdf::GenSpec*>RooStats::ToyMCSampler::_gsList!
list<RooArgSet*>RooStats::ToyMCSampler::_obsList!
list<RooAbsPdf*>RooStats::ToyMCSampler::_pdfList!
Double_tRooStats::ToyMCSampler::fAdaptiveHighLimit
Double_tRooStats::ToyMCSampler::fAdaptiveLowLimit
boolfApplyVeto
RooArgSetfConditionalObsset of conditional observables
Bool_tRooStats::ToyMCSampler::fExpectedNuisanceParwhether to use expectation values for nuisance parameters (ie Asimov data set)
Bool_tRooStats::ToyMCSampler::fGenerateAutoBinned
Bool_tRooStats::ToyMCSampler::fGenerateBinned
TStringRooStats::ToyMCSampler::fGenerateBinnedTag
boolfGenerateFromNull
const RooArgSet*RooStats::ToyMCSampler::fGlobalObservables
vector<RooAbsReal*>fImpNLLs!
vector<RooAbsPdf*>fImportanceDensities
vector<const RooArgSet*>fImportanceSnapshots
unsigned intfIndexGenDensity
Double_tRooStats::ToyMCSampler::fMaxToys
Int_tRooStats::ToyMCSampler::fNEventsnumber of events per toy (may be ignored depending on settings)
Int_tRooStats::ToyMCSampler::fNToysnumber of toys to generate
RooStats::NuisanceParametersSampler*RooStats::ToyMCSampler::fNuisanceParametersSampler!
const RooArgSet*RooStats::ToyMCSampler::fNuisancePars
vector<RooAbsPdf*>fNullDensities
vector<RooAbsReal*>fNullNLLs!
vector<const RooArgSet*>fNullSnapshots
const RooArgSet*RooStats::ToyMCSampler::fObservables
const RooArgSet*RooStats::ToyMCSampler::fParametersForTestStat
RooAbsPdf*RooStats::ToyMCSampler::fPdfmodel (can be alt or null)
RooAbsPdf*RooStats::ToyMCSampler::fPriorNuisanceprior pdf for nuisance parameters
RooStats::ProofConfig*RooStats::ToyMCSampler::fProofConfig!
const RooDataSet*RooStats::ToyMCSampler::fProtoDatain dev
boolfReuseNLL
stringRooStats::ToyMCSampler::fSamplingDistNamename of the model
Double_tRooStats::ToyMCSampler::fSize
vector<RooStats::TestStatistic*>RooStats::ToyMCSampler::fTestStatistics
Double_tRooStats::ToyMCSampler::fToysInTails
RooStats::toysStrategiesfToysStrategy
Bool_tRooStats::ToyMCSampler::fUseMultiGenUse PrepareMultiGen?
static Bool_tRooStats::ToyMCSampler::fgAlwaysUseMultiGenUse PrepareMultiGen always

Class Charts

Inheritance Inherited Members Includes Libraries
Class Charts

Function documentation

~ToyMCImportanceSampler()
void ClearCache(void)
RooDataSet* GetSamplingDistributionsSingleWorker(RooArgSet& paramPoint)
RooAbsData* GenerateToyData(RooArgSet& paramPoint, double& weight) const
RooAbsData* GenerateToyData(RooArgSet& paramPoint, double& weight, vector<double>& impNLLs, double& nullNLL) const
RooAbsData* GenerateToyData(vector<double>& weights) const
RooAbsData* GenerateToyData(vector<double>& weights, vector<double>& nullNLLs, vector<double>& impNLLs) const
 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.
int CreateImpDensitiesForOnePOIAdaptively(RooAbsPdf& pdf, const RooArgSet& allPOI, RooRealVar& poi, double nStdDevOverlap = 0.5, double poiValueForBackground = 0.)
 these might not necessarily be the same thing.
int CreateNImpDensitiesForOnePOI(RooAbsPdf& pdf, const RooArgSet& allPOI, RooRealVar& poi, int n, double poiValueForBackground = 0.)
 n is the number of importance densities
ToyMCImportanceSampler()
 Proof constructor. Do not use.
ToyMCImportanceSampler(RooStats::TestStatistic& ts, Int_t ntoys)
void SetDensityToGenerateFromByIndex(unsigned int i, bool fromNull = false)
 specifies the pdf to sample from
void AddImportanceDensity(RooAbsPdf* p, const RooArgSet* s)
 For importance sampling with multiple desnities/snapshots:
 This is used to check the current Likelihood against Likelihoods from
 other importance densities apart from the one given as importance snapshot.
 The pdf can be NULL in which case the density from SetImportanceDensity()
 is used. The snapshot is also optional.
void AddNullDensity(RooAbsPdf* p, const RooArgSet* s = __null)
 The pdf can be NULL in which case the density from SetPdf()
 is used. The snapshot and TestStatistic is also optional.
void SetPdf(RooAbsPdf& pdf)
 overwrite from ToyMCSampler
void SetParametersForTestStat(const RooArgSet& nullpoi)
 overwrite from ToyMCSampler
void SetApplyVeto(bool b = true)
 When set to true, this sets the weight of all toys to zero that
 do not have the largest likelihood under the density it was generated
 compared to the other densities.
{ fApplyVeto = b; }
void SetReuseNLL(bool r = true)
{ fReuseNLL = r; }
void SetConditionalObservables(const RooArgSet& set)
 set the conditional observables which will be used when creating the NLL
 so the pdf's will not be normalized on the conditional observables when computing the NLL
 Since the class use a NLL we need to set the ocnditional onservables if they exist in the model
{fConditionalObs.removeAll(); fConditionalObs.add(set);}
void SetEqualNumToysPerDensity( void )
{ fToysStrategy = EQUALTOYSPERDENSITY; }
void SetExpIncreasingNumToysPerDensity( void )
{ fToysStrategy = EXPONENTIALTOYDISTRIBUTION; }