45 const RooArgSet& projDeps,
bool extended =
false,
71 std::unique_ptr<RooBatchCompute::RunContext> &evalData,
72 RooArgSet *normSet,
bool weightSq, std::size_t stepSize,
73 std::size_t firstEvent, std::size_t lastEvent);
75 bool weightSq, std::size_t stepSize, std::size_t firstEvent,
76 std::size_t lastEvent,
bool doBinOffset=
false);
81 double evaluatePartition(std::size_t firstEvent, std::size_t lastEvent, std::size_t stepSize)
const override;
96 mutable std::vector<double>
_binw ;
98 mutable std::unique_ptr<RooBatchCompute::RunContext>
_evalData;
#define ClassDefOverride(name, id)
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void on
The Kahan summation is a compensated summation algorithm, which significantly reduces numerical error...
RooAbsData is the common abstract base class for binned and unbinned datasets.
RooAbsOptTestStatistic is the abstract base class for test statistics objects that evaluate a functio...
RooAbsReal is the common abstract base class for objects that represent a real value and implements f...
RooAbsTestStatistic is the abstract base class for all test statistics.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
RooCmdArg is a named container for two doubles, two integers two object points and three string point...
static const RooCmdArg & none()
Return reference to null argument.
Class RooNLLVar implements a -log(likelihood) calculation from a dataset and a PDF.
ComputeResult computeScalar(std::size_t stepSize, std::size_t firstEvent, std::size_t lastEvent) const
bool processEmptyDataSets() const override
static RooNLLVar::ComputeResult computeScalarFunc(const RooAbsPdf *pdfClone, RooAbsData *dataClone, RooArgSet *normSet, bool weightSq, std::size_t stepSize, std::size_t firstEvent, std::size_t lastEvent, bool doBinOffset=false)
RooRealSumPdf * _binnedPdf
!
ROOT::Math::KahanSum< double > _offsetSaveW2
!
static RooNLLVar::ComputeResult computeBatchedFunc(const RooAbsPdf *pdfClone, RooAbsData *dataClone, std::unique_ptr< RooBatchCompute::RunContext > &evalData, RooArgSet *normSet, bool weightSq, std::size_t stepSize, std::size_t firstEvent, std::size_t lastEvent)
static RooArgSet _emptySet
void batchMode(bool on=true)
void applyWeightSquared(bool flag) override
Disables or enables the usage of squared weights.
std::vector< double > _binw
!
std::pair< ROOT::Math::KahanSum< double >, double > ComputeResult
TObject * clone(const char *newname) const override
RooAbsTestStatistic * create(const char *name, const char *title, RooAbsReal &pdf, RooAbsData &adata, const RooArgSet &projDeps, RooAbsTestStatistic::Configuration const &cfg) override
Create a test statistic using several properties of the current instance.
void enableBinOffsetting(bool on=true)
double defaultErrorLevel() const override
std::unique_ptr< RooBatchCompute::RunContext > _evalData
! Struct to store function evaluation workspaces.
ComputeResult computeBatched(std::size_t stepSize, std::size_t firstEvent, std::size_t lastEvent) const
Compute probabilites of all data events.
bool _weightSq
Apply weights squared?
double evaluatePartition(std::size_t firstEvent, std::size_t lastEvent, std::size_t stepSize) const override
Calculate and return likelihood on subset of data.
The class RooRealSumPdf implements a PDF constructed from a sum of functions:
Mother of all ROOT objects.
Namespace for dispatching RooFit computations to various backends.