16#ifndef RooFit_RooNLLVarNew_h
17#define RooFit_RooNLLVarNew_h
33 static constexpr const char *weightVarName =
"_weight";
42 double defaultErrorLevel()
const override {
return 0.5; }
45 bool canComputeBatchWithCuda()
const override {
return !
_binnedL; }
46 bool isReducerNode()
const override {
return true; }
48 void setPrefix(std::string
const &prefix);
50 void applyWeightSquared(
bool flag)
override;
52 void enableOffsetting(
bool)
override;
58 RooAbsPdf const &pdf()
const {
return *_pdf; }
62 RooAbsReal const *expectedEvents()
const {
return _expectedEvents ? &**_expectedEvents :
nullptr; }
65 double evaluate()
const override {
return _value; }
74 std::unique_ptr<RooTemplateProxy<RooAbsReal>> _expectedEvents;
75 std::unique_ptr<RooTemplateProxy<RooAbsPdf>>
_offsetPdf;
76 mutable double _sumWeight = 0.0;
84 std::vector<double> _binw;
#define ClassDefOverride(name, id)
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t Int_t Int_t UInt_t UInt_t Rectangle_t result
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...
Abstract interface for all probability density functions.
Abstract base class for objects that represent a real value and implements functionality common to al...
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Mother of all ROOT objects.
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
OffsetMode
For setting the offset mode with the Offset() command argument to RooAbsPdf::fitTo()
void evaluate(typename Architecture_t::Tensor_t &A, EActivationFunction f)
Apply the given activation function to each value in the given tensor A.