16#ifndef RooFit_RooNLLVarNew_h
17#define RooFit_RooNLLVarNew_h
30 static constexpr const char *weightVarName =
"_weight";
39 double defaultErrorLevel()
const override {
return 0.5; }
42 bool canComputeBatchWithCuda()
const override {
return !
_binnedL; }
43 bool isReducerNode()
const override {
return true; }
45 void setPrefix(std::string
const &prefix);
47 void applyWeightSquared(
bool flag)
override;
49 void enableOffsetting(
bool)
override;
51 void enableBinOffsetting(
bool on =
true) { _doBinOffset =
on; }
58 double evaluate()
const override {
return _value; }
67 std::unique_ptr<RooTemplateProxy<RooAbsReal>> _expectedEvents;
68 std::unique_ptr<RooTemplateProxy<RooAbsPdf>> _offsetPdf;
69 mutable double _sumWeight = 0.0;
73 bool _doOffset =
false;
74 bool _doBinOffset =
false;
77 std::vector<double> _binw;
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.
A class to maintain the context for squashing of RooFit models into code.
Mother of all ROOT objects.
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.