RooBinSamplingPdf.h

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// Authors: Stephan Hageboeck, CERN; Andrea Sciandra, SCIPP-UCSC/Atlas; Nov 2020
 
/*****************************************************************************
 * Project: RooFit                                                           *
 * Package: RooFitCore                                                       *
 * Authors:                                                                  *
 *   WV, Wouter Verkerke, UC Santa Barbara, verkerke@slac.stanford.edu       *
 *   DK, David Kirkby,    UC Irvine,         dkirkby@uci.edu                 *
 *                                                                           *
 * Copyright (c) 2000-2018, Regents of the University of California          *
 *                          and Stanford University. All rights reserved.    *
 *                                                                           *
 * Redistribution and use in source and binary forms,                        *
 * with or without modification, are permitted according to the terms        *
 * listed in LICENSE (http://roofit.sourceforge.net/license.txt)             *
 *****************************************************************************/
#ifndef ROO_BIN_SAMPLING__PDF
#define ROO_BIN_SAMPLING__PDF
 
#include "RooAbsReal.h"
#include "RooTemplateProxy.h"
#include "RooAbsPdf.h"
 
#include "Math/Integrator.h"
 
#include <memory>
 
class RooBinSamplingPdf : public RooAbsPdf {
public:
 
  RooBinSamplingPdf() { };
  RooBinSamplingPdf(const char *name, const char *title, RooAbsRealLValue& observable, RooAbsPdf& inputPdf,
      double epsilon = 1.E-4);
  virtual ~RooBinSamplingPdf() {};
 
  RooBinSamplingPdf(const RooBinSamplingPdf& other, const char* name = 0);
 
  virtual TObject* clone(const char* newname) const override {
    return new RooBinSamplingPdf(*this, newname);
  }
 
  // Analytical Integration handling
  Bool_t forceAnalyticalInt(const RooAbsArg& dep) const override {
    return _pdf->forceAnalyticalInt(dep);
  }
  /// Forwards to the PDF's implementation.
  Int_t getAnalyticalIntegralWN(RooArgSet& allVars, RooArgSet& analVars, const RooArgSet* normSet,
      const char* rangeName=0) const override {
    return _pdf->getAnalyticalIntegralWN(allVars, analVars, normSet, rangeName);
  }
  /// Forwards to the PDF's implementation.
  Int_t getAnalyticalIntegral(RooArgSet& allVars, RooArgSet& numVars,
      const char* rangeName=0) const override {
    return _pdf->getAnalyticalIntegral(allVars, numVars, rangeName);
  }
  /// Forwards to the PDF's implementation.
  double analyticalIntegralWN(Int_t code, const RooArgSet* normSet, const char* rangeName) const override {
    return _pdf->analyticalIntegralWN(code, normSet, rangeName);
  }
  /// Forwards to the PDF's implementation.
  double analyticalIntegral(Int_t code, const char* rangeName=0) const override {
    return _pdf->analyticalIntegral(code, rangeName);
  }
 
  /// Since contained PDF is already normalised, this always returns true.
  bool selfNormalized() const override { return true; }
 
  ExtendMode extendMode() const override { return _pdf->extendMode(); }
  using RooAbsPdf::expectedEvents;
  virtual Double_t expectedEvents(const RooArgSet* nset) const override { return _pdf->expectedEvents(nset); }
 
  /// Forwards to the PDF's implementation.
  Int_t getGenerator(const RooArgSet& directVars, RooArgSet& generateVars, bool staticInitOK = true) const override {
    return _pdf->getGenerator(directVars, generateVars, staticInitOK);
  }
  /// Forwards to the PDF's implementation.
  void initGenerator(Int_t code) override { _pdf->initGenerator(code); }
  /// Forwards to the PDF's implementation.
  void generateEvent(Int_t code) override { _pdf->generateEvent(code); }
  /// Forwards to the PDF's implementation.
  Bool_t isDirectGenSafe(const RooAbsArg& arg) const override { return _pdf->isDirectGenSafe(arg); }
 
 
  // Hints for optimized brute-force sampling
  Int_t getMaxVal(const RooArgSet& vars) const override { return _pdf->getMaxVal(vars); }
  Double_t maxVal(Int_t code) const override { return _pdf->maxVal(code); }
  Int_t minTrialSamples(const RooArgSet& arGenObs) const override { return _pdf->minTrialSamples(arGenObs); }
 
  // Plotting and binning hints
  /// Returns true, since this PDF is meant to be binned.
  bool isBinnedDistribution(const RooArgSet& /*obs*/) const override { return true; }
  std::list<double>* binBoundaries(RooAbsRealLValue& obs, Double_t xlo, Double_t xhi) const override;
  std::list<double>* plotSamplingHint(RooAbsRealLValue& obs, double xlo, double xhi) const override;
 
  std::unique_ptr<ROOT::Math::IntegratorOneDim>& integrator() const;
 
 
protected:
  double evaluate() const override;
  RooSpan<double> evaluateSpan(RooBatchCompute::RunContext& evalData, const RooArgSet* normSet) const override;
  RooSpan<const double> binBoundaries() const;
 
private:
  template<typename Func>
  friend class ROOT::Math::WrappedFunction;
  // Call operator for our internal integrator.
  double operator()(double x) const;
  double integrate(const RooArgSet* normSet, double low, double high) const;
 
 
  RooTemplateProxy<RooAbsPdf> _pdf;
  RooTemplateProxy<RooAbsRealLValue> _observable;
  double _relEpsilon{1.E-4}; /// Default integrator precision.
 
  mutable std::unique_ptr<ROOT::Math::IntegratorOneDim> _integrator{nullptr}; //! Integrator used to sample bins.
  mutable std::vector<double> _binBoundaries; //! Workspace to store data for bin sampling
  mutable const RooArgSet* _normSetForIntegrator{nullptr}; //! Normalisation set for operator() calls.
 
  ClassDefOverride(RooBinSamplingPdf,1)
};
 
#endif