/usr/include/root/RooStats/MinNLLTestStat.h is in libroot-roofit-dev 5.34.00-2.
This file is owned by root:root, with mode 0o644.
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// Author: Kyle Cranmer, Lorenzo Moneta, Gregory Schott, Wouter Verkerke
// Additional Contributions: Giovanni Petrucciani
/*************************************************************************
* Copyright (C) 1995-2008, Rene Brun and Fons Rademakers. *
* All rights reserved. *
* *
* For the licensing terms see $ROOTSYS/LICENSE. *
* For the list of contributors see $ROOTSYS/README/CREDITS. *
*************************************************************************/
#ifndef ROOSTATS_MinNLLTestStat
#define ROOSTATS_MinNLLTestStat
//_________________________________________________
/*
BEGIN_HTML
<p>
MinNLLTestStat is an implementation of the TestStatistic interface that calculates the minimum value of the negative log likelihood
function and returns it as a test statistic.
Internaly it operates by delegating to a MinNLLTestStat object.
</p>
END_HTML
*/
//
#ifndef ROOT_Rtypes
#include "Rtypes.h"
#endif
#include <vector>
#include "RooStats/RooStatsUtils.h"
//#include "RooStats/DistributionCreator.h"
#include "RooStats/SamplingDistribution.h"
#include "RooStats/TestStatistic.h"
#include "RooStats/RooStatsUtils.h"
#include "RooRealVar.h"
#include "RooProfileLL.h"
#include "RooNLLVar.h"
#include "RooMsgService.h"
#include "RooMinuit.h"
#include "RooMinimizer.h"
#include "Math/MinimizerOptions.h"
#include "TStopwatch.h"
#include "ProfileLikelihoodTestStat.h"
namespace RooStats {
class MinNLLTestStat : public TestStatistic{
public:
MinNLLTestStat() {
// Proof constructor. Do not use.
fProflts = 0;
}
MinNLLTestStat(RooAbsPdf& pdf) {
fProflts = new ProfileLikelihoodTestStat(pdf);
}
MinNLLTestStat(const MinNLLTestStat& rhs) : fProflts(0) {
RooAbsPdf * pdf = rhs.fProflts->GetPdf();
if (pdf) fProflts = new ProfileLikelihoodTestStat(*pdf);
}
MinNLLTestStat & operator=(const MinNLLTestStat& rhs) {
if (this == &rhs) return *this;
RooAbsPdf * pdf = rhs.fProflts->GetPdf();
if (fProflts) delete fProflts;
fProflts = NULL;
if (pdf) fProflts = new ProfileLikelihoodTestStat(*pdf);
return *this;
}
virtual ~MinNLLTestStat() {
delete fProflts;
}
void SetOneSided(Bool_t flag=true) {fProflts->SetOneSided(flag);}
void SetOneSidedDiscovery(Bool_t flag=true) {fProflts->SetOneSidedDiscovery(flag);}
void SetReuseNLL(Bool_t flag) { fProflts->SetReuseNLL(flag); }
void SetMinimizer(const char* minimizer){ fProflts->SetMinimizer(minimizer); }
void SetStrategy(Int_t strategy){ fProflts->SetStrategy(strategy); }
void SetTolerance(double tol){ fProflts->SetTolerance(tol); }
void SetPrintLevel(Int_t printlevel){ fProflts->SetPrintLevel(printlevel); }
// Main interface to evaluate the test statistic on a dataset
virtual Double_t Evaluate(RooAbsData& data, RooArgSet& paramsOfInterest) {
return fProflts->EvaluateProfileLikelihood(1, data, paramsOfInterest); //find unconditional NLL minimum
}
virtual void EnableDetailedOutput( bool e=true ) { fProflts->EnableDetailedOutput(e); }
virtual const RooArgSet* GetDetailedOutput(void) const {
// Returns detailed output. The value returned by this function is updated after each call to Evaluate().
// The returned RooArgSet contains the following:
// <ul>
// <li> the minimum nll, fitstatus and convergence quality for each fit </li>
// <li> for all non-constant parameters their value, error and pull </li>
// </ul>
return fProflts->GetDetailedOutput();
}
virtual void SetVarName(const char* name) { fProflts->SetVarName(name); }
virtual const TString GetVarName() const { return fProflts->GetVarName(); }
private:
ProfileLikelihoodTestStat* fProflts;
protected:
ClassDef(MinNLLTestStat,1) // implements the minimum NLL as a test statistic to be used with several tools
};
}
#endif
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