rf606_nllerrorhandling.C File Reference

Detailed Description

Likelihood and minimization: understanding and customizing error handling in likelihood evaluations

 
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooArgusBG.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit;
 
void rf606_nllerrorhandling()
{
   // C r e a t e   m o d e l  a n d   d a t a s e t
   // ----------------------------------------------
 
   // Observable
   RooRealVar m("m", "m", 5.20, 5.30);
 
   // Parameters
   RooRealVar m0("m0", "m0", 5.291, 5.20, 5.30);
   RooRealVar k("k", "k", -30, -50, -10);
 
   // Pdf
   RooArgusBG argus("argus", "argus", m, m0, k);
 
   // Sample 1000 events in m from argus
   std::unique_ptr<RooDataSet> data{argus.generate(m, 1000)};
 
   // P l o t   m o d e l   a n d   d a t a
   // --------------------------------------
 
   RooPlot *frame1 = m.frame(Bins(40), Title("Argus model and data"));
   data->plotOn(frame1);
   argus.plotOn(frame1);
 
   // F i t   m o d e l   t o   d a t a
   // ---------------------------------
 
   // The ARGUS background shape has a sharp kinematic cutoff at m=m0
   // and is prone to evaluation errors if the cutoff parameter m0
   // is floated: when the pdf cutoff value is lower than that in data
   // events with m>m0 will have zero probability
 
   // Perform unbinned ML fit. Print detailed error messages for up to
   // 10 events per likelihood evaluation. The default error handling strategy
   // is to return a very high value of the likelihood to MINUIT if errors occur,
   // which will force MINUIT to retreat from the problematic area
 
   argus.fitTo(*data, PrintEvalErrors(10));
 
   // Perform another fit. In this configuration only the number of errors per
   // likelihood evaluation is shown, if it is greater than zero. The
   // EvalErrorWall(false) arguments disables the default error handling strategy
   // and will cause the actual (problematic) value of the likelihood to be passed
   // to MINUIT.
   //
   // NB: Use of this option is NOT recommended as default strategy as broken -log(L) values
   // can often be lower than 'good' ones because offending events are removed.
   // This may effectively create a false minimum in problem areas. This is clearly
   // illustrated in the second plot
 
   m0.setError(0.1);
   argus.fitTo(*data, PrintEvalErrors(0), EvalErrorWall(false));
 
   // P l o t   l i k e l i h o o d   a s   f u n c t i o n   o f   m 0
   // ------------------------------------------------------------------
 
   // Construct likelihood function of model and data
   std::unique_ptr<RooAbsReal> nll{argus.createNLL(*data)};
 
   // Plot likelihood in m0 in range that includes problematic values
   // In this configuration no messages are printed for likelihood evaluation errors,
   // but if an likelihood value evaluates with error, the corresponding value
   // on the curve will be set to the value given in EvalErrorValue().
 
   RooPlot *frame2 = m0.frame(Range(5.288, 5.293), Title("-log(L) scan vs m0, problematic regions masked"));
   nll->plotOn(frame2, PrintEvalErrors(-1), ShiftToZero(), EvalErrorValue(nll->getVal() + 10), LineColor(kRed));
   frame2->SetMaximum(15);
   frame2->SetMinimum(0);
 
   TCanvas *c = new TCanvas("rf606_nllerrorhandling", "rf606_nllerrorhandling", 1200, 400);
   c->Divide(2);
   c->cd(1);
   gPad->SetLeftMargin(0.15);
   frame1->GetYaxis()->SetTitleOffset(1.4);
   frame1->Draw();
   c->cd(2);
   gPad->SetLeftMargin(0.15);
   frame2->GetYaxis()->SetTitleOffset(1.4);
   frame2->Draw();
}

 
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
Minuit2Minimizer: Minimize with max-calls 1000 convergence for edm < 1 strategy 1
RooAbsMinimizerFcn: Minimized function has error status.
Returning maximum FCN so far (-2417.08) to force MIGRAD to back out of this region. Error log follows.
Parameter values:    k=-33.8075  m0=5.29014
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ]
     function value is NAN @ parameters=(k = -33.8075,m0 = 5.29014)
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ]
     getLogVal() top-level p.d.f evaluates to zero @ m=m=5.29019, m0=m0=5.29014, c=k=-33.8075, p=0.5=0.5
 
RooAbsMinimizerFcn: Minimized function has error status.
Returning maximum FCN so far (-2417.08) to force MIGRAD to back out of this region. Error log follows.
Parameter values:    k=-36.7074  m0=5.2901
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ]
     function value is NAN @ parameters=(k = -36.7074,m0 = 5.2901)
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ]
     getLogVal() top-level p.d.f evaluates to zero @ m=m=5.29019, m0=m0=5.2901, c=k=-36.7074, p=0.5=0.5
 
Minuit2Minimizer : Valid minimum - status = 0
FVAL  = -2419.30692128725559
Edm   = 2.90497786168460102e-06
Nfcn  = 47
k    = -35.3713    +/-  3.51942  (limited)
m0   = 5.2904   +/-  0.000261877 (limited)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
Minuit2Minimizer: Minimize with max-calls 1000 convergence for edm < 1 strategy 1
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.28877
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 4 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=nan m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=nan
RooRealIntegral::argus_Int[m][ Int argusd[Ana](m) ] has 1 errors
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 2000 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.27133
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 166 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.28726
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 9 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.2898
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 1 errors
 
Minuit2Minimizer : Invalid Minimum - status = 3
FVAL  = -2419.31
Edm   = -nan
Nfcn  = 34
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.2898
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 1 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.28374
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 44 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.27133
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 166 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.28726
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 9 errors
 
RooAbsMinimizerFcn: Minimized function has error status but is ignored.
Parameter values:    k=-35.3713  m0=5.2898
RooNLLVar::nll_argus_argusData[ parameters=(k,m0) ] has 1 errors
RooArgusBG::argus[ m=m m0=m0 c=k p=0.5 ] has 1 errors
 
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization

Date

July 2008

Author

Wouter Verkerke

Definition in file rf606_nllerrorhandling.C.