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Reference Guide
rf605_profilell.C File Reference

Detailed Description

View in nbviewer Open in SWAN Likelihood and minimization: working with the profile likelihood estimator

RooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
All rights reserved, please read http://roofit.sourceforge.net/license.txt
[#0] WARNING:InputArguments -- The parameter 'sigma_g1' with range [-1e+30, 1e+30] of the RooGaussian 'g1' exceeds the safe range of (0, inf). Advise to limit its range.
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** 1 **SET PRINT 1
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** 2 **SET NOGRAD
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PARAMETER DEFINITIONS:
NO. NAME VALUE STEP SIZE LIMITS
1 frac 5.00000e-01 1.00000e-01 0.00000e+00 1.00000e+00
2 mean 0.00000e+00 2.00000e+00 -1.00000e+01 1.00000e+01
3 sigma_g2 4.00000e+00 3.00000e-01 3.00000e+00 6.00000e+00
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** 3 **SET ERR 0.5
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** 4 **SET PRINT 1
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** 5 **SET STR 1
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NOW USING STRATEGY 1: TRY TO BALANCE SPEED AGAINST RELIABILITY
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** 6 **MIGRAD 1500 1
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FIRST CALL TO USER FUNCTION AT NEW START POINT, WITH IFLAG=4.
[#1] INFO:Eval -- RooAbsTestStatistic::initMPMode: started 2 remote server process.
START MIGRAD MINIMIZATION. STRATEGY 1. CONVERGENCE WHEN EDM .LT. 1.00e-03
FCN=2660.22 FROM MIGRAD STATUS=INITIATE 10 CALLS 11 TOTAL
EDM= unknown STRATEGY= 1 NO ERROR MATRIX
EXT PARAMETER CURRENT GUESS STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 frac 5.00000e-01 1.00000e-01 2.01358e-01 -5.61980e+00
2 mean 0.00000e+00 2.00000e+00 2.01358e-01 -7.16779e+00
3 sigma_g2 4.00000e+00 3.00000e-01 2.14402e-01 7.28535e+00
ERR DEF= 0.5
MIGRAD MINIMIZATION HAS CONVERGED.
MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.
COVARIANCE MATRIX CALCULATED SUCCESSFULLY
FCN=2659.74 FROM MIGRAD STATUS=CONVERGED 67 CALLS 68 TOTAL
EDM=5.19798e-06 STRATEGY= 1 ERROR MATRIX ACCURATE
EXT PARAMETER STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 frac 6.23972e-01 1.64510e-01 5.33134e-03 6.83204e-03
2 mean 4.57491e-03 1.09369e-01 3.87767e-04 -1.84350e-01
3 sigma_g2 4.11576e+00 4.07375e-01 4.33560e-03 -6.97269e-03
ERR DEF= 0.5
EXTERNAL ERROR MATRIX. NDIM= 25 NPAR= 3 ERR DEF=0.5
2.817e-02 -1.610e-03 6.258e-02
-1.610e-03 1.196e-02 -4.302e-03
6.258e-02 -4.302e-03 1.705e-01
PARAMETER CORRELATION COEFFICIENTS
NO. GLOBAL 1 2 3
1 0.90293 1.000 -0.088 0.903
2 0.09533 -0.088 1.000 -0.095
3 0.90308 0.903 -0.095 1.000
[#1] INFO:Eval -- RooAbsTestStatistic::initMPMode: started 2 remote server process.
[#1] INFO:Eval -- RooAbsTestStatistic::initMPMode: started 2 remote server process.
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[frac]) Creating instance of MINUIT
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[frac]) determining minimum likelihood for current configurations w.r.t all observable
[#1] INFO:Eval -- RooAbsTestStatistic::initMPMode: started 2 remote server process.
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[frac]) minimum found at (frac=0.623915)
..................................................................................
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[sigma_g2]) Creating instance of MINUIT
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[sigma_g2]) determining minimum likelihood for current configurations w.r.t all observable
[#1] INFO:Eval -- RooAbsTestStatistic::initMPMode: started 2 remote server process.
[#1] INFO:Minization -- RooProfileLL::evaluate(nll_model_modelData_Profile[sigma_g2]) minimum found at (sigma_g2=4.11588)
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#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooAddPdf.h"
#include "RooMinimizer.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit;
void rf605_profilell()
{
// C r e a t e m o d e l a n d d a t a s e t
// -----------------------------------------------
// Observable
RooRealVar x("x", "x", -20, 20);
// Model (intentional strong correlations)
RooRealVar mean("mean", "mean of g1 and g2", 0, -10, 10);
RooRealVar sigma_g1("sigma_g1", "width of g1", 3);
RooGaussian g1("g1", "g1", x, mean, sigma_g1);
RooRealVar sigma_g2("sigma_g2", "width of g2", 4, 3.0, 6.0);
RooGaussian g2("g2", "g2", x, mean, sigma_g2);
RooRealVar frac("frac", "frac", 0.5, 0.0, 1.0);
RooAddPdf model("model", "model", RooArgList(g1, g2), frac);
// Generate 1000 events
RooDataSet *data = model.generate(x, 1000);
// C o n s t r u c t p l a i n l i k e l i h o o d
// ---------------------------------------------------
// Construct unbinned likelihood
RooAbsReal *nll = model.createNLL(*data, NumCPU(2));
// Minimize likelihood w.r.t all parameters before making plots
// Plot likelihood scan frac
RooPlot *frame1 = frac.frame(Bins(10), Range(0.01, 0.95), Title("LL and profileLL in frac"));
nll->plotOn(frame1, ShiftToZero());
// Plot likelihood scan in sigma_g2
RooPlot *frame2 = sigma_g2.frame(Bins(10), Range(3.3, 5.0), Title("LL and profileLL in sigma_g2"));
nll->plotOn(frame2, ShiftToZero());
// C o n s t r u c t p r o f i l e l i k e l i h o o d i n f r a c
// -----------------------------------------------------------------------
// The profile likelihood estimator on nll for frac will minimize nll w.r.t
// all floating parameters except frac for each evaluation
RooAbsReal *pll_frac = nll->createProfile(frac);
// Plot the profile likelihood in frac
pll_frac->plotOn(frame1, LineColor(kRed));
// Adjust frame maximum for visual clarity
frame1->SetMinimum(0);
frame1->SetMaximum(3);
// C o n s t r u c t p r o f i l e l i k e l i h o o d i n s i g m a _ g 2
// -------------------------------------------------------------------------------
// The profile likelihood estimator on nll for sigma_g2 will minimize nll
// w.r.t all floating parameters except sigma_g2 for each evaluation
RooAbsReal *pll_sigmag2 = nll->createProfile(sigma_g2);
// Plot the profile likelihood in sigma_g2
pll_sigmag2->plotOn(frame2, LineColor(kRed));
// Adjust frame maximum for visual clarity
frame2->SetMinimum(0);
frame2->SetMaximum(3);
// Make canvas and draw RooPlots
TCanvas *c = new TCanvas("rf605_profilell", "rf605_profilell", 800, 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();
delete pll_frac;
delete pll_sigmag2;
delete nll;
}
Date
July 2008
Author
Wouter Verkerke

Definition in file rf605_profilell.C.

c
#define c(i)
Definition: RSha256.hxx:101
RooPlot::Draw
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:691
RooAddPdf
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:32
RooFit::Bins
RooCmdArg Bins(Int_t nbin)
Definition: RooGlobalFunc.cxx:177
RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
RooGaussian.h
RooFit::ShiftToZero
RooCmdArg ShiftToZero()
Definition: RooGlobalFunc.cxx:51
RooPlot::SetMaximum
virtual void SetMaximum(Double_t maximum=-1111)
Set maximum value of Y axis.
Definition: RooPlot.cxx:1081
RooMinimizer::migrad
Int_t migrad()
Execute MIGRAD.
Definition: RooMinimizer.cxx:344
x
Double_t x[n]
Definition: legend1.C:17
RooGaussian
Plain Gaussian p.d.f.
Definition: RooGaussian.h:24
RooAddPdf.h
RooAbsReal
RooAbsReal is the common abstract base class for objects that represent a real value and implements f...
Definition: RooAbsReal.h:61
TCanvas.h
RooDataSet.h
RooPlot::frame
static RooPlot * frame(const RooAbsRealLValue &var, Double_t xmin, Double_t xmax, Int_t nBins)
Create a new frame for a given variable in x.
Definition: RooPlot.cxx:249
RooFit
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition: RooCFunction1Binding.h:29
RooPlot.h
RooPlot::GetYaxis
TAxis * GetYaxis() const
Definition: RooPlot.cxx:1258
RooPlot
A RooPlot is a plot frame and a container for graphics objects within that frame.
Definition: RooPlot.h:44
RooRealVar.h
kRed
@ kRed
Definition: Rtypes.h:66
RooConstVar.h
RooAbsReal::plotOn
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg(), const RooCmdArg &arg2=RooCmdArg(), const RooCmdArg &arg3=RooCmdArg(), const RooCmdArg &arg4=RooCmdArg(), const RooCmdArg &arg5=RooCmdArg(), const RooCmdArg &arg6=RooCmdArg(), const RooCmdArg &arg7=RooCmdArg(), const RooCmdArg &arg8=RooCmdArg(), const RooCmdArg &arg9=RooCmdArg(), const RooCmdArg &arg10=RooCmdArg()) const
Plot (project) PDF on specified frame.
Definition: RooAbsReal.cxx:1730
RooAbsReal::createProfile
virtual RooAbsReal * createProfile(const RooArgSet &paramsOfInterest)
Create a RooProfileLL object that eliminates all nuisance parameters in the present function.
Definition: RooAbsReal.cxx:529
RooFit::NumCPU
RooCmdArg NumCPU(Int_t nCPU, Int_t interleave=0)
Definition: RooGlobalFunc.cxx:158
RooFit::LineColor
RooCmdArg LineColor(Color_t color)
Definition: RooGlobalFunc.cxx:57
TCanvas
The Canvas class.
Definition: TCanvas.h:23
RooMinimizer.h
TAxis.h
RooFit::Range
RooCmdArg Range(const char *rangeName, Bool_t adjustNorm=kTRUE)
Definition: RooGlobalFunc.cxx:53
RooPlot::SetMinimum
virtual void SetMinimum(Double_t minimum=-1111)
Set minimum value of Y axis.
Definition: RooPlot.cxx:1091
gPad
#define gPad
Definition: TVirtualPad.h:287
RooDataSet
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
make_cnn_model.model
model
Definition: make_cnn_model.py:6
TAttAxis::SetTitleOffset
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:293
RooRealVar
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:37
RooMinimizer
RooMinimizer is a wrapper class around ROOT::Fit:Fitter that provides a seamless interface between th...
Definition: RooMinimizer.h:40
RooFit::Title
RooCmdArg Title(const char *name)
Definition: RooGlobalFunc.cxx:176