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Reference Guide
rs_bernsteinCorrection.C File Reference

Detailed Description

View in nbviewer Open in SWAN Example of the BernsteinCorrection utility in RooStats.

The idea is that one has a distribution coming either from data or Monte Carlo (called "reality" in the macro) and a nominal model that is not sufficiently flexible to take into account the real distribution. One wants to take into account the systematic associated with this imperfect modeling by augmenting the nominal model with some correction term (in this case a polynomial). The BernsteinCorrection utility will import into your workspace a corrected model given by nominal(x) * poly_N(x), where poly_N is an n-th order polynomial in the Bernstein basis. The degree N of the polynomial is chosen by specifying the tolerance one has in adding an extra term to the polynomial. The Bernstein basis is nice because it only has positive-definite terms and works well with PDFs. Finally, the macro makes a plot of:

␛[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby␛[0m
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
All rights reserved, please read http://roofit.sourceforge.net/license.txt
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing dataset realityData
[#1] INFO:ObjectHandling -- RooWorkSpace::import(myWorksspace) changing name of dataset from realityData to data
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::x
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooGaussian::nominal
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooConstVar::0
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::sigma
BernsteinCorrection::ImportCorrectedPdf - Doing initial Fit with nominal model
[#1] INFO:Minization -- createNLL: caching constraint set under name CONSTR_OF_PDF_nominal_FOR_OBS_x with 0 entries
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooEffProd::corrected
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooBernstein::poly
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_0
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_1
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_2
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_3
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_4
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_5
[#1] INFO:ObjectHandling -- RooWorkspace::import(myWorksspace) importing RooRealVar::c_6
------ Begin Bernstein Correction Log --------
degree = 1 -log L(0) = 1216.78 -log L(1) = 1208.89 q = 15.7692 P(chi^2_1 > q) = 7.1557e-05
degree = 2 -log L(1) = 1208.89 -log L(2) = 1203.21 q = 11.3692 P(chi^2_1 > q) = 0.000746732
degree = 3 -log L(2) = 1203.21 -log L(3) = 1198.85 q = 8.72213 P(chi^2_1 > q) = 0.00314371
degree = 4 -log L(3) = 1198.85 -log L(4) = 1190.19 q = 17.3163 P(chi^2_1 > q) = 3.1646e-05
degree = 5 -log L(4) = 1190.19 -log L(5) = 1183.56 q = 13.259 P(chi^2_1 > q) = 0.00027127
degree = 6 -log L(5) = 1183.56 -log L(6) = 1182.57 q = 1.98376 P(chi^2_1 > q) = 0.158995
------ End Bernstein Correction Log --------
Correction based on Bernstein Poly of degree 6
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
Minuit2Minimizer: Minimize with max-calls 500 convergence for edm < 1 strategy 1
Minuit2Minimizer : Valid minimum - status = 0
FVAL = 1216.77793416266263
Edm = 4.16187321843267985e-07
Nfcn = 19
sigma = 1.18138 +/- 0.0315451 (limited)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minization -- createNLL: caching constraint set under name CONSTR_OF_PDF_corrected_FOR_OBS_x with 0 entries
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
Minuit2Minimizer: Minimize with max-calls 3500 convergence for edm < 1 strategy 1
Minuit2Minimizer : Valid minimum - status = 0
FVAL = 1182.56771140342289
Edm = 0.000104058539332425995
Nfcn = 184
c_1 = 3.18369 +/- 0.83541 (limited)
c_2 = 1.25333e-05 +/- 3.09835 (limited)
c_3 = 1.62863e-06 +/- 1.52587 (limited)
c_4 = 0.971397 +/- 2.53146 (limited)
c_5 = 0.199979 +/- 75.676 (limited)
c_6 = 10.5075 +/- 23.0146 (limited)
sigma = 1.26617 +/- 0.232486 (limited)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(corrected_clone_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
made pdfs, make toy generator
on toy 0
on toy 1
on toy 2
on toy 3
on toy 4
on toy 5
on toy 6
on toy 7
on toy 8
on toy 9
on toy 10
on toy 11
on toy 12
on toy 13
on toy 14
on toy 15
on toy 16
on toy 17
on toy 18
on toy 19
#include "RooDataSet.h"
#include "RooRealVar.h"
#include "RooConstVar.h"
#include "RooBernstein.h"
#include "TCanvas.h"
#include "RooAbsPdf.h"
#include "RooFit.h"
#include "RooFitResult.h"
#include "RooPlot.h"
#include <string>
#include <vector>
#include <stdio.h>
#include <sstream>
#include <iostream>
#include "RooProdPdf.h"
#include "RooAddPdf.h"
#include "RooGaussian.h"
#include "RooNLLVar.h"
#include "RooMinuit.h"
#include "RooProfileLL.h"
#include "RooWorkspace.h"
// use this order for safety on library loading
using namespace RooFit;
using namespace RooStats;
//____________________________________
void rs_bernsteinCorrection()
{
// set range of observable
Double_t lowRange = -1, highRange = 5;
// make a RooRealVar for the observable
RooRealVar x("x", "x", lowRange, highRange);
// true model
RooGaussian narrow("narrow", "", x, RooConst(0.), RooConst(.8));
RooGaussian wide("wide", "", x, RooConst(0.), RooConst(2.));
RooAddPdf reality("reality", "", RooArgList(narrow, wide), RooConst(0.8));
RooDataSet *data = reality.generate(x, 1000);
// nominal model
RooRealVar sigma("sigma", "", 1., 0, 10);
RooGaussian nominal("nominal", "", x, RooConst(0.), sigma);
RooWorkspace *wks = new RooWorkspace("myWorksspace");
wks->import(*data, Rename("data"));
wks->import(nominal);
if (TClass::GetClass("ROOT::Minuit2::Minuit2Minimizer")) {
// use Minuit2 if ROOT was built with support for it:
}
// The tolerance sets the probability to add an unnecessary term.
// lower tolerance will add fewer terms, while higher tolerance
// will add more terms and provide a more flexible function.
Double_t tolerance = 0.05;
BernsteinCorrection bernsteinCorrection(tolerance);
Int_t degree = bernsteinCorrection.ImportCorrectedPdf(wks, "nominal", "x", "data");
if (degree < 0) {
Error("rs_bernsteinCorrection", "Bernstein correction failed ! ");
return;
}
cout << " Correction based on Bernstein Poly of degree " << degree << endl;
RooPlot *frame = x.frame();
data->plotOn(frame);
// plot the best fit nominal model in blue
nominal.fitTo(*data, PrintLevel(0), Minimizer(minimType));
nominal.plotOn(frame);
// plot the best fit corrected model in red
RooAbsPdf *corrected = wks->pdf("corrected");
if (!corrected)
return;
// fit corrected model
corrected->fitTo(*data, PrintLevel(0), Minimizer(minimType));
corrected->plotOn(frame, LineColor(kRed));
// plot the correction term (* norm constant) in dashed green
// should make norm constant just be 1, not depend on binning of data
RooAbsPdf *poly = wks->pdf("poly");
if (poly)
// this is a switch to check the sampling distribution
// of -2 log LR for two comparisons:
// the first is for n-1 vs. n degree polynomial corrections
// the second is for n vs. n+1 degree polynomial corrections
// Here we choose n to be the one chosen by the tolerance
// criterion above, eg. n = "degree" in the code.
// Setting this to true is takes about 10 min.
bool checkSamplingDist = true;
int numToyMC = 20; // increase this value for sensible results
TCanvas *c1 = new TCanvas();
if (checkSamplingDist) {
c1->Divide(1, 2);
c1->cd(1);
}
frame->Draw();
gPad->Update();
if (checkSamplingDist) {
// check sampling dist
TH1F *samplingDist = new TH1F("samplingDist", "", 20, 0, 10);
TH1F *samplingDistExtra = new TH1F("samplingDistExtra", "", 20, 0, 10);
bernsteinCorrection.CreateQSamplingDist(wks, "nominal", "x", "data", samplingDist, samplingDistExtra, degree,
numToyMC);
c1->cd(2);
samplingDistExtra->SetLineColor(kRed);
samplingDistExtra->Draw();
samplingDist->Draw("same");
}
}
int Int_t
Definition: RtypesCore.h:41
double Double_t
Definition: RtypesCore.h:55
@ kRed
Definition: Rtypes.h:64
@ kGreen
Definition: Rtypes.h:64
@ kDashed
Definition: TAttLine.h:48
void Error(const char *location, const char *msgfmt,...)
#define gPad
Definition: TVirtualPad.h:286
static void SetDefaultMinimizer(const char *type, const char *algo=0)
static const std::string & DefaultMinimizerType()
static void SetDefaultPrintLevel(int level)
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
Calls RooPlot* plotOn(RooPlot* frame, const RooLinkedList& cmdList) const ;.
Definition: RooAbsData.cxx:552
virtual RooFitResult * fitTo(RooAbsData &data, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none())
Fit PDF to given dataset.
Definition: RooAbsPdf.cxx:1119
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none(), const RooCmdArg &arg9=RooCmdArg::none(), const RooCmdArg &arg10=RooCmdArg::none()) const
Helper calling plotOn(RooPlot*, RooLinkedList&) const.
Definition: RooAbsPdf.h:119
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:29
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:31
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
A RooPlot is a plot frame and a container for graphics objects within that frame.
Definition: RooPlot.h:41
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:558
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
The RooWorkspace is a persistable container for RooFit projects.
Definition: RooWorkspace.h:43
Bool_t import(const RooAbsArg &arg, 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())
Import a RooAbsArg object, e.g.
RooAbsPdf * pdf(const char *name) const
Retrieve p.d.f (RooAbsPdf) with given name. A null pointer is returned if not found.
virtual void SetLineColor(Color_t lcolor)
Set the line color.
Definition: TAttLine.h:40
The Canvas class.
Definition: TCanvas.h:31
static TClass * GetClass(const char *name, Bool_t load=kTRUE, Bool_t silent=kFALSE)
Static method returning pointer to TClass of the specified class name.
Definition: TClass.cxx:2895
1-D histogram with a float per channel (see TH1 documentation)}
Definition: TH1.h:571
virtual void Draw(Option_t *option="")
Draw this histogram with options.
Definition: TH1.cxx:2981
Basic string class.
Definition: TString.h:131
const Double_t sigma
return c1
Definition: legend1.C:41
Double_t x[n]
Definition: legend1.C:17
Template specialisation used in RooAbsArg:
RooCmdArg Rename(const char *suffix)
RooConstVar & RooConst(Double_t val)
RooCmdArg PrintLevel(Int_t code)
RooCmdArg LineColor(Color_t color)
RooCmdArg LineStyle(Style_t style)
RooCmdArg Minimizer(const char *type, const char *alg=0)
Namespace for the RooStats classes.
Definition: Asimov.h:20
static constexpr double degree
Author
Kyle Cranmer

Definition in file rs_bernsteinCorrection.C.