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Reference Guide
rf602_chi2fit.C File Reference

Detailed Description

View in nbviewer Open in SWAN Likelihood and minimization: setting up a chi^2 fit to a binned dataset

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 'sigma1' with range [-1e+30, 1e+30] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range.
[#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-1e+30, 1e+30] of the RooGaussian 'sig2' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- The following expressions have been identified as constant and will be precalculated and cached: (sig1,sig2)
**********
** 1 **SET PRINT 1
**********
**********
** 2 **SET NOGRAD
**********
PARAMETER DEFINITIONS:
NO. NAME VALUE STEP SIZE LIMITS
1 a0 5.00000e-01 1.00000e-01 0.00000e+00 1.00000e+00
2 a1 2.00000e-01 1.00000e-01 0.00000e+00 1.00000e+00
3 bkgfrac 5.00000e-01 1.00000e-01 0.00000e+00 1.00000e+00
4 sig1frac 8.00000e-01 1.00000e-01 0.00000e+00 1.00000e+00
**********
** 3 **SET ERR 1
**********
**********
** 4 **SET PRINT 1
**********
**********
** 5 **SET STR 1
**********
NOW USING STRATEGY 1: TRY TO BALANCE SPEED AGAINST RELIABILITY
**********
** 6 **MIGRAD 2000 1
**********
FIRST CALL TO USER FUNCTION AT NEW START POINT, WITH IFLAG=4.
START MIGRAD MINIMIZATION. STRATEGY 1. CONVERGENCE WHEN EDM .LT. 1.00e-03
FCN=106.175 FROM MIGRAD STATUS=INITIATE 16 CALLS 17 TOTAL
EDM= unknown STRATEGY= 1 NO ERROR MATRIX
EXT PARAMETER CURRENT GUESS STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 a0 5.00000e-01 1.00000e-01 2.01358e-01 -9.22919e+00
2 a1 2.00000e-01 1.00000e-01 2.57889e-01 3.56932e+01
3 bkgfrac 5.00000e-01 1.00000e-01 2.01358e-01 2.47046e+01
4 sig1frac 8.00000e-01 1.00000e-01 2.57889e-01 9.71383e+00
MIGRAD MINIMIZATION HAS CONVERGED.
MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.
COVARIANCE MATRIX CALCULATED SUCCESSFULLY
FCN=104.639 FROM MIGRAD STATUS=CONVERGED 78 CALLS 79 TOTAL
EDM=5.30614e-06 STRATEGY= 1 ERROR MATRIX ACCURATE
EXT PARAMETER STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 a0 5.00975e-01 2.29160e-02 2.25835e-04 -3.66627e-02
2 a1 1.58055e-01 3.68598e-02 3.29973e-04 9.16128e-03
3 bkgfrac 5.06726e-01 1.13595e-02 6.50594e-05 4.90783e-02
4 sig1frac 8.16064e-01 3.74255e-02 3.05383e-04 -3.32372e-02
EXTERNAL ERROR MATRIX. NDIM= 25 NPAR= 4 ERR DEF=1
5.255e-04 1.573e-04 -3.988e-05 -1.315e-04
1.573e-04 1.363e-03 -3.100e-04 -9.244e-04
-3.988e-05 -3.100e-04 1.291e-04 3.237e-04
-1.315e-04 -9.244e-04 3.237e-04 1.405e-03
PARAMETER CORRELATION COEFFICIENTS
NO. GLOBAL 1 2 3 4
1 0.18992 1.000 0.186 -0.153 -0.153
2 0.75966 0.186 1.000 -0.739 -0.668
3 0.82130 -0.153 -0.739 1.000 0.760
4 0.77660 -0.153 -0.668 0.760 1.000
**********
** 7 **SET ERR 1
**********
**********
** 8 **SET PRINT 1
**********
**********
** 9 **HESSE 2000
**********
COVARIANCE MATRIX CALCULATED SUCCESSFULLY
FCN=104.639 FROM HESSE STATUS=OK 23 CALLS 102 TOTAL
EDM=5.30457e-06 STRATEGY= 1 ERROR MATRIX ACCURATE
EXT PARAMETER INTERNAL INTERNAL
NO. NAME VALUE ERROR STEP SIZE VALUE
1 a0 5.00975e-01 2.29157e-02 4.51671e-05 1.95002e-03
2 a1 1.58055e-01 3.68515e-02 6.59945e-05 -7.53081e-01
3 bkgfrac 5.06726e-01 1.13574e-02 1.30119e-05 1.34521e-02
4 sig1frac 8.16064e-01 3.74193e-02 6.10765e-05 6.84296e-01
EXTERNAL ERROR MATRIX. NDIM= 25 NPAR= 4 ERR DEF=1
5.255e-04 1.572e-04 -3.986e-05 -1.314e-04
1.572e-04 1.363e-03 -3.098e-04 -9.239e-04
-3.986e-05 -3.098e-04 1.290e-04 3.236e-04
-1.314e-04 -9.239e-04 3.236e-04 1.405e-03
PARAMETER CORRELATION COEFFICIENTS
NO. GLOBAL 1 2 3 4
1 0.18986 1.000 0.186 -0.153 -0.153
2 0.75953 0.186 1.000 -0.739 -0.668
3 0.82122 -0.153 -0.739 1.000 0.760
4 0.77651 -0.153 -0.668 0.760 1.000
[#0] ERROR:Eval -- RooChi2Var::RooChi2Var(chi2_lowstat) INFINITY ERROR: bin 1 has zero error
0
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooChebychev.h"
#include "RooAddPdf.h"
#include "RooChi2Var.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit;
void rf602_chi2fit()
{
// S e t u p m o d e l
// ---------------------
// Declare observable x
RooRealVar x("x", "x", 0, 10);
// Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
RooRealVar mean("mean", "mean of gaussians", 5);
RooRealVar sigma1("sigma1", "width of gaussians", 0.5);
RooRealVar sigma2("sigma2", "width of gaussians", 1);
RooGaussian sig1("sig1", "Signal component 1", x, mean, sigma1);
RooGaussian sig2("sig2", "Signal component 2", x, mean, sigma2);
// Build Chebychev polynomial pdf
RooRealVar a0("a0", "a0", 0.5, 0., 1.);
RooRealVar a1("a1", "a1", 0.2, 0., 1.);
RooChebychev bkg("bkg", "Background", x, RooArgSet(a0, a1));
// Sum the signal components into a composite signal pdf
RooRealVar sig1frac("sig1frac", "fraction of component 1 in signal", 0.8, 0., 1.);
RooAddPdf sig("sig", "Signal", RooArgList(sig1, sig2), sig1frac);
// Sum the composite signal and background
RooRealVar bkgfrac("bkgfrac", "fraction of background", 0.5, 0., 1.);
RooAddPdf model("model", "g1+g2+a", RooArgList(bkg, sig), bkgfrac);
// C r e a t e b i n n e d d a t a s e t
// -----------------------------------------
RooDataSet *d = model.generate(x, 10000);
RooDataHist *dh = d->binnedClone();
// Construct a chi^2 of the data and the model.
// When a pdf is used in a chi^2 fit, the probability density scaled
// by the number of events in the dataset to obtain the fit function
// If model is an extended pdf, the expected number events is used
// instead of the observed number of events.
model.chi2FitTo(*dh);
// NB: It is also possible to fit a RooAbsReal function to a RooDataHist
// using chi2FitTo().
// Note that entries with zero bins are _not_ allowed
// for a proper chi^2 calculation and will give error
// messages
RooDataSet *dsmall = (RooDataSet *)d->reduce(EventRange(1, 100));
RooDataHist *dhsmall = dsmall->binnedClone();
RooChi2Var chi2_lowstat("chi2_lowstat", "chi2", model, *dhsmall);
cout << chi2_lowstat.getVal() << endl;
}
Date
July 2008
Author
Wouter Verkerke

Definition in file rf602_chi2fit.C.

RooChebychev.h
RooAddPdf
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:32
RooFit::EventRange
RooCmdArg EventRange(Int_t nStart, Int_t nStop)
Definition: RooGlobalFunc.cxx:183
RooChebychev
Chebychev polynomial p.d.f.
Definition: RooChebychev.h:25
RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
RooGaussian.h
RooChi2Var
RooChi2Var implements a simple calculation from a binned dataset and a PDF.
Definition: RooChi2Var.h:25
x
Double_t x[n]
Definition: legend1.C:17
RooGaussian
Plain Gaussian p.d.f.
Definition: RooGaussian.h:24
RooAddPdf.h
TCanvas.h
RooDataSet.h
RooChi2Var.h
RooDataHist
The RooDataHist is a container class to hold N-dimensional binned data.
Definition: RooDataHist.h:39
RooFit
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition: RooCFunction1Binding.h:29
RooPlot.h
RooRealVar.h
RooConstVar.h
TAxis.h
RooDataSet::binnedClone
RooDataHist * binnedClone(const char *newName=0, const char *newTitle=0) const
Return binned clone of this dataset.
Definition: RooDataSet.cxx:975
d
#define d(i)
Definition: RSha256.hxx:102
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
RooRealVar
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:37
RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:29