Data and categories: latex printing of lists and sets of RooArgSets
Author: Wouter Verkerke
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Sunday, February 05, 2023 at 11:15 AM.
%%cpp -d
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooChebychev.h"
#include "RooAddPdf.h"
#include "RooExponential.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
using namespace RooFit;
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);
[#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.
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);
Build Chebychev polynomial pdf
RooRealVar a0("a0", "a0", 0.5, 0., 1.);
RooRealVar a1("a1", "a1", 0.2, 0., 1.);
RooChebychev bkg1("bkg1", "Background 1", x, RooArgSet(a0, a1));
Build expontential pdf
RooRealVar alpha("alpha", "alpha", -1);
RooExponential bkg2("bkg2", "Background 2", x, alpha);
Sum the background components into a composite background pdf
RooRealVar bkg1frac("sig1frac", "fraction of component 1 in background", 0.2, 0., 1.);
RooAddPdf bkg("bkg", "Signal", RooArgList(bkg1, bkg2), 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);
Make list of model parameters
RooArgSet *params = model.getParameters(x);
Save snapshot of prefit parameters
RooArgSet *initParams = (RooArgSet *)params->snapshot();
Do fit to data, to obtain error estimates on parameters
RooDataSet *data = model.generate(x, 1000);
model.fitTo(*data);
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization [#1] INFO:Minimization -- The following expressions have been identified as constant and will be precalculated and cached: (bkg2,sig1,sig2) [#1] INFO:Minimization -- The following expressions will be evaluated in cache-and-track mode: (bkg1) ********** ** 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 0.5 ********** ********** ** 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=1963.41 FROM MIGRAD STATUS=INITIATE 14 CALLS 15 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 5.45557e+00 2 a1 2.00000e-01 1.00000e-01 2.57889e-01 2.12468e+00 3 bkgfrac 5.00000e-01 1.00000e-01 2.01358e-01 2.95374e+01 4 sig1frac 8.00000e-01 1.00000e-01 2.57889e-01 1.90239e+01 ERR DEF= 0.5 MIGRAD MINIMIZATION HAS CONVERGED. MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX. COVARIANCE MATRIX CALCULATED SUCCESSFULLY FCN=1960.64 FROM MIGRAD STATUS=CONVERGED 100 CALLS 101 TOTAL EDM=3.75265e-06 STRATEGY= 1 ERROR MATRIX ACCURATE EXT PARAMETER STEP FIRST NO. NAME VALUE ERROR SIZE DERIVATIVE 1 a0 6.45917e-01 2.21997e-01 7.59449e-03 -6.13466e-03 2 a1 2.39717e-01 1.63607e-01 8.68922e-03 8.68189e-04 3 bkgfrac 4.48723e-01 2.86509e-02 1.18450e-03 2.52740e-02 4 sig1frac 7.07467e-01 5.79941e-02 1.94490e-03 -2.93455e-02 ERR DEF= 0.5 EXTERNAL ERROR MATRIX. NDIM= 25 NPAR= 4 ERR DEF=0.5 5.330e-02 -1.068e-02 -1.772e-03 -1.095e-02 -1.068e-02 2.819e-02 -2.571e-03 1.770e-04 -1.772e-03 -2.571e-03 8.218e-04 8.391e-04 -1.095e-02 1.770e-04 8.391e-04 3.382e-03 PARAMETER CORRELATION COEFFICIENTS NO. GLOBAL 1 2 3 4 1 0.85615 1.000 -0.276 -0.268 -0.815 2 0.68971 -0.276 1.000 -0.534 0.018 3 0.74062 -0.268 -0.534 1.000 0.503 4 0.86784 -0.815 0.018 0.503 1.000 ********** ** 7 **SET ERR 0.5 ********** ********** ** 8 **SET PRINT 1 ********** ********** ** 9 **HESSE 2000 ********** COVARIANCE MATRIX CALCULATED SUCCESSFULLY FCN=1960.64 FROM HESSE STATUS=OK 23 CALLS 124 TOTAL EDM=3.75168e-06 STRATEGY= 1 ERROR MATRIX ACCURATE EXT PARAMETER INTERNAL INTERNAL NO. NAME VALUE ERROR STEP SIZE VALUE 1 a0 6.45917e-01 2.21223e-01 1.51890e-03 2.96143e-01 2 a1 2.39717e-01 1.63005e-01 3.47569e-04 -5.47513e-01 3 bkgfrac 4.48723e-01 2.85510e-02 2.36899e-04 -1.02734e-01 4 sig1frac 7.07467e-01 5.77889e-02 3.88981e-04 4.27870e-01 ERR DEF= 0.5 EXTERNAL ERROR MATRIX. NDIM= 25 NPAR= 4 ERR DEF=0.5 5.289e-02 -1.058e-02 -1.763e-03 -1.085e-02 -1.058e-02 2.797e-02 -2.538e-03 1.785e-04 -1.763e-03 -2.538e-03 8.161e-04 8.330e-04 -1.085e-02 1.785e-04 8.330e-04 3.358e-03 PARAMETER CORRELATION COEFFICIENTS NO. GLOBAL 1 2 3 4 1 0.85497 1.000 -0.275 -0.268 -0.814 2 0.68674 -0.275 1.000 -0.531 0.018 3 0.73847 -0.268 -0.531 1.000 0.503 4 0.86683 -0.814 0.018 0.503 1.000 [#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
input_line_57:2:2: warning: 'data' shadows a declaration with the same name in the 'std' namespace; use '::data' to reference this declaration RooDataSet *data = model.generate(x, 1000); ^
Print parameter list in LaTeX for (one column with names, one column with values)
params->printLatex();
\begin{tabular}{lc} $\verb+a0+ $ & $ 0.6\pm 0.2$\\ $\verb+a1+ $ & $ 0.2\pm 0.2$\\ $\verb+alpha+ $ & $ -1.00$\\ $\verb+bkgfrac+ $ & $ 0.45\pm 0.03$\\ $\verb+mean+ $ & $ 5$\\ $\verb+sig1frac+ $ & $ 0.71\pm 0.06$\\ $\verb+sigma1+ $ & $ 0.5$\\ $\verb+sigma2+ $ & $ 1$\\ \end{tabular}
Print parameter list in LaTeX for (names values|names values)
params->printLatex(Columns(2));
\begin{tabular}{lc|lc} $\verb+a0+ $ & $ 0.6\pm 0.2$ & $\verb+mean+ $ & $ 5$\\ $\verb+a1+ $ & $ 0.2\pm 0.2$ & $\verb+sig1frac+ $ & $ 0.71\pm 0.06$\\ $\verb+alpha+ $ & $ -1.00$ & $\verb+sigma1+ $ & $ 0.5$\\ $\verb+bkgfrac+ $ & $ 0.45\pm 0.03$ & $\verb+sigma2+ $ & $ 1$\\ \end{tabular}
Print two parameter lists side by side (name values initvalues)
params->printLatex(Sibling(*initParams));
\begin{tabular}{lcc} $\verb+a0+ $ & $ 0.6\pm 0.2$ & $ 0.5$\\ $\verb+a1+ $ & $ 0.2\pm 0.2$ & $ 0.2$\\ $\verb+alpha+ $ & $ -1.00$ & $-1.00$\\ $\verb+bkgfrac+ $ & $ 0.45\pm 0.03$ & $ 0.5$\\ $\verb+mean+ $ & $ 5$ & $ 5$\\ $\verb+sig1frac+ $ & $ 0.71\pm 0.06$ & $ 0.8$\\ $\verb+sigma1+ $ & $ 0.5$ & $ 0.5$\\ $\verb+sigma2+ $ & $ 1$ & $ 1$\\ \end{tabular}
Print two parameter lists side by side (name values initvalues|name values initvalues)
params->printLatex(Sibling(*initParams), Columns(2));
\begin{tabular}{lcc|lcc} $\verb+a0+ $ & $ 0.6\pm 0.2$ & $ 0.5$ & $\verb+mean+ $ & $ 5$ & $ 5$\\ $\verb+a1+ $ & $ 0.2\pm 0.2$ & $ 0.2$ & $\verb+sig1frac+ $ & $ 0.71\pm 0.06$ & $ 0.8$\\ $\verb+alpha+ $ & $ -1.00$ & $-1.00$ & $\verb+sigma1+ $ & $ 0.5$ & $ 0.5$\\ $\verb+bkgfrac+ $ & $ 0.45\pm 0.03$ & $ 0.5$ & $\verb+sigma2+ $ & $ 1$ & $ 1$\\ \end{tabular}
Write LaTex table to file
params->printLatex(Sibling(*initParams), OutputFile("rf407_latextables.tex"));