Data and categories: latex printing of lists and sets of RooArgSets
Author: Clemens Lange, Wouter Verkerke (C++ version)
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Wednesday, April 17, 2024 at 11:18 AM.
import ROOT
Declare observable x
x = ROOT.RooRealVar("x", "x", 0, 10)
Create two Gaussian PDFs g1(x,mean1,sigma) anf g2(x,mean2,sigma) and their parameters
mean = ROOT.RooRealVar("mean", "mean of gaussians", 5)
sigma1 = ROOT.RooRealVar("sigma1", "width of gaussians", 0.5)
sigma2 = ROOT.RooRealVar("sigma2", "width of gaussians", 1)
sig1 = ROOT.RooGaussian("sig1", "Signal component 1", x, mean, sigma1)
sig2 = ROOT.RooGaussian("sig2", "Signal component 2", x, mean, sigma2)
[#0] WARNING:InputArguments -- The parameter 'sigma1' with range [-inf, inf] of the RooGaussian 'sig1' exceeds the safe range of (0, inf). Advise to limit its range. [#0] WARNING:InputArguments -- The parameter 'sigma2' with range [-inf, inf] 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
sig1frac = ROOT.RooRealVar("sig1frac", "fraction of component 1 in signal", 0.8, 0.0, 1.0)
sig = ROOT.RooAddPdf("sig", "Signal", [sig1, sig2], [sig1frac])
Build Chebychev polynomial pdf
a0 = ROOT.RooRealVar("a0", "a0", 0.5, 0.0, 1.0)
a1 = ROOT.RooRealVar("a1", "a1", -0.2, 0.0, 1.0)
bkg1 = ROOT.RooChebychev("bkg1", "Background 1", x, [a0, a1])
Build expontential pdf
alpha = ROOT.RooRealVar("alpha", "alpha", -1)
bkg2 = ROOT.RooExponential("bkg2", "Background 2", x, alpha)
Sum the background components into a composite background pdf
bkg1frac = ROOT.RooRealVar("sig1frac", "fraction of component 1 in background", 0.2, 0.0, 1.0)
bkg = ROOT.RooAddPdf("bkg", "Signal", [bkg1, bkg2], [sig1frac])
Sum the composite signal and background
bkgfrac = ROOT.RooRealVar("bkgfrac", "fraction of background", 0.5, 0.0, 1.0)
model = ROOT.RooAddPdf("model", "g1+g2+a", [bkg, sig], [bkgfrac])
Make list of model parameters
params = model.getParameters({x})
Save snapshot of prefit parameters
initParams = params.snapshot()
Do fit to data, obtain error estimates on parameters
data = model.generate({x}, 1000)
model.fitTo(data, PrintLevel=-1)
<cppyy.gbl.RooFitResult object at 0x(nil)>
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data [#1] INFO:Fitting -- using CPU computation library compiled with -mavx2 [#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level [#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization [#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
Print parameter list in LaTeX for (one column with names, column with values)
params.printLatex()
\begin{tabular}{lc} $\verb+a0+ $ & $ 0.5\pm 0.2$\\ $\verb+a1+ $ & $ 0.3\pm 0.1$\\ $\verb+alpha+ $ & $ -1.00$\\ $\verb+bkgfrac+ $ & $ 0.46\pm 0.03$\\ $\verb+mean+ $ & $ 5$\\ $\verb+sig1frac+ $ & $ 0.79\pm 0.05$\\ $\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+ $ & $ 0.5\pm 0.2$ & $\verb+mean+ $ & $ 5$\\ $\verb+a1+ $ & $ 0.3\pm 0.1$ & $\verb+sig1frac+ $ & $ 0.79\pm 0.05$\\ $\verb+alpha+ $ & $ -1.00$ & $\verb+sigma1+ $ & $ 0.5$\\ $\verb+bkgfrac+ $ & $ 0.46\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+ $ & $ 0.5\pm 0.2$ & $ 0.5$\\ $\verb+a1+ $ & $ 0.3\pm 0.1$ & $ 0$\\ $\verb+alpha+ $ & $ -1.00$ & $-1.00$\\ $\verb+bkgfrac+ $ & $ 0.46\pm 0.03$ & $ 0.5$\\ $\verb+mean+ $ & $ 5$ & $ 5$\\ $\verb+sig1frac+ $ & $ 0.79\pm 0.05$ & $ 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+ $ & $ 0.5\pm 0.2$ & $ 0.5$ & $\verb+mean+ $ & $ 5$ & $ 5$\\ $\verb+a1+ $ & $ 0.3\pm 0.1$ & $ 0$ & $\verb+sig1frac+ $ & $ 0.79\pm 0.05$ & $ 0.8$\\ $\verb+alpha+ $ & $ -1.00$ & $-1.00$ & $\verb+sigma1+ $ & $ 0.5$ & $ 0.5$\\ $\verb+bkgfrac+ $ & $ 0.46\pm 0.03$ & $ 0.5$ & $\verb+sigma2+ $ & $ 1$ & $ 1$\\ \end{tabular}
Write LaTex table to file
params.printLatex(Sibling=initParams, OutputFile="rf407_latextables.tex")