'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #316
Using the likelihood ratio technique to construct a signal enhanced one-dimensional projection of a multi-dimensional p.d.f.
Processing /mnt/build/workspace/root-makedoc-v612/rootspi/rdoc/src/v6-12-00-patches/tutorials/roofit/rf316_llratioplot.C...
[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:Plotting -- RooAbsReal::plotOn(model) plot on x integrates over variables (y,z)
[#1] INFO:Plotting -- RooAbsReal::plotOn(model) plot on x averages using data variables (y,z)
[#1] INFO:Plotting -- RooAbsReal::plotOn(model) only the following components of the projection data will be used: (y,z)
[#1] INFO:Plotting -- RooDataWeightedAverage::ctor(modelDataWgtAvg) constructing data weighted average of function model_Norm[x] over 767 data points of (y,z) with a total weight of 767
[#1] INFO:Minization -- The following expressions have been identified as constant and will be precalculated and cached: (gy,gz,py,pz)
.................................................................................................................................................
void rf316_llratioplot()
{
RooRealVar fsig(
"fsig",
"signal fraction",0.1,0.,1.) ;
RooPlot* frame = x.frame(
Title(
"Projection of 3D data and pdf on X"),
Bins(40)) ;
model.plotOn(frame) ;
RooAbsPdf* totyz = model.createProjection(x) ;
RooPlot* frame2 = x.frame(
Title(
"Same projection on X with LLratio(y,z)>0.7"),
Bins(40)) ;
model.plotOn(frame2,
ProjWData(*mcprojDataSel)) ;
TCanvas* c =
new TCanvas(
"rf316_llratioplot",
"rf316_llratioplot",800,400) ;
}
- Author
- 07/2008 - Wouter Verkerke
Definition in file rf316_llratioplot.C.