rf510_wsnamedsets.C File Reference

Detailed Description

Organization and simultaneous fits: working with named parameter sets and parameter snapshots in workspaces

 
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooChebychev.h"
#include "RooAddPdf.h"
#include "RooWorkspace.h"
#include "RooPlot.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "TFile.h"
#include "TH1.h"
 
using namespace RooFit;
 
void fillWorkspace(RooWorkspace &w);
 
void rf510_wsnamedsets()
{
   // C r e a t e   m o d e l   a n d   d a t a s e t
   // -----------------------------------------------
 
   RooWorkspace *w = new RooWorkspace("w");
   fillWorkspace(*w);
 
   // Exploit convention encoded in named set "parameters" and "observables"
   // to use workspace contents w/o need for introspected
   RooAbsPdf *model = w->pdf("model");
 
   // Generate data from pdf in given observables
   std::unique_ptr<RooDataSet> data{model->generate(*w->set("observables"), 1000)};
 
   // Fit model to data
   model->fitTo(*data, PrintLevel(-1));
 
   // Plot fitted model and data on frame of first (only) observable
   RooPlot *frame = ((RooRealVar *)w->set("observables")->first())->frame();
   data->plotOn(frame);
   model->plotOn(frame);
 
   // Overlay plot with model with reference parameters as stored in snapshots
   w->loadSnapshot("reference_fit");
   model->plotOn(frame, LineColor(kRed));
   w->loadSnapshot("reference_fit_bkgonly");
   model->plotOn(frame, LineColor(kRed), LineStyle(kDashed));
 
   // Draw the frame on the canvas
   new TCanvas("rf510_wsnamedsets", "rf503_wsnamedsets", 600, 600);
   gPad->SetLeftMargin(0.15);
   frame->GetYaxis()->SetTitleOffset(1.4);
   frame->Draw();
 
   // Print workspace contents
   w->Print();
 
   // Workspace will remain in memory after macro finishes
   gDirectory->Add(w);
}
 
void fillWorkspace(RooWorkspace &w)
{
   // C r e a t e   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, 0, 10);
   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);
 
   // Import model into pdf
   w.import(model);
 
   // E n c o d e   d e f i n i t i o n   o f   p a r a m e t e r s   i n   w o r k s p a c e
   // ---------------------------------------------------------------------------------------
 
   // Define named sets "parameters" and "observables", which list which variables should be considered
   // parameters and observables by the users convention
   //
   // Variables appearing in sets _must_ live in the workspace already, or the autoImport flag
   // of defineSet must be set to import them on the fly. Named sets contain only references
   // to the original variables, therefore the value of observables in named sets already
   // reflect their 'current' value
   std::unique_ptr<RooArgSet> params{model.getParameters(x)};
   w.defineSet("parameters", *params);
   w.defineSet("observables", x);
 
   // E n c o d e   r e f e r e n c e   v a l u e   f o r   p a r a m e t e r s   i n   w o r k s p a c e
   // ---------------------------------------------------------------------------------------------------
 
   // Define a parameter 'snapshot' in the pdf
   // Unlike a named set, a parameter snapshot stores an independent set of values for
   // a given set of variables in the workspace. The values can be stored and reloaded
   // into the workspace variable objects using the loadSnapshot() and saveSnapshot()
   // methods. A snapshot saves the value of each variable, any errors that are stored
   // with it as well as the 'Constant' flag that is used in fits to determine if a
   // parameter is kept fixed or not.
 
   // Do a dummy fit to a (supposedly) reference dataset here and store the results
   // of that fit into a snapshot
   std::unique_ptr<RooDataSet> refData{model.generate(x, 10000)};
   model.fitTo(*refData, PrintLevel(-1));
 
   // The true flag imports the values of the objects in (*params) into the workspace
   // If not set, the present values of the workspace parameters objects are stored
   w.saveSnapshot("reference_fit", *params, true);
 
   // Make another fit with the signal component forced to zero
   // and save those parameters too
 
   bkgfrac.setVal(1);
   bkgfrac.setConstant(true);
   bkgfrac.removeError();
   model.fitTo(*refData, PrintLevel(-1));
 
   w.saveSnapshot("reference_fit_bkgonly", *params, true);
}

 
[#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.
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::model
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooChebychev::bkg
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::x
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a0
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::a1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::bkgfrac
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooAddPdf::sig
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::mean
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma1
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sig1frac
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooGaussian::sig2
[#1] INFO:ObjectHandling -- RooWorkspace::import(w) importing RooRealVar::sigma2
[#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
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#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
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#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
 
RooWorkspace(w) w contents
 
variables
---------
(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2,x)
 
p.d.f.s
-------
RooChebychev::bkg[ x=x coefList=(a0,a1) ] = 1
RooAddPdf::model[ bkgfrac * bkg + [%] * sig ] = 1/1
RooAddPdf::sig[ sig1frac * sig1 + [%] * sig2 ] = 0.999388/1
RooGaussian::sig1[ x=x mean=mean sigma=sigma1 ] = 0.999291
RooGaussian::sig2[ x=x mean=mean sigma=sigma2 ] = 0.999823
 
parameter snapshots
-------------------
reference_fit = (a0=0.500613 +/- 0.023199,a1=0.160315 +/- 0.0373121,bkgfrac=0.504699 +/- 0.0113933,mean=5.01883 +/- 0.0101222,sigma1=0.5[C],sig1frac=0.8179 +/- 0.0374037,sigma2=1[C])
reference_fit_bkgonly = (a0=0.474264 +/- 0,a1=6.8252e-12 +/- 0,bkgfrac=1[C],mean=5.01883 +/- 0,sigma1=0.5[C],sig1frac=0.8179 +/- 0,sigma2=1[C])
 
named sets
----------
observables:(x)
parameters:(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2)
 

Date

April 2009

Author

Wouter Verkerke

Definition in file rf510_wsnamedsets.C.