rf510_wsnamedsets.C File Reference

Detailed Description

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

 
[#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:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization --  The following expressions will be evaluated in cache-and-track mode: (bkg,sig1,sig2)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization --  The following expressions will be evaluated in cache-and-track mode: (bkg,sig1,sig2)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization --  The following expressions will be evaluated in cache-and-track mode: (bkg,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 mean         5.00000e+00  1.00000e+00    0.00000e+00  1.00000e+01
     5 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        2500           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=1953.02 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  -5.24449e+00
   2  a1           2.00000e-01   1.00000e-01   2.57889e-01  -8.31158e+00
   3  bkgfrac      5.00000e-01   1.00000e-01   2.01358e-01  -1.67086e+01
   4  mean         5.00000e+00   1.00000e+00   2.01358e-01  -1.20616e+02
   5  sig1frac     8.00000e-01   1.00000e-01   2.57889e-01  -8.99606e+00
                               ERR DEF= 0.5
 MIGRAD MINIMIZATION HAS CONVERGED.
 MIGRAD WILL VERIFY CONVERGENCE AND ERROR MATRIX.
 COVARIANCE MATRIX CALCULATED SUCCESSFULLY
 FCN=1949.67 FROM MIGRAD    STATUS=CONVERGED     164 CALLS         165 TOTAL
                     EDM=2.46934e-05    STRATEGY= 1      ERROR MATRIX ACCURATE 
  EXT PARAMETER                                   STEP         FIRST   
  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE 
   1  a0           5.35942e-01   6.82140e-02   4.16868e-03   9.78465e-04
   2  a1           1.95503e-01   7.79188e-02   5.51158e-03   2.08158e-03
   3  bkgfrac      5.40925e-01   2.13219e-02   1.19176e-03   1.14661e-02
   4  mean         5.01914e+00   2.93156e-02   1.77988e-04   4.20703e-01
   5  sig1frac     9.99993e-01   6.58597e-01   3.40053e-02  -3.59510e-03
                               ERR DEF= 0.5
 EXTERNAL ERROR MATRIX.    NDIM=  25    NPAR=  5    ERR DEF=0.5
  4.682e-03  1.464e-04 -2.241e-05 -1.666e-04  1.597e-06 
  1.464e-04  6.151e-03 -6.777e-04 -1.233e-04  1.335e-05 
 -2.241e-05 -6.777e-04  4.549e-04  1.230e-05 -4.750e-06 
 -1.666e-04 -1.233e-04  1.230e-05  8.594e-04 -6.227e-08 
  1.597e-06  1.335e-05 -4.750e-06 -6.227e-08  9.468e-06 
 PARAMETER  CORRELATION COEFFICIENTS  
       NO.  GLOBAL      1      2      3      4      5
        1  0.08648   1.000  0.027 -0.015 -0.083  0.008
        2  0.40890   0.027  1.000 -0.405 -0.054  0.055
        3  0.40825  -0.015 -0.405  1.000  0.020 -0.072
        4  0.09773  -0.083 -0.054  0.020  1.000 -0.001
        5  0.07801   0.008  0.055 -0.072 -0.001  1.000
 **********
 **    7 **SET ERR         0.5
 **********
 **********
 **    8 **SET PRINT           1
 **********
 **********
 **    9 **HESSE        2500
 **********
 COVARIANCE MATRIX CALCULATED SUCCESSFULLY
 FCN=1949.67 FROM HESSE     STATUS=OK             31 CALLS         196 TOTAL
                     EDM=2.47191e-05    STRATEGY= 1      ERROR MATRIX ACCURATE 
  EXT PARAMETER                                INTERNAL      INTERNAL  
  NO.   NAME      VALUE            ERROR       STEP SIZE       VALUE   
   1  a0           5.35942e-01   6.82123e-02   1.66747e-04   7.19468e-02
   2  a1           1.95503e-01   7.77468e-02   2.20463e-04  -6.54793e-01
   3  bkgfrac      5.40925e-01   2.12519e-02   2.38351e-04   8.19410e-02
   4  mean         5.01914e+00   2.93147e-02   3.55975e-05   3.82861e-03
   5  sig1frac     9.99993e-01   6.60187e-01   6.80107e-03   1.56563e+00
                               ERR DEF= 0.5
 EXTERNAL ERROR MATRIX.    NDIM=  25    NPAR=  5    ERR DEF=0.5
  4.682e-03  1.450e-04 -2.161e-05 -1.666e-04 -2.406e-07 
  1.450e-04  6.124e-03 -6.677e-04 -1.218e-04 -2.003e-06 
 -2.161e-05 -6.677e-04  4.519e-04  1.192e-05  7.150e-07 
 -1.666e-04 -1.218e-04  1.192e-05  8.594e-04  9.374e-09 
 -2.406e-07 -2.003e-06  7.150e-07  9.374e-09  9.576e-06 
 PARAMETER  CORRELATION COEFFICIENTS  
       NO.  GLOBAL      1      2      3      4      5
        1  0.08622   1.000  0.027 -0.015 -0.083 -0.001
        2  0.40431   0.027  1.000 -0.401 -0.053 -0.008
        3  0.40145  -0.015 -0.401  1.000  0.019  0.011
        4  0.09742  -0.083 -0.053  0.019  1.000  0.000
        5  0.01172  -0.001 -0.008  0.011  0.000  1.000
[#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 ] = 0.0106966/1
RooGaussian::sig1[ x=x mean=mean sigma=sigma1 ] = 1.19649e-05
RooGaussian::sig2[ x=x mean=mean sigma=sigma2 ] = 0.0588136
 
parameter snapshots
-------------------
reference_fit = (a0=0.500958 +/- 0.0231941,a1=0.160483 +/- 0.0372743,bkgfrac=0.504708 +/- 0.0113925,mean=5.01893 +/- 0.0101204,sigma1=0.5[C],sig1frac=0.818293 +/- 0.0374314,sigma2=1[C])
reference_fit_bkgonly = (a0=0.474267 +/- 0.0211215,a1=2.86676e-12 +/- 0.000176662,bkgfrac=1[C],mean=2.6195 +/- 2.39943,sigma1=0.5[C],sig1frac=0.818293 +/- 0.324473,sigma2=1[C])
 
named sets
----------
observables:(x)
parameters:(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2)
 

 
#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
   RooDataSet *data = model->generate(*w->set("observables"), 1000);
 
   // Fit model to data
   model->fitTo(*data);
 
   // 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
   RooArgSet *params = (RooArgSet *)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
   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);
}

Date

April 2009

Author

Wouter Verkerke

Definition in file rf510_wsnamedsets.C.