# rf510_wsnamedsets¶

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

Author: Wouter Verkerke
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Wednesday, November 30, 2022 at 11:23 AM.

In [1]:
%%cpp -d
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooChebychev.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);


Definition of a helper function:

In [2]:
%%cpp -d
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);
}


## Create model and dataset¶

In [3]:
RooWorkspace *w = new RooWorkspace("w");
fillWorkspace(*w);

[#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.
[#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


Exploit convention encoded in named set "parameters" and "observables" to use workspace contents w/o need for introspected

In [4]:
RooAbsPdf *model = w->pdf("model");


Generate data from pdf in given observables

In [5]:
RooDataSet *data = model->generate(*w->set("observables"), 1000);

input_line_72:2:2: warning: 'data' shadows a declaration with the same name in the 'std' namespace; use '::data' to reference this declaration
RooDataSet *data = model->generate(*w->set("observables"), 1000);
^


Fit model to data

In [6]:
model->fitTo(*data);

input_line_73:2:16: error: reference to 'data' is ambiguous
model->fitTo(*data);
^
input_line_72:2:14: note: candidate found by name lookup is '__cling_N523::data'
RooDataSet *data = model->generate(*w->set("observables"), 1000);
^
/usr/include/c++/9/bits/range_access.h:318:5: note: candidate found by name lookup is 'std::data'
data(initializer_list<_Tp> __il) noexcept
^
/usr/include/c++/9/bits/range_access.h:289:5: note: candidate found by name lookup is 'std::data'
data(_Container& __cont) noexcept(noexcept(__cont.data()))
^
/usr/include/c++/9/bits/range_access.h:299:5: note: candidate found by name lookup is 'std::data'
data(const _Container& __cont) noexcept(noexcept(__cont.data()))
^
/usr/include/c++/9/bits/range_access.h:309:5: note: candidate found by name lookup is 'std::data'
data(_Tp (&__array)[_Nm]) noexcept
^


Plot fitted model and data on frame of first (only) observable

In [7]:
RooPlot *frame = ((RooRealVar *)w->set("observables")->first())->frame();
data->plotOn(frame);
model->plotOn(frame);

input_line_74:3:1: error: reference to 'data' is ambiguous
data->plotOn(frame);
^
input_line_72:2:14: note: candidate found by name lookup is '__cling_N523::data'
RooDataSet *data = model->generate(*w->set("observables"), 1000);
^
/usr/include/c++/9/bits/range_access.h:318:5: note: candidate found by name lookup is 'std::data'
data(initializer_list<_Tp> __il) noexcept
^
/usr/include/c++/9/bits/range_access.h:289:5: note: candidate found by name lookup is 'std::data'
data(_Container& __cont) noexcept(noexcept(__cont.data()))
^
/usr/include/c++/9/bits/range_access.h:299:5: note: candidate found by name lookup is 'std::data'
data(const _Container& __cont) noexcept(noexcept(__cont.data()))
^
/usr/include/c++/9/bits/range_access.h:309:5: note: candidate found by name lookup is 'std::data'
data(_Tp (&__array)[_Nm]) noexcept
^


Overlay plot with model with reference parameters as stored in snapshots

In [8]:
w->loadSnapshot("reference_fit");
model->plotOn(frame, LineColor(kRed));
model->plotOn(frame, LineColor(kRed), LineStyle(kDashed));

input_line_75:3:32: error: cannot take the address of an rvalue of type 'EColor'
model->plotOn(frame, LineColor(kRed));
^~~~
Error while creating dynamic expression for:
model->plotOn(frame, LineColor(kRed))
input_line_75:5:32: error: cannot take the address of an rvalue of type 'EColor'
model->plotOn(frame, LineColor(kRed), LineStyle(kDashed));
^~~~
Error while creating dynamic expression for:
model->plotOn(frame, LineColor(kRed), LineStyle(kDashed))


Draw the frame on the canvas

In [9]:
new TCanvas("rf510_wsnamedsets", "rf503_wsnamedsets", 600, 600);
frame->GetYaxis()->SetTitleOffset(1.4);
frame->Draw();

IncrementalExecutor::executeFunction: symbol '_ZN5cling7runtime8internal9EvaluateTIvEET_PNS1_15DynamicExprInfoEPN5clang11DeclContextE' unresolved while linking [cling interface function]!
You are probably missing the definition of void cling::runtime::internal::EvaluateT<void>(cling::runtime::internal::DynamicExprInfo*, clang::DeclContext*)
Maybe you need to load the corresponding shared library?


Print workspace contents

In [10]:
w->Print();

RooWorkspace(w) w contents

variables
---------
(a0,a1,bkgfrac,mean,sig1frac,sigma1,sigma2,x)

p.d.f.s
-------
RooChebychev::bkg[ x=x coefList=(a0,a1) ] = 0.8
RooAddPdf::model[ bkgfrac * bkg + [%] * sig ] = 0.9/1
RooAddPdf::sig[ sig1frac * sig1 + [%] * sig2 ] = 1/1
RooGaussian::sig1[ x=x mean=mean sigma=sigma1 ] = 1
RooGaussian::sig2[ x=x mean=mean sigma=sigma2 ] = 1

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)



Workspace will remain in memory after macro finishes

In [11]:
gDirectory->Add(w);


Draw all canvases

In [12]:
%jsroot on
gROOT->GetListOfCanvases()->Draw()