doc/master/rf514__RooCustomizer_8C.html

#include "RooRealVar.h"

#include "RooGaussian.h"

#include "RooPolynomial.h"

#include "RooAddPdf.h"

#include "RooCustomizer.h"

#include "RooCategory.h"

#include "RooFormulaVar.h"

#include <iostream>


void rf514_RooCustomizer() {


  // Define a proto model that will be used as the template for each category

  // ---------------------------------------------------------------------------


  RooRealVar E("Energy","Energy",0,3000);


  RooRealVar meanG("meanG","meanG", 100., 0., 3000.);

  RooRealVar sigmaG("sigmaG","sigmaG", 3.);

  RooGaussian gauss("gauss", "gauss", E, meanG, sigmaG);


  RooRealVar pol1("pol1", "Constant of the polynomial", 1, -10, 10);

  RooPolynomial linear("linear", "linear", E, pol1);


  RooRealVar yieldSig("yieldSig", "yieldSig", 1, 0, 1.E4);

  RooRealVar yieldBkg("yieldBkg", "yieldBkg", 1, 0, 1.E4);


  RooAddPdf model("model", "S + B model",

      RooArgList(gauss,linear),

      RooArgList(yieldSig, yieldBkg));


  std::cout << "The proto model before customisation:" << std::endl;

  model.Print("T"); // "T" prints the model as a tree


  // Build the categories

  RooCategory sample("sample","sample");

  sample["Sample1"] = 1;

  sample["Sample2"] = 2;

  sample["Sample3"] = 3;


  // Start to customise the proto model that was defined above.

  // ---------------------------------------------------------------------------


  // We need two sets for bookkeeping of PDF nodes:

  RooArgSet newLeaves;           // This set collects leaves that are created in the process.

  RooArgSet allCustomiserNodes; // This set lists leaves that have been used in a replacement operation.


  // 1. Each sample should have its own mean for the gaussian

  // The customiser will make copies of `meanG` for each category.

  // These will all appear in the set `newLeaves`, which will own the new nodes.

  RooCustomizer cust(model, sample, newLeaves, &allCustomiserNodes);

  cust.splitArg(meanG, sample);


  // 2. Each sample should have its own signal yield, but there is an extra complication:

  // We need the yields 1 and 2 to be a function of the variable "mass".

  // For this, we pre-define nodes with exactly the names that the customiser would have created automatically,

  // that is, "<nodeName>_<categoryName>", and we register them in the set of customiser nodes.

  // The customiser will pick them up instead of creating new ones.

  // If we don't provide one (e.g. for "yieldSig_Sample3"), it will be created automatically by cloning `yieldSig`.

  RooRealVar mass("M", "M", 1, 0, 12000);

  RooFormulaVar yield1("yieldSig_Sample1", "Signal yield in the first sample", "M/3.360779", mass);

  RooFormulaVar yield2("yieldSig_Sample2", "Signal yield in the second sample", "M/2", mass);

  allCustomiserNodes.add(yield1);

  allCustomiserNodes.add(yield2);


  // Instruct the customiser to replace all yieldSig nodes for each sample:

  cust.splitArg(yieldSig, sample);


  // Now we can start building the PDFs for all categories:

  auto pdf1 = cust.build("Sample1");

  auto pdf2 = cust.build("Sample2");

  auto pdf3 = cust.build("Sample3");


  // And we inspect the two PDFs

  std::cout << "\nPDF 1 with a yield depending on M:" << std::endl;

  pdf1->Print("T");

  std::cout << "\nPDF 2 with a yield depending on M:" << std::endl;

  pdf2->Print("T");

  std::cout << "\nPDF 3 with a free yield:" << std::endl;

  pdf3->Print("T");


  std::cout << "\nThe following leaves have been created automatically while customising:" << std::endl;

  newLeaves.Print("V");


  // If we needed to set reasonable values for the means of the gaussians, this could be done as follows:

  auto& meanG1 = static_cast<RooRealVar&>(allCustomiserNodes["meanG_Sample1"]);

  meanG1.setVal(200);

  auto& meanG2 = static_cast<RooRealVar&>(allCustomiserNodes["meanG_Sample2"]);

  meanG2.setVal(300);


  std::cout << "\nThe following leaves have been used while customising"

    << "\n\t(partial overlap with the set of automatically created leaves."

    << "\n\ta new customiser for a different PDF could reuse them if necessary.):" << std::endl;

  allCustomiserNodes.Print("V");


}

RooAddPdf.h

RooCategory.h

RooCustomizer.h

RooFormulaVar.h

RooGaussian.h

RooPolynomial.h

RooRealVar.h

RooAbsCollection::add
virtual bool add(const RooAbsArg &var, bool silent=false)
Add the specified argument to list.
Definition RooAbsCollection.cxx:443

RooAbsCollection::Print
void Print(Option_t *options=nullptr) const override
This method must be overridden when a class wants to print itself.
Definition RooAbsCollection.h:315

RooAddPdf
Efficient implementation of a sum of PDFs of the form.
Definition RooAddPdf.h:33

RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition RooArgList.h:22

RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition RooArgSet.h:24

RooCategory
Object to represent discrete states.
Definition RooCategory.h:28

RooCustomizer
RooCustomizer is a factory class to produce clones of a prototype composite PDF object with the same ...
Definition RooCustomizer.h:36

RooFormulaVar
A RooFormulaVar is a generic implementation of a real-valued object, which takes a RooArgList of serv...
Definition RooFormulaVar.h:30

RooGaussian
Plain Gaussian p.d.f.
Definition RooGaussian.h:24

RooPolynomial
RooPolynomial implements a polynomial p.d.f of the form.
Definition RooPolynomial.h:25

RooRealVar
Variable that can be changed from the outside.
Definition RooRealVar.h:37

RooRealVar::setVal
void setVal(double value) override
Set value of variable to 'value'.
Definition RooRealVar.cxx:226

rf514_RooCustomizer
Definition rf514_RooCustomizer.py:1