doc/v620/df004__cutFlowReport_8C.html

using FourVector = ROOT::Math::XYZTVector;

using FourVectors = std::vector<FourVector>;

using CylFourVector = ROOT::Math::RhoEtaPhiVector;


// A simple helper function to fill a test tree: this makes the example

// stand-alone.

void fill_tree(const char *treeName, const char *fileName)

{

   ROOT::RDataFrame d(50);

   int i(0);

   d.Define("b1", [&i]() { return (double)i; })

      .Define("b2",

              [&i]() {

                 auto j = i * i;

                 ++i;

                 return j;

              })

      .Snapshot(treeName, fileName);

}


void df004_cutFlowReport()

{


   // We prepare an input tree to run on

   auto fileName = "df004_cutFlowReport.root";

   auto treeName = "myTree";

   fill_tree(treeName, fileName);


   // We read the tree from the file and create a RDataFrame

   ROOT::RDataFrame d(treeName, fileName, {"b1", "b2"});


   // ## Define cuts and create the report

   // Here we define two simple cuts

   auto cut1 = [](double b1) { return b1 > 25.; };

   auto cut2 = [](int b2) { return 0 == b2 % 2; };


   // An optional string parameter name can be passed to the Filter method to create a named filter.

   // Named filters work as usual, but also keep track of how many entries they accept and reject.

   auto filtered1 = d.Filter(cut1, {"b1"}, "Cut1");

   auto filtered2 = d.Filter(cut2, {"b2"}, "Cut2");


   auto augmented1 = filtered2.Define("b3", [](double b1, int b2) { return b1 / b2; });

   auto cut3 = [](double x) { return x < .5; };

   auto filtered3 = augmented1.Filter(cut3, {"b3"}, "Cut3");


   // Statistics are retrieved through a call to the Report method:

   // when Report is called on the main RDataFrame object, it retrieves stats

   // for all named filters declared up to that point.

   // When called on a stored chain state (i.e. a chain/graph node), it

   // retrieves stats for all named filters in the section of the chain between

   // the main RDataFrame and that node (included).

   // Stats are printed in the same order as named filters have been added to

   // the graph, and refer to the latest event-loop that has been run using the

   // relevant RDataFrame.

   std::cout << "Cut3 stats:" << std::endl;

   filtered3.Report()->Print();


   // It is not only possible to print the information about cuts, but also to

   // retrieve it to then use it programmatically.

   std::cout << "All stats:" << std::endl;

   auto allCutsReport = d.Report();

   allCutsReport->Print();


   // We can now loop on the cuts

   std::cout << "Name\tAll\tPass\tEfficiency" << std::endl;

   for (auto &&cutInfo : allCutsReport) {

      std::cout << cutInfo.GetName() << "\t" << cutInfo.GetAll() << "\t" << cutInfo.GetPass() << "\t"

                << cutInfo.GetEff() << " %" << std::endl;

   }


   // Or get information about them individually

   auto cutName = "Cut1";

   auto cut = allCutsReport->At("Cut1");

   std::cout << cutName << " efficiency is " << cut.GetEff() << " %" << std::endl;

}

d
#define d(i)
Definition: RSha256.hxx:102

ROOT::RDataFrame
ROOT's RDataFrame offers a high level interface for analyses of data stored in TTrees,...
Definition: RDataFrame.hxx:42

x
Double_t x[n]
Definition: legend1.C:17

ROOT::Math::RhoEtaPhiVector
DisplacementVector3D< CylindricalEta3D< double >, DefaultCoordinateSystemTag > RhoEtaPhiVector
3D Vector based on the eta based cylindrical coordinates rho, eta, phi in double precision.
Definition: Vector3Dfwd.h:50

ROOT::Math::XYZTVector
LorentzVector< PxPyPzE4D< double > > XYZTVector
LorentzVector based on x,y,x,t (or px,py,pz,E) coordinates in double precision with metric (-,...
Definition: Vector4Dfwd.h:33

df004_cutFlowReport
Definition: df004_cutFlowReport.py:1