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Reference Guide
df002_dataModel.C File Reference

Detailed Description

View in nbviewer Open in SWAN This tutorial shows the possibility to use data models which are more complex than flat ntuples with RDataFrame

using FourVector = ROOT::Math::XYZTVector;
using FourVectorVec = std::vector<FourVector>;
using FourVectorRVec = ROOT::VecOps::RVec<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 *filename, const char *treeName)
{
const double M = 0.13957; // set pi+ mass
TRandom3 R(1);
auto genTracks = [&](){
FourVectorVec tracks;
const auto nPart = R.Poisson(15);
tracks.reserve(nPart);
for (int j = 0; j < nPart; ++j) {
const auto px = R.Gaus(0, 10);
const auto py = R.Gaus(0, 10);
const auto pt = sqrt(px * px + py * py);
const auto eta = R.Uniform(-3, 3);
const auto phi = R.Uniform(0.0, 2 * TMath::Pi());
CylFourVector vcyl(pt, eta, phi);
// set energy
auto E = sqrt(vcyl.R() * vcyl.R() + M * M);
// fill track vector
tracks.emplace_back(vcyl.X(), vcyl.Y(), vcyl.Z(), E);
}
return tracks;
};
d.Define("tracks", genTracks).Snapshot<FourVectorVec>(treeName, filename, {"tracks"});
}
{
// We prepare an input tree to run on
auto fileName = "df002_dataModel.root";
auto treeName = "myTree";
fill_tree(fileName, treeName);
// We read the tree from the file and create a RDataFrame, a class that
// allows us to interact with the data contained in the tree.
ROOT::RDataFrame d(treeName, fileName, {"tracks"});
// ## Operating on branches which are collection of objects
// Here we deal with the simplest of the cuts: we decide to accept the event
// only if the number of tracks is greater than 5.
auto n_cut = [](const FourVectorRVec &tracks) { return tracks.size() > 8; };
auto nentries = d.Filter(n_cut, {"tracks"}).Count();
std::cout << *nentries << " passed all filters" << std::endl;
// Another possibility consists in creating a new column containing the
// quantity we are interested in.
// In this example, we will cut on the number of tracks and plot their
// transverse momentum.
auto getPt = [](const FourVectorRVec &tracks) {
return ROOT::VecOps::Map(tracks, [](const FourVector& v){return v.Pt();});
};
// We do the same for the weights.
auto getPtWeights = [](const FourVectorRVec &tracks) {
return ROOT::VecOps::Map(tracks, [](const FourVector& v){ return 1. / v.Pt();});
};
auto augmented_d = d.Define("tracks_n", [](const FourVectorRVec &tracks) { return (int)tracks.size(); })
.Filter([](int tracks_n) { return tracks_n > 2; }, {"tracks_n"})
.Define("tracks_pts", getPt)
.Define("tracks_pts_weights", getPtWeights);
auto trN = augmented_d.Histo1D({"", "", 40, -.5, 39.5}, "tracks_n");
auto trPts = augmented_d.Histo1D("tracks_pts");
auto trWPts = augmented_d.Histo1D("tracks_pts", "tracks_pts_weights");
auto c1 = new TCanvas();
trN->DrawCopy();
auto c2 = new TCanvas();
trPts->DrawCopy();
auto c3 = new TCanvas();
trWPts->DrawCopy();
return 0;
}
pict1_df002_dataModel.C.png
pict2_df002_dataModel.C.png
pict3_df002_dataModel.C.png
Date
December 2016
Author
Danilo Piparo

Definition in file df002_dataModel.C.