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Reference Guide
df002_dataModel.C File Reference

Detailed Description

View in nbviewer Open in SWAN Show how to work with non-flat data models, e.g.

vectors of tracks.

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);
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();
auto c2 = new TCanvas();
auto c3 = new TCanvas();
return 0;
December 2016
Danilo Piparo (CERN)

Definition in file df002_dataModel.C.

auto Map(Args &&... args) -> decltype(ROOT::Detail::VecOps::MapFromTuple(std::forward_as_tuple(args...), std::make_index_sequence< sizeof...(args) - 1 >()))
Create new collection applying a callable to the elements of the input collection.
Definition: RVec.hxx:915
return c3
Definition: legend3.C:15
DisplacementVector3D< CylindricalEta3D< double >, DefaultCoordinateSystemTag > RhoEtaPhiVector
3D Vector based on the eta based cylindrical coordinates rho, eta, phi in double precision.
Definition: Vector3Dfwd.h:62
Definition: df002_dataModel.py:1
int nentries
Definition: THbookFile.cxx:91
ROOT's RDataFrame offers a high level interface for analyses of data stored in TTree,...
Definition: RDataFrame.hxx:42
@ v
Definition: rootcling_impl.cxx:3664
#define R(a, b, c, d, e, f, g, h, i)
Definition: RSha256.hxx:110
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
constexpr Double_t Pi()
Definition: TMath.h:37
Random number generator class based on M.
Definition: TRandom3.h:27
double sqrt(double)
RVec< T > Filter(const RVec< T > &v, F &&f)
Create a new collection with the elements passing the filter expressed by the predicate.
Definition: RVec.hxx:944
void tracks()
Definition: tracks.C:49
The Canvas class.
Definition: TCanvas.h:23
#define d(i)
Definition: RSha256.hxx:102
return c2
Definition: legend2.C:14
TPaveText * pt
Definition: entrylist_figure1.C:7
constexpr Double_t E()
Base of natural log:
Definition: TMath.h:96
A "std::vector"-like collection of values implementing handy operation to analyse them.
Definition: RVec.hxx:283
return c1
Definition: legend1.C:41