phitutorial_step2.cxx

// Copyright 2019-2025 CERN and copyright holders of ALICE O2.
// See https://alice-o2.web.cern.ch/copyright for details of the copyright holders.
// All rights not expressly granted are reserved.
//
// This software is distributed under the terms of the GNU General Public
// License v3 (GPL Version 3), copied verbatim in the file "COPYING".
//
// In applying this license CERN does not waive the privileges and immunities
// granted to it by virtue of its status as an Intergovernmental Organization
// or submit itself to any jurisdiction.
/// \file phitutorial.cxx
/// \brief Phi meson analysis tutorial
/// \author Adrian Fereydon Nassirpour <adrian.fereydon.nassirpour@cern.ch>

// IMPORTANT INCLUDES
#include "Common/DataModel/Centrality.h"
#include "Common/DataModel/EventSelection.h"
#include "Common/DataModel/Multiplicity.h"
#include "Common/DataModel/PIDResponse.h"
#include "Common/DataModel/TrackSelectionTables.h"

#include "Framework/ASoA.h"
#include "Framework/AnalysisDataModel.h"
#include "Framework/AnalysisTask.h"
#include "ReconstructionDataFormats/Track.h"
#include <Framework/ASoAHelpers.h>
#include <Framework/runDataProcessing.h>

// ROOT Includes (optional)
#include <TLorentzVector.h>

// C++ includes
#include <string>
#include <vector>

using namespace o2;
using namespace o2::framework;
using namespace o2::framework::expressions;

// MAIN STRUCT
struct phitutorial_step2 {

  //*************************************//
  // SLICECACHE AND REGISTRY DEFS
  //*************************************//
  SliceCache cache;
  HistogramRegistry histos{"histos", {}, OutputObjHandlingPolicy::AnalysisObject};

  //*************************************//
  // INIT FUNCTION AND HISTOGRAM BOOKING
  //*************************************//
  void init(o2::framework::InitContext&)
  {
    const AxisSpec ptAxis = {200, 0, 20.0};
    const AxisSpec MinvAxis = {200, 0.85, 1.25};

    histos.add("Nch_pT", "Nch_pT", kTH1F, {ptAxis});
    histos.add("Nch_USS_Minv", "Nch_USS_Minv", kTH1F, {MinvAxis});

  }; // end of init

  //*************************************//
  // TIME TO BUILD TRACK AND EVENT CANDIDATES
  //*************************************//
  using EventCandidates = soa::Join<aod::Collisions, aod::EvSels, aod::FT0Mults, aod::CentFT0Ms>;
  using TrackCandidates = soa::Join<aod::Tracks, aod::TracksExtra, aod::TracksDCA, aod::TrackSelection, aod::pidTPCFullKa, aod::pidTOFFullKa>;
  double massKa = o2::constants::physics::MassKPlus;

  //***************************************//
  // PREAMBLE COMPLETE, NOW WE DO HELPER FCNS
  //**************************************//
  template <typename EventType>
  bool eventSelection(const EventType event)
  {
    if (!event.sel8()) // This is required to extract good events
      return false;

    return true;
  };
  //********************************************//
  template <typename TracksType>
  bool trackSelection(const TracksType track)
  {
    if (!track.isGlobalTrack())
      return false;
    if (track.pt() < 0.15)
      return false;
    if (std::abs(track.eta()) > 1.0)
      return false;

    return true;
  };
  // Space for more helper functions!
  //********************************************//

  //********************************************//
  // HELPER FCNS COMPLETE, NOW WE DO PROCESS FCNS
  //********************************************//

  // SAME EVENT
  int nEvents = 0;
  void processDataSameEvent(EventCandidates::iterator const& collision, TrackCandidates const& tracks)
  {
    nEvents++;
    if ((nEvents + 1) % 10000 == 0) {
      std::cout << "Processed Data Events: " << nEvents << std::endl;
    }

    if (!eventSelection(collision))
      return;

    // Now, we want to add some PID to ensure that we are with a higher likelhood pairing Kaons.
    // Three ways to do this:
    // 1.) Directly cut on the tracks in the looping functions (not recommended)

    // 2.) Create a helper function above similar to trackSelection

    // 3.) Partition your tracks with a preselection by adding this outside of your process function:
    // Partition<TrackCandidates> kaon (nabs(aod::pidtpc::tpcNSigmaKa) <= X); // X is a cfg value or a hardcoded integer.
    // Then inside the function: auto tracks1 = kaon->sliceByCached(aod::track::collisionId, collision1.globalIndex(), cache); Do the same for tracks2.

    // Getters for PID:
    //  tracks.tpcNSigmaKa()
    //  tracks.tofNSigmaKa()
    //  Good starting value for the selected nsigma value is "3".
    //  You might not want to have a STRICT TOF cut, a lot of tracks with good TPC PID does not have TOF information. You can make a conditional cut on TOF by only implementing the TOF cut if track.hasTOF() returns TRUE.

    for (const auto& track : tracks) {
      if (!trackSelection(track)) {
        continue;
      }
      histos.fill(HIST("Nch_pT"), track.pt());
    }

    for (const auto& [trk1, trk2] : combinations(o2::soa::CombinationsStrictlyUpperIndexPolicy(tracks, tracks))) {
      if (!trackSelection(trk1) || !trackSelection(trk2)) {
        continue;
      }
      ROOT::Math::PxPyPzMVector lDecayDaughter1, lDecayDaughter2, lResonance;
      lDecayDaughter1 = ROOT::Math::PxPyPzMVector(trk1.px(), trk1.py(), trk1.pz(), massKa);
      lDecayDaughter2 = ROOT::Math::PxPyPzMVector(trk2.px(), trk2.py(), trk2.pz(), massKa);

      lResonance = lDecayDaughter1 + lDecayDaughter2;
      double conjugate = trk1.sign() * trk2.sign();
      if (conjugate < 0) {
        histos.fill(HIST("Nch_USS_Minv"), lResonance.M());
      }
    } // Invariant mass combinations

  } // proccessSameEvent
  PROCESS_SWITCH(phitutorial_step2, processDataSameEvent, "process Data Same Event", false);

  //***************************************//
  // TASK COMPLETE!
  //**************************************//
};
WorkflowSpec defineDataProcessing(ConfigContext const& cfgc)
{
  return WorkflowSpec{adaptAnalysisTask<phitutorial_step2>(cfgc)};
};