## main102

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    // main102.cc is a part of the PYTHIA event generator.
    // Copyright (C) 2024 Torbjorn Sjostrand.
    // PYTHIA is licenced under the GNU GPL v2 or later, see COPYING for details.
    // Please respect the MCnet Guidelines, see GUIDELINES for details.

    // Authors:
    //            Christian Bierlich

    // Keywords:
    //            Hadronization
    //            Colour reconnection
    //            Rope hadronization

    // This program provides a demonstration of the flavour rope model supplied
    // in the Rope Hadronization framework. It produces four histograms
    // showing the ratio of respectively K^0_s, Lambda_0, Cascade and Omega^-
    // to pions as function of event multiplicity.
    // No kind of Levy-Tsallis fitting, triggering or similar
    // is done is this simple demonstration analysis. It should therefore not be
    // taken as anything but a proof of concept.

    #include "Pythia8/Pythia.h"
    using namespace Pythia8;

    int main() {
      // Generator. Process selection. LHC initialization.
      Pythia pythia;
      pythia.readString("Beams:eCM = 7000.");
      pythia.readString("SoftQCD:nonDiffractive = on");
      // Enabling flavour ropes, setting model parameters.
      // The model is still untuned. These parameter values
      // are choosen for illustrative purposes.
      pythia.readString("Ropewalk:RopeHadronization = on");
      pythia.readString("Ropewalk:doShoving = off");
      pythia.readString("Ropewalk:doFlavour = on");
      pythia.readString("Ropewalk:r0 = 0.5");
      pythia.readString("Ropewalk:m0 = 0.2");
      pythia.readString("Ropewalk:beta = 0.1");
      // Enabling setting of vertex information.
      pythia.readString("PartonVertex:setVertex = on");
      // Prevent unstable particles from decaying.
      pythia.readString("ParticleDecays:limitTau0 = on");
      pythia.readString("ParticleDecays:tau0Max = 10");
      pythia.init();

      // Histograms.
      Hist pion("pions (mult)", 50, 10., 135.);
      Hist kaon("kaons (mult)", 50, 10., 135.);
      Hist lambda("lambdas (mult)", 50, 10., 135.);
      Hist xi("xi (mult)", 50, 10., 135.);
      Hist omega("omega (mult)", 50, 10., 135.);

      // Note: High statistics is needed to fill the high multiplicity
      // end of the histograms, especially for Omega.
      const int nEvent = 4000;
      // Begin event loop. Generate event. Skip if error. List first one.
      for (int iEvent = 0; iEvent < nEvent; ++iEvent) {
        if (!pythia.next()) continue;
        // Counters for particle species.
        int nCharged = 0, nPions = 0, nKaons = 0;
        int nLambdas = 0, nXis = 0, nOmegas = 0;
        // Event short notation.
        Event& event = pythia.event;
        for (int i = 0; i < event.size(); ++i){
            Particle& p = event[i];
            // Apply simple, particle level, cuts.
            if(p.isFinal() && abs(p.eta()) < 2.5 && p.pT() > 0.1 ){
              if(p.isCharged()) ++nCharged;
              int absid = abs(p.id());
              if(absid == 211) ++nPions;
              else if(absid == 310) ++nKaons;
              else if(absid == 3122) ++nLambdas;
              else if(absid == 3312) ++nXis;
              else if(absid == 3334) ++nOmegas;
            }
         }
         // Discard events with event multiplicity less than 10.
         if(nCharged < 10) continue;
         // Fill histograms.
         pion.fill( double(nCharged), double(nPions) );
         kaon.fill( double(nCharged), double(nKaons) );
         lambda.fill( double(nCharged), double(nLambdas) );
         xi.fill( double(nCharged), double(nXis) );
         omega.fill( double(nCharged), double(nOmegas) );
      // End of event loop.
      }
      // Construct ratio histograms.
      Hist kp = kaon / pion;
      kp.title("kaon / pion (multiplicity)");
      Hist lp = lambda / pion;
      lp.title("lambda / pion (multiplicity)");
      Hist xp = xi / pion;
      xp.title("xi / pion (multiplicity)");
      Hist op = omega / pion;
      op.title("omega / pion (multiplicity)");
      // Statistics. Histograms. Done.
      pythia.stat();
      cout << kp << lp << xp << op;
      return 0;
    }