Rivet analyses
MC analysis for process total cross section
Experiment: ()
Status: VALIDATED
Authors: - Marek Schoenherr - Christian Gutschow
References: none listed
Beams: * *
Beam energies: ANY
Run details: - Suitable for any process.
Analysis for bookkeeping of the total cross section, number of generated events and the ratio of events with positive and negative weights. This analysis will not produce sensible distributions in case of correlated NLO sub-events.
Source
code:MC_XS.cc
// -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/AnalysisHandler.hh"
namespace Rivet {
/// Analysis of the generated cross-section
class MC_XS : public Analysis {
public:
RIVET_DEFAULT_ANALYSIS_CTOR(MC_XS);
/// @name Analysis methods
/// @{
/// Book histograms and initialise projections before the run
void init() {
/// @todo Convert to Scatter1D or Counter
book(_h_XS, "XS");
book(_h_N, "N", 1, 0.0, 1.0);
book(_h_pmXS, "pmXS", 2, -1.0, 1.0);
book(_h_pmN, "pmN", 2, -1.0, 1.0);
}
/// Perform the per-event analysis
void analyze(const Event& event) {
const size_t numWeights = event.weights().size();
const vector<pair<double,double>> xsecs = event.crossSections();
for (size_t m = 0; m < numWeights; ++m) {
size_t idx = (xsecs.size() == numWeights)? m : 0;
const double xs = xsecs[idx].first;
const double xserr = xsecs[idx].second;
_h_XS.get()->persistent(m)->set(xs, xserr);
const double weight = event.weights()[m];
_h_pmXS.get()->persistent(m)->fill(0.5*(weight > 0 ? 1. : -1), abs(weight));
_h_pmN.get()->persistent(m)->fill(0.5*(weight > 0 ? 1. : -1), 1.);
_h_N.get()->persistent(m)->fill(0.5, 1.0);
}
}
/// Normalise histograms etc., after the run
void finalize() {
scale(_h_pmXS, crossSection()/picobarn/sumOfWeights());
}
/// @}
/// @name Histograms
/// @{
Estimate0DPtr _h_XS;
Histo1DPtr _h_pmXS, _h_pmN, _h_N;
/// @}
};
RIVET_DECLARE_PLUGIN(MC_XS);
}