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| // -*- C++ -*-
#include "Rivet/Analysis.hh"
#include "Rivet/AnalysisHandler.hh"
namespace Rivet {
/// Analysis of the generated event-weight distributions
class MC_WEIGHTS : public Analysis {
public:
RIVET_DEFAULT_ANALYSIS_CTOR(MC_WEIGHTS);
/// @name Analysis methods
/// @{
/// Book histograms and initialise projections before the run
void init() {
/// @todo Convert to Scatter1D or Counter
book(_h_weight_100, "weight_100", 200, -100.0, 100.0);
book(_h_weight_10, "weight_10", 200, -10.0, 10.0);
book(_h_logweight_pos, "logweight_pos", logspace(100, 0.1, 10000.0));
book(_h_logweight_neg, "logweight_neg", logspace(100, 0.1, 10000.0));
book(_h_xsfraction_neg, "xsfraction_neg");
}
/// Perform the per-event analysis
void analyze(const Event& event) {
const size_t numWeights = event.weights().size();
for (size_t m = 0; m < numWeights; ++m) {
const double weight = event.weights()[m];
_h_weight_100.get()->_getPersistent(m)->fill(weight, 1.0);
_h_weight_10.get()->_getPersistent(m)->fill(weight, 1.0);
if (weight < 0.) {
_h_logweight_neg.get()->_getPersistent(m)->fill(fabs(weight), 1.0);
} else {
_h_logweight_pos.get()->_getPersistent(m)->fill(weight, 1.0);
}
}
}
/// Normalise histograms etc., after the run
void finalize() {
const double sf = 1.0 / numEvents();
scale(_h_weight_100, sf);
scale(_h_weight_10, sf);
scale(_h_logweight_pos, sf);
scale(_h_logweight_neg, sf);
const double totalSumW = _h_logweight_neg->sumW() + _h_logweight_pos->sumW();
const double totalSumW2 = _h_logweight_neg->sumW2() + _h_logweight_pos->sumW2();
const double negFrac = _h_logweight_neg->sumW() / totalSumW;
const double negFracErr = negFrac * totalSumW / sqrt(totalSumW2);
_h_xsfraction_neg->addPoint(0, negFrac, 0.5, negFracErr);
}
/// @}
/// @name Histograms
/// @{
Scatter2DPtr _h_xsfraction_neg;
Histo1DPtr _h_weight_100, _h_weight_10, _h_logweight_pos, _h_logweight_neg;
/// @}
};
RIVET_DECLARE_PLUGIN(MC_WEIGHTS);
}
|