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The gen <=> reco mapping tests task #68

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Sep 7, 2021
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The gen <=> reco mapping tests task #68

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bf1a786
The gen to reco mapping tests task
victor-gonzalez Sep 7, 2021
e13e90a
Fix for allowing reconstructed track with label equal to 0
victor-gonzalez Sep 7, 2021
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160 changes: 154 additions & 6 deletions PWGCF/Tasks/dptdptcorrelations-simchl.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -1470,40 +1470,188 @@ struct TracksAndEventClassificationQAGen {
}
};

/// \brief Checks the correspondence generator level <=> detector level
struct CheckGeneratorLevelVsDetectorLevel {
OutputObj<TH1F> multirecDeltaEta{TH1F("mrDeltaEta", "#Delta#eta multirec tracks;#Delta#eta", 100, -2, 2)};
OutputObj<TH1F> multirecDeltaPhi{TH1F("mrDeltaPhi", "#Delta#varphi multirec tracks;#Delta#varphi", 100, 0, 2.0f * static_cast<float>(M_PI))};
OutputObj<TH1F> multirecDeltaPt{TH1F("mrDeltaPt", "#Delta#it{p}_{T} multirec tracks;#Delta#it{p}_{T}", 100, 0, 4)};
OutputObj<TH1F> multirecDistribution{TH1F("multirec", "Multiple reconstruction; ##/particle; counts", 11, -0.5f, 10.5f)};
OutputObj<TH1F> multirecDeltaEta_nc{TH1F("mrDeltaEta_nc", "#Delta#eta multirec tracks;#Delta#eta", 100, -2, 2)};
OutputObj<TH1F> multirecDeltaPhi_nc{TH1F("mrDeltaPhi_nc", "#Delta#varphi multirec tracks;#Delta#varphi", 100, 0, 2.0f * static_cast<float>(M_PI))};
OutputObj<TH1F> multirecDeltaPt_nc{TH1F("mrDeltaPt_nc", "#Delta#it{p}_{T} multirec tracks;#Delta#it{p}_{T}", 100, 0, 4)};
OutputObj<TH1F> multirecDistribution_nc{TH1F("multirec_nc", "Multiple reconstruction; ##/particle; counts", 11, -0.5f, 10.5f)};
TDatabasePDG* fPDG;

void init(InitContext const& context)
{
fPDG = TDatabasePDG::Instance();
}

void process(soa::Join<aod::Tracks, aod::McTrackLabels> const& tracks, aod::McParticles const& mcParticles)
{
constexpr float TWOPI = 2.0F * static_cast<float>(M_PI);

std::vector<std::vector<int64_t>> mclabelpos(mcParticles.size());
std::vector<std::vector<int64_t>> mclabelneg(mcParticles.size());
std::vector<std::vector<int64_t>> mclabelpos_negcoll(mcParticles.size());
std::vector<std::vector<int64_t>> mclabelneg_negcoll(mcParticles.size());

size_t nreco = tracks.size();
size_t ngen = 0;

for (auto& part : mcParticles) {
auto pdgpart = fPDG->GetParticle(part.pdgCode());
if (pdgpart != nullptr) {
float charge = (pdgpart->Charge() / 3 >= 1) ? 1.0 : ((pdgpart->Charge() / 3 <= -1) ? -1.0 : 0.0);
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if (charge != 0.0) {
ngen++;
}
}
}

// Let's go through the reco-gen mapping to detect multi-reconstructed particles
// For the time being we are only interested in the information based on the reconstructed tracks
LOGF(info, "New chunk with %d generated charged particles and %d reconstructed tracks", ngen, nreco);
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for (auto& track : tracks) {
int64_t recix = track.globalIndex();
int32_t label = track.mcParticleId();

// LOGF(info, "Track with global Id %d and collision Id %d has label %d associated to MC collision %d", recix, track.collisionId(), label, track.mcParticle().mcCollisionId());
if (track.collisionId() < 0) {
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if (label > 0) {
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mclabelpos_negcoll[label].push_back(recix);
} else if (label < 0) {
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mclabelneg_negcoll[-label].push_back(recix);
}
} else {
if (label > 0) {
mclabelpos[label].push_back(recix);
} else if (label < 0) {
mclabelneg[-label].push_back(recix);
}
}
}

/* let's provide information on a per chunk level */
int nrec_poslabel = 0;
int nrec_neglabel = 0;
int nrec_poslabel_nc = 0;
int nrec_neglabel_nc = 0;
int nrec_poslabel_crosscoll = 0;
for (int il = 0; il < mcParticles.size(); ++il) {
/* multireconstructed tracks only for positive labels */
int nrec = mclabelpos[il].size();
nrec_poslabel += mclabelpos[il].size();
nrec_neglabel += mclabelneg[il].size();

if (nrec > 1) {
multirecDistribution->Fill(nrec);
bool crosscollfound = false;
for (int i = 0; i < mclabelpos[il].size(); ++i) {
for (int j = i + 1; j < mclabelpos[il].size(); ++j) {
auto track1 = tracks.iteratorAt(mclabelpos[il][i]);
auto track2 = tracks.iteratorAt(mclabelpos[il][j]);

if (track1.collisionId() != track2.collisionId()) {
nrec_poslabel_crosscoll++;
crosscollfound = true;
break;
}
}
if (crosscollfound) {
break;
}
}

for (int i = 0; i < mclabelpos[il].size(); ++i) {
for (int j = i + 1; j < mclabelpos[il].size(); ++j) {
auto track1 = tracks.iteratorAt(mclabelpos[il][i]);
auto track2 = tracks.iteratorAt(mclabelpos[il][j]);

float deltaeta = track1.eta() - track2.eta();
float deltaphi = track1.phi() - track2.phi();
if (deltaphi < 0) {
deltaphi += TWOPI;
}
if (deltaphi > TWOPI) {
deltaphi -= TWOPI;
}
float deltapt = (track1.pt() > track2.pt()) ? track1.pt() - track2.pt() : track2.pt() - track1.pt();

multirecDeltaEta->Fill(deltaeta);
multirecDeltaPhi->Fill(deltaphi);
multirecDeltaPt->Fill(deltapt);
}
}
}

/* multireconstructed tracks only for positive labels */
int nrec_nc = mclabelpos_negcoll[il].size();
nrec_poslabel_nc += mclabelpos_negcoll[il].size();
nrec_neglabel_nc += mclabelneg_negcoll[il].size();

if (nrec_nc > 1) {
multirecDistribution_nc->Fill(nrec_nc);
for (int i = 0; i < mclabelpos_negcoll[il].size(); ++i) {
for (int j = i + 1; j < mclabelpos_negcoll[il].size(); ++j) {
auto track1 = tracks.iteratorAt(mclabelpos_negcoll[il][i]);
auto track2 = tracks.iteratorAt(mclabelpos_negcoll[il][j]);

float deltaeta = track1.eta() - track2.eta();
float deltaphi = track1.phi() - track2.phi();
if (deltaphi < 0) {
deltaphi += TWOPI;
}
if (deltaphi > TWOPI) {
deltaphi -= TWOPI;
}
float deltapt = (track1.pt() > track2.pt()) ? track1.pt() - track2.pt() : track2.pt() - track1.pt();

multirecDeltaEta_nc->Fill(deltaeta);
multirecDeltaPhi_nc->Fill(deltaphi);
multirecDeltaPt_nc->Fill(deltapt);
}
}
}
}
LOGF(info, "Reconstructed tracks with positive collision ID: %d with positive label, %d with negative label, %d with cross collision", nrec_poslabel, nrec_neglabel, nrec_poslabel_crosscoll);
LOGF(info, "Reconstructed tracks with negative collision ID: %d with positive label, %d with negative label", nrec_poslabel_nc, nrec_neglabel_nc);
}
};

WorkflowSpec defineDataProcessing(ConfigContext const& cfgc)
{
std::string multest = cfgc.options().get<std::string>("wfcentmultestimator");
bool ismc = cfgc.options().get<bool>("isMCPROD");
if (ismc) {
if (multest == "NOCM") {
/* no centrality/multiplicity classes available */
WorkflowSpec workflow{
adaptAnalysisTask<DptDptCorrelationsFilterAnalysisTask>(cfgc, SetDefaultProcesses{{{"processWithoutCent", true}, {"processWithoutCentMC", true}}}),
adaptAnalysisTask<TracksAndEventClassificationQARec>(cfgc),
adaptAnalysisTask<TracksAndEventClassificationQAGen>(cfgc),
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskRec"}, SetDefaultProcesses{{{"processRecLevel", true}}}),
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskGen"}, SetDefaultProcesses{{{"processGenLevel", true}}})};
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskGen"}, SetDefaultProcesses{{{"processGenLevel", true}}}),
adaptAnalysisTask<CheckGeneratorLevelVsDetectorLevel>(cfgc)};
return workflow;
} else {
/* centrality/multiplicity classes available */
WorkflowSpec workflow{
adaptAnalysisTask<DptDptCorrelationsFilterAnalysisTask>(cfgc, SetDefaultProcesses{{{"processWithCent", true}, {"processWithCentMC", true}}}),
adaptAnalysisTask<TracksAndEventClassificationQARec>(cfgc),
adaptAnalysisTask<TracksAndEventClassificationQAGen>(cfgc),
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskRec"}, SetDefaultProcesses{{{"processRecLevel", true}}}),
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskGen"}, SetDefaultProcesses{{{"processGenLevel", true}}})};
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskGen"}, SetDefaultProcesses{{{"processGenLevel", true}}}),
adaptAnalysisTask<CheckGeneratorLevelVsDetectorLevel>(cfgc)};
return workflow;
}
} else {
if (multest == "NOCM") {
/* no centrality/multiplicity classes available */
WorkflowSpec workflow{
adaptAnalysisTask<DptDptCorrelationsFilterAnalysisTask>(cfgc, SetDefaultProcesses{{{"processWithoutCent", true}}}),
adaptAnalysisTask<TracksAndEventClassificationQARec>(cfgc),
adaptAnalysisTask<DptDptCorrelationsTask>(cfgc, TaskName{"DptDptCorrelationsTaskRec"}, SetDefaultProcesses{{{"processRecLevel", true}}})};
return workflow;
} else {
/* centrality/multiplicity classes available */
WorkflowSpec workflow{
adaptAnalysisTask<DptDptCorrelationsFilterAnalysisTask>(cfgc, SetDefaultProcesses{{{"processWithCent", true}}}),
adaptAnalysisTask<TracksAndEventClassificationQARec>(cfgc),
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