remove normalisation by area in seeding

PFCal-dev · Jul 27, 2021 · dda19c4 · dda19c4
1 parent 874e4c4
commit dda19c4
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Showing 4 changed files with 26 additions and 3 deletions.
diff --git a/L1Trigger/L1THGCal/interface/backend/HGCalHistoSeedingImpl.h b/L1Trigger/L1THGCal/interface/backend/HGCalHistoSeedingImpl.h
@@ -156,6 +156,9 @@ class HGCalHistoSeedingImpl {
   std::vector<double> neighbour_weights_;
   std::vector<double> smoothing_ecal_;
   std::vector<double> smoothing_hcal_;
+  bool seeds_norm_by_area_;
+
+  float area_10pct_;
 
   HGCalTriggerTools triggerTools_;
   Navigator navigator_;

diff --git a/L1Trigger/L1THGCal/python/customHistoSeeding.py b/L1Trigger/L1THGCal/python/customHistoSeeding.py
@@ -102,3 +102,9 @@ def custom_3dclustering_XYHistoMax(process,
     process.hgcalBackEndLayer2Producer.ProcessorParameters.C3d_parameters.histoMax_C3d_seeding_parameters = parameters_c3d
     return process
 
+def custom_3dclustering_seedNoArea(process,
+                                   seed_threshold=cms.double(20)):
+    parameters_c3d = histoMax_C3d_seeding_params.clone(seeds_norm_by_area = False,
+                                                        threshold_histo_multicluster = seed_threshold)
+    process.hgcalBackEndLayer2Producer.ProcessorParameters.C3d_parameters.histoMax_C3d_seeding_parameters = parameters_c3d
+    return process
diff --git a/L1Trigger/L1THGCal/python/hgcalBackEndLayer2Producer_cfi.py b/L1Trigger/L1THGCal/python/hgcalBackEndLayer2Producer_cfi.py
@@ -87,6 +87,7 @@
                                seeding_space=cms.string("RPhi"),# RPhi, XY
                                seed_smoothing_ecal=seed_smoothing_ecal,
                                seed_smoothing_hcal=seed_smoothing_hcal,
+                               seeds_norm_by_area=cms.bool(True)
                               )
 
 histoMax_C3d_clustering_params = cms.PSet(dR_multicluster=cms.double(0.03),

diff --git a/L1Trigger/L1THGCal/src/backend/HGCalHistoSeedingImpl.cc b/L1Trigger/L1THGCal/src/backend/HGCalHistoSeedingImpl.cc
@@ -13,6 +13,7 @@ HGCalHistoSeedingImpl::HGCalHistoSeedingImpl(const edm::ParameterSet& conf)
       neighbour_weights_(conf.getParameter<std::vector<double>>("neighbour_weights")),
       smoothing_ecal_(conf.getParameter<std::vector<double>>("seed_smoothing_ecal")),
       smoothing_hcal_(conf.getParameter<std::vector<double>>("seed_smoothing_hcal")),
+      seeds_norm_by_area_(conf.getParameter<bool>("seeds_norm_by_area")),
       kROverZMin_(conf.getParameter<double>("kROverZMin")),
       kROverZMax_(conf.getParameter<double>("kROverZMax")) {
   if (seedingAlgoType_ == "HistoMaxC3d") {
@@ -64,6 +65,13 @@ HGCalHistoSeedingImpl::HGCalHistoSeedingImpl(const edm::ParameterSet& conf)
         << "Inconsistent size of neighbour weights vector in HGCalMulticlustering ( " << neighbour_weights_.size()
         << " ). Should be " << neighbour_weights_size_ << "\n";
   }
+
+  // compute quantities for non-normalised-by-area histoMax
+  // The 0.1 factor in bin1_10pct is an attempt to keep the same rough scale for seeds. The exact value is arbitrary.
+  int bin1_10pct = (int)0.1 * nBins1_;
+  float R1_10pct = kROverZMin_ + bin1_10pct * (kROverZMax_ - kROverZMin_) / nBins1_;
+  float R2_10pct = R1_10pct + ((kROverZMax_ - kROverZMin_) / nBins1_);
+  area_10pct_ = ((M_PI * (pow(R2_10pct, 2) - pow(R1_10pct, 2))) / nBins2_);
 }
 
 HGCalHistoSeedingImpl::Histogram HGCalHistoSeedingImpl::fillHistoClusters(
@@ -166,16 +174,21 @@ HGCalHistoSeedingImpl::Histogram HGCalHistoSeedingImpl::fillSmoothPhiHistoCluste
   for (int z_side : {-1, 1}) {
     for (unsigned bin1 = 0; bin1 < nBins1_; bin1++) {
       int nBinsSide = (binSums[bin1] - 1) / 2;
-      float R1 = kROverZMin_ + bin1 * (kROverZMax_ - kROverZMin_) / nBins1_;
-      float R2 = R1 + ((kROverZMax_ - kROverZMin_) / nBins1_);
       double area =
-          ((M_PI * (pow(R2, 2) - pow(R1, 2))) / nBins2_) *
           (1 +
            2.0 *
                (1 -
                 pow(0.5,
                     nBinsSide)));  // Takes into account different area of bins in different R-rings + sum of quadratic weights used
 
+      if (seeds_norm_by_area_) {
+        float R1 = kROverZMin_ + bin1 * (kROverZMax_ - kROverZMin_) / nBins1_;
+        float R2 = R1 + ((kROverZMax_ - kROverZMin_) / nBins1_);
+        area = area * ((M_PI * (pow(R2, 2) - pow(R1, 2))) / nBins2_);
+      } else {
+        area = area * area_10pct_;
+      }
+
       for (unsigned bin2 = 0; bin2 < nBins2_; bin2++) {
         const auto& bin_orig = histoClusters.at(z_side, bin1, bin2);
         float content = bin_orig.values[Bin::Content::Sum];