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Adapt FastJet plugin to LayerTiles type traits
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// Author: Marco Rovere - [email protected] | ||
// Date: 04/2021 | ||
// Date: 10/2021 | ||
#include <algorithm> | ||
#include <set> | ||
#include <vector> | ||
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@@ -99,12 +99,12 @@ void PatternRecognitionbyFastJet<TILES>::makeTracksters( | |
const CaloGeometry &geom = es.getData(caloGeomToken_); | ||
rhtools_.setGeometry(geom); | ||
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int type = input.tiles[0].typeT(); | ||
int nEtaBin = (type == 1) ? ticl::TileConstantsHFNose::nEtaBins : ticl::TileConstants::nEtaBins; | ||
int nPhiBin = (type == 1) ? ticl::TileConstantsHFNose::nPhiBins : ticl::TileConstants::nPhiBins; | ||
constexpr auto isHFnose = std::is_same<TILES, TICLLayerTilesHFNose>::value; | ||
constexpr int nEtaBin = TILES::constants_type_t::nEtaBins; | ||
constexpr int nPhiBin = TILES::constants_type_t::nPhiBins; | ||
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// We need to partition the two sides of the HGCAL detector | ||
auto lastLayerPerSide = static_cast<unsigned int>(rhtools_.lastLayer(false)) - 1; | ||
auto lastLayerPerSide = static_cast<unsigned int>(rhtools_.lastLayer(isHFnose)) - 1; | ||
unsigned int maxLayer = 2 * lastLayerPerSide - 1; | ||
std::vector<fastjet::PseudoJet> fjInputs; | ||
fjInputs.clear(); | ||
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@@ -150,7 +150,7 @@ void PatternRecognitionbyFastJet<TILES>::makeTracksters( | |
ticl::assignPCAtoTracksters(result, | ||
input.layerClusters, | ||
input.layerClustersTime, | ||
rhtools_.getPositionLayer(rhtools_.lastLayerEE(false), false).z()); | ||
rhtools_.getPositionLayer(rhtools_.lastLayerEE(isHFnose), isHFnose).z()); | ||
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// run energy regression and ID | ||
energyRegressionAndID(input.layerClusters, result); | ||
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// Author: Marco Rovere - [email protected] | ||
// Date: 04/2021 | ||
// Date: 10/2021 | ||
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#ifndef __RecoHGCal_TICL_PRbyFASTJET_H__ | ||
#define __RecoHGCal_TICL_PRbyFASTJET_H__ | ||
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