[35cdc46] | 1 | //FJSTARTHEADER
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[b7b836a] | 2 | // $Id: JadePlugin.cc 4354 2018-04-22 07:12:37Z salam $
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[d7d2da3] | 3 | //
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[b7b836a] | 4 | // Copyright (c) 2007-2018, Matteo Cacciari, Gavin P. Salam and Gregory Soyez
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[d7d2da3] | 5 | //
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| 6 | //----------------------------------------------------------------------
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| 7 | // This file is part of FastJet.
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| 8 | //
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| 9 | // FastJet is free software; you can redistribute it and/or modify
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| 10 | // it under the terms of the GNU General Public License as published by
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| 11 | // the Free Software Foundation; either version 2 of the License, or
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| 12 | // (at your option) any later version.
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| 13 | //
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| 14 | // The algorithms that underlie FastJet have required considerable
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[35cdc46] | 15 | // development. They are described in the original FastJet paper,
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| 16 | // hep-ph/0512210 and in the manual, arXiv:1111.6097. If you use
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[d7d2da3] | 17 | // FastJet as part of work towards a scientific publication, please
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[35cdc46] | 18 | // quote the version you use and include a citation to the manual and
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| 19 | // optionally also to hep-ph/0512210.
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[d7d2da3] | 20 | //
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| 21 | // FastJet is distributed in the hope that it will be useful,
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| 22 | // but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 23 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 24 | // GNU General Public License for more details.
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| 25 | //
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| 26 | // You should have received a copy of the GNU General Public License
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| 27 | // along with FastJet. If not, see <http://www.gnu.org/licenses/>.
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| 28 | //----------------------------------------------------------------------
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[35cdc46] | 29 | //FJENDHEADER
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[d7d2da3] | 30 |
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| 31 | // fastjet stuff
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| 32 | #include "fastjet/ClusterSequence.hh"
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| 33 | #include "fastjet/JadePlugin.hh"
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| 34 | #include <iostream>
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| 35 | //#include "fastjet/internal/ClusterSequence_N2.icc"
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| 36 | #include "fastjet/NNH.hh"
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[1d208a2] | 37 | #include "fastjet/NNFJN2Plain.hh"
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[d7d2da3] | 38 |
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| 39 | // other stuff
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| 40 | #include <vector>
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| 41 | #include <sstream>
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| 42 | #include <limits>
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| 43 |
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| 44 |
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| 45 |
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| 46 |
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| 47 | using namespace std;
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| 48 |
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| 49 | FASTJET_BEGIN_NAMESPACE // defined in fastjet/internal/base.hh
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| 50 |
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| 51 |
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| 52 | //----------------------------------------------------------------------
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| 53 | /// class to help run a JADE algorithm
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[1d208a2] | 54 | ///
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| 55 | /// This class works both with NNH and NNFJN2Plain clustering
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| 56 | /// helpers. They both use the same init(...) call, but for the
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| 57 | /// clustering:
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| 58 | ///
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| 59 | /// - NNH uses distance(...) and beam_distance()
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| 60 | /// - NNFJPlainN2 uses geometrical_distance(...), momentum_factor()
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| 61 | /// and geometrical_beam_distance()
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| 62 | ///
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| 63 | /// For NNFJPlainN2 the 2 E_i E_j (1-cos theta_{ij}) factor
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| 64 | /// gets broken up into
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| 65 | ///
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| 66 | /// sqrt(2)*min(E_i,E_j) * [sqrt(2)*max(E_i,E_j) (1 - cos \theta_{ij})]
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| 67 | ///
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| 68 | /// The second factor is what we call the "geometrical_distance" even
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| 69 | /// though it isn't actually purely geometrical. But the fact that it
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| 70 | /// gets multiplied by min(E_i,E_j) to get the full distance is
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| 71 | /// sufficient for the validity of the FJ lemma, allowing for the use
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| 72 | /// of NNFJN2Plain.
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[d7d2da3] | 73 | class JadeBriefJet {
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| 74 | public:
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| 75 | void init(const PseudoJet & jet) {
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| 76 | double norm = 1.0/sqrt(jet.modp2());
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| 77 | nx = jet.px() * norm;
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| 78 | ny = jet.py() * norm;
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| 79 | nz = jet.pz() * norm;
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| 80 | rt2E = sqrt(2.0)*jet.E();
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| 81 | }
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| 82 |
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| 83 | double distance(const JadeBriefJet * jet) const {
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| 84 | double dij = 1 - nx*jet->nx
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| 85 | - ny*jet->ny
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| 86 | - nz*jet->nz;
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| 87 | dij *= rt2E*jet->rt2E;
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| 88 | return dij;
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| 89 | }
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| 90 |
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[1d208a2] | 91 | double geometrical_distance(const JadeBriefJet * jet) const {
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| 92 | double dij = 1 - nx*jet->nx
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| 93 | - ny*jet->ny
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| 94 | - nz*jet->nz;
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| 95 | dij *= max(rt2E,jet->rt2E);
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| 96 | return dij;
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| 97 | }
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| 98 |
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| 99 | double momentum_factor() const {
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| 100 | return rt2E;
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| 101 | }
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| 102 |
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[d7d2da3] | 103 | double beam_distance() const {
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| 104 | return numeric_limits<double>::max();
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| 105 | }
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| 106 |
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[1d208a2] | 107 | double geometrical_beam_distance() const {
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| 108 | // get a number that is almost the same as max(), just a little
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| 109 | // smaller so as to ensure that when we divide it by rt2E and then
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| 110 | // multiply it again, we won't get an overflow
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| 111 | const double almost_max = numeric_limits<double>::max() * (1 - 1e-13);
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| 112 | return almost_max / rt2E;
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| 113 | }
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| 114 |
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[d7d2da3] | 115 | private:
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| 116 | double rt2E, nx, ny, nz;
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| 117 | };
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| 118 |
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| 119 |
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| 120 | //----------------------------------------------------------------------
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| 121 | string JadePlugin::description () const {
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| 122 | ostringstream desc;
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| 123 | desc << "e+e- JADE algorithm plugin";
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[1d208a2] | 124 | switch(_strategy) {
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| 125 | case strategy_NNH:
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| 126 | desc << ", using NNH strategy"; break;
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| 127 | case strategy_NNFJN2Plain:
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| 128 | desc << ", using NNFJN2Plain strategy"; break;
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| 129 | default:
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| 130 | throw Error("Unrecognized strategy in JadePlugin");
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| 131 | }
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| 132 |
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[d7d2da3] | 133 | return desc.str();
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| 134 | }
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| 135 |
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[1d208a2] | 136 | // //----------------------------------------------------------------------
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| 137 | // void JadePlugin::run_clustering(ClusterSequence & cs) const {
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| 138 | // int njets = cs.jets().size();
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| 139 | //
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| 140 | // //SharedPtr<NNBase<> > nn;
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| 141 | // NNBase<> * nn;
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| 142 | // switch(_strategy) {
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| 143 | // case strategy_NNH:
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| 144 | // //nn.reset(new NNH<JadeBriefJet>(cs.jets()));
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| 145 | // nn = new NNH<JadeBriefJet>(cs.jets());
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| 146 | // break;
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| 147 | // case strategy_NNFJN2Plain:
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| 148 | // //nn.reset(new NNFJN2Plain<JadeBriefJet>(cs.jets()));
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| 149 | // nn = new NNFJN2Plain<JadeBriefJet>(cs.jets());
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| 150 | // break;
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| 151 | // default:
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| 152 | // throw Error("Unrecognized strategy in JadePlugin");
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| 153 | // }
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| 154 | // //NNH<JadeBriefJet> nnh(cs.jets());
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| 155 | // //NNFJN2Plain<JadeBriefJet> nnh(cs.jets());
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| 156 | //
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| 157 | // // if testing against Hoeth's implementation, need to rescale the
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| 158 | // // dij by Q^2.
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| 159 | // //double Q2 = cs.Q2();
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| 160 | //
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| 161 | // while (njets > 0) {
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| 162 | // int i, j, k;
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| 163 | // double dij = nn->dij_min(i, j);
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| 164 | //
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| 165 | // if (j >= 0) {
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| 166 | // cs.plugin_record_ij_recombination(i, j, dij, k);
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| 167 | // nn->merge_jets(i, j, cs.jets()[k], k);
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| 168 | // } else {
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| 169 | // double diB = cs.jets()[i].E()*cs.jets()[i].E(); // get new diB
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| 170 | // cs.plugin_record_iB_recombination(i, diB);
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| 171 | // nn->remove_jet(i);
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| 172 | // }
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| 173 | // njets--;
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| 174 | // }
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| 175 | // delete nn;
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| 176 | // }
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| 177 |
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| 178 |
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| 179 | template<class N> void JadePlugin::_actual_run_clustering(ClusterSequence & cs) const {
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| 180 |
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[d7d2da3] | 181 | int njets = cs.jets().size();
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[1d208a2] | 182 |
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| 183 | N nn(cs.jets());
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[d7d2da3] | 184 |
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| 185 | // if testing against Hoeth's implementation, need to rescale the
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| 186 | // dij by Q^2.
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| 187 | //double Q2 = cs.Q2();
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| 188 |
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| 189 | while (njets > 0) {
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| 190 | int i, j, k;
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[1d208a2] | 191 | double dij = nn.dij_min(i, j);
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[d7d2da3] | 192 |
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| 193 | if (j >= 0) {
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| 194 | cs.plugin_record_ij_recombination(i, j, dij, k);
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[1d208a2] | 195 | nn.merge_jets(i, j, cs.jets()[k], k);
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[d7d2da3] | 196 | } else {
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| 197 | double diB = cs.jets()[i].E()*cs.jets()[i].E(); // get new diB
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| 198 | cs.plugin_record_iB_recombination(i, diB);
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[1d208a2] | 199 | nn.remove_jet(i);
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[d7d2da3] | 200 | }
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| 201 | njets--;
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| 202 | }
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[1d208a2] | 203 |
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[d7d2da3] | 204 | }
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| 205 |
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[1d208a2] | 206 | //----------------------------------------------------------------------
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| 207 | void JadePlugin::run_clustering(ClusterSequence & cs) const {
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| 208 |
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| 209 | switch(_strategy) {
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| 210 | case strategy_NNH:
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| 211 | _actual_run_clustering<NNH<JadeBriefJet> >(cs);
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| 212 | break;
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| 213 | case strategy_NNFJN2Plain:
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| 214 | _actual_run_clustering<NNFJN2Plain<JadeBriefJet> >(cs);
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| 215 | break;
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| 216 | default:
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| 217 | throw Error("Unrecognized strategy in JadePlugin");
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| 218 | }
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| 219 | }
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| 220 |
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| 221 |
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[d7d2da3] | 222 | FASTJET_END_NAMESPACE // defined in fastjet/internal/base.hh
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