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| 2 | //STARTHEADER
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| 3 | // $Id: ClusterSequenceAreaBase.cc,v 1.1 2008-11-06 14:32:14 ovyn Exp $
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| 4 | //
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| 5 | // Copyright (c) 2005-2006, Matteo Cacciari and Gavin Salam
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| 6 | //
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| 7 | //----------------------------------------------------------------------
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| 8 | // This file is part of FastJet.
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| 9 | //
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| 10 | // FastJet is free software; you can redistribute it and/or modify
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| 11 | // it under the terms of the GNU General Public License as published by
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| 12 | // the Free Software Foundation; either version 2 of the License, or
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| 13 | // (at your option) any later version.
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| 14 | //
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| 15 | // The algorithms that underlie FastJet have required considerable
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| 16 | // development and are described in hep-ph/0512210. If you use
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| 17 | // FastJet as part of work towards a scientific publication, please
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| 18 | // include a citation to the FastJet paper.
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| 19 | //
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| 20 | // FastJet is distributed in the hope that it will be useful,
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| 21 | // but WITHOUT ANY WARRANTY; without even the implied warranty of
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| 22 | // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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| 23 | // GNU General Public License for more details.
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| 24 | //
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| 25 | // You should have received a copy of the GNU General Public License
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| 26 | // along with FastJet; if not, write to the Free Software
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| 27 | // Foundation, Inc.:
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| 28 | // 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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| 29 | //----------------------------------------------------------------------
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| 30 | //ENDHEADER
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| 31 |
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| 32 |
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| 33 |
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| 34 |
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| 35 | #include "../include/fastjet/ClusterSequenceAreaBase.hh"
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| 36 | #include <algorithm>
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| 37 |
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| 38 | FASTJET_BEGIN_NAMESPACE
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| 39 |
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| 40 | using namespace std;
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| 41 |
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| 42 |
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| 43 | /// allow for warnings
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| 44 | LimitedWarning ClusterSequenceAreaBase::_warnings;
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| 45 |
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| 46 | //----------------------------------------------------------------------
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| 47 | /// return the total area, within range, that is free of jets.
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| 48 | ///
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| 49 | /// Calculate this as (range area) - \sum_{i in range} A_i
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| 50 | ///
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| 51 | double ClusterSequenceAreaBase::empty_area(const RangeDefinition & range) const {
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| 52 | double empty = range.area();
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| 53 | vector<PseudoJet> incl_jets(inclusive_jets(0.0));
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| 54 | for (unsigned i = 0; i < incl_jets.size(); i++) {
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| 55 | if (range.is_in_range(incl_jets[i])) empty -= area(incl_jets[i]);
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| 56 | }
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| 57 | return empty;
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| 58 | }
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| 59 |
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| 60 | double ClusterSequenceAreaBase::median_pt_per_unit_area(const RangeDefinition & range) const {
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| 61 | return median_pt_per_unit_something(range,false);
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| 62 | }
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| 63 |
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| 64 | double ClusterSequenceAreaBase::median_pt_per_unit_area_4vector(const RangeDefinition & range) const {
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| 65 | return median_pt_per_unit_something(range,true);
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| 66 | }
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| 67 |
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| 68 |
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| 69 | //----------------------------------------------------------------------
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| 70 | /// the median of (pt/area) for jets contained within range, counting
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| 71 | /// the empty area as if it were made up of a collection of empty
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| 72 | /// jets each of area (0.55 * pi R^2).
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| 73 | double ClusterSequenceAreaBase::median_pt_per_unit_something(
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| 74 | const RangeDefinition & range, bool use_area_4vector) const {
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| 75 |
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| 76 | double median, sigma, mean_area;
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| 77 | get_median_rho_and_sigma(range, use_area_4vector, median, sigma, mean_area);
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| 78 | return median;
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| 79 |
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| 80 | }
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| 81 |
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| 82 |
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| 83 | //----------------------------------------------------------------------
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| 84 | /// fits a form pt_per_unit_area(y) = a + b*y^2 for jets in range.
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| 85 | /// exclude_above allows one to exclude large values of pt/area from fit.
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| 86 | /// use_area_4vector = true uses the 4vector areas.
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| 87 | void ClusterSequenceAreaBase::parabolic_pt_per_unit_area(
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| 88 | double & a, double & b, const RangeDefinition & range,
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| 89 | double exclude_above, bool use_area_4vector) const {
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| 90 |
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| 91 | int n=0;
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| 92 | int n_excluded = 0;
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| 93 | double mean_f=0, mean_x2=0, mean_x4=0, mean_fx2=0;
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| 94 |
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| 95 | vector<PseudoJet> incl_jets = inclusive_jets();
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| 96 |
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| 97 | for (unsigned i = 0; i < incl_jets.size(); i++) {
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| 98 | if (range.is_in_range(incl_jets[i])) {
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| 99 | double this_area;
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| 100 | if ( use_area_4vector ) {
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| 101 | this_area = area_4vector(incl_jets[i]).perp();
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| 102 | } else {
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| 103 | this_area = area(incl_jets[i]);
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| 104 | }
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| 105 | double f = incl_jets[i].perp()/this_area;
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| 106 | if (exclude_above <= 0.0 || f < exclude_above) {
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| 107 | double x = incl_jets[i].rap(); double x2 = x*x;
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| 108 | mean_f += f;
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| 109 | mean_x2 += x2;
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| 110 | mean_x4 += x2*x2;
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| 111 | mean_fx2 += f*x2;
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| 112 | n++;
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| 113 | } else {
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| 114 | n_excluded++;
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| 115 | }
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| 116 | }
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| 117 | }
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| 118 |
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| 119 | if (n <= 1) {
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| 120 | // meaningful results require at least two jets inside the
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| 121 | // area -- mind you if there are empty jets we should be in
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| 122 | // any case doing something special...
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| 123 | a = 0.0;
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| 124 | b = 0.0;
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| 125 | } else {
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| 126 | mean_f /= n;
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| 127 | mean_x2 /= n;
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| 128 | mean_x4 /= n;
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| 129 | mean_fx2 /= n;
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| 130 |
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| 131 | b = (mean_f*mean_x2 - mean_fx2)/(mean_x2*mean_x2 - mean_x4);
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| 132 | a = mean_f - b*mean_x2;
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| 133 | }
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| 134 | //cerr << "n_excluded = "<< n_excluded << endl;
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| 135 | }
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| 136 |
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| 137 |
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| 138 |
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| 139 |
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| 140 | void ClusterSequenceAreaBase::get_median_rho_and_sigma(
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| 141 | const RangeDefinition & range, bool use_area_4vector,
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| 142 | double & median, double & sigma, double & mean_area) const {
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| 143 |
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| 144 | _check_jet_alg_good_for_median();
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| 145 |
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| 146 | vector<double> pt_over_areas;
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| 147 | vector<PseudoJet> incl_jets = inclusive_jets();
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| 148 | double total_area = 0.0;
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| 149 | double total_njets = 0;
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| 150 |
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| 151 | for (unsigned i = 0; i < incl_jets.size(); i++) {
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| 152 | if (range.is_in_range(incl_jets[i])) {
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| 153 | double this_area;
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| 154 | if (use_area_4vector) {
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| 155 | this_area = area_4vector(incl_jets[i]).perp();
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| 156 | } else {
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| 157 | this_area = area(incl_jets[i]);
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| 158 | }
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| 159 | pt_over_areas.push_back(incl_jets[i].perp()/this_area);
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| 160 | total_area += this_area;
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| 161 | total_njets += 1.0;
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| 162 | }
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| 163 | }
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| 164 |
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| 165 | // there is nothing inside our region, so answer will always be zero
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| 166 | if (pt_over_areas.size() == 0) {
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| 167 | median = 0.0;
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| 168 | sigma = 0.0;
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| 169 | mean_area = 0.0;
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| 170 | return;
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| 171 | }
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| 172 |
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| 173 | // get median (pt/area) [this is the "old" median definition. It considers
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| 174 | // only the "real" jets in calculating the median, i.e. excluding the
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| 175 | // only-ghost ones]
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| 176 | sort(pt_over_areas.begin(), pt_over_areas.end());
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| 177 |
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| 178 | // now get the median & error, accounting for empty jets
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| 179 | // define the fractions of distribution at median, median-1sigma
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| 180 | double posn[2] = {0.5, (1.0-0.6827)/2.0};
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| 181 | double res[2];
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| 182 |
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| 183 | double n_empty = n_empty_jets(range);
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| 184 | total_njets += n_empty;
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| 185 | total_area += empty_area(range);
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| 186 |
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| 187 | for (int i = 0; i < 2; i++) {
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| 188 | double nj_median_pos =
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| 189 | (pt_over_areas.size()-1 + n_empty)*posn[i] - n_empty;
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| 190 | double nj_median_ratio;
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| 191 | if (nj_median_pos >= 0 && pt_over_areas.size() > 1) {
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| 192 | int int_nj_median = int(nj_median_pos);
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| 193 | nj_median_ratio =
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| 194 | pt_over_areas[int_nj_median] * (int_nj_median+1-nj_median_pos)
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| 195 | + pt_over_areas[int_nj_median+1] * (nj_median_pos - int_nj_median);
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| 196 | } else {
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| 197 | nj_median_ratio = 0.0;
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| 198 | }
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| 199 | res[i] = nj_median_ratio;
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| 200 | }
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| 201 | median = res[0];
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| 202 | double error = res[0] - res[1];
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| 203 | mean_area = total_area / total_njets;
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| 204 | sigma = error * sqrt(mean_area);
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| 205 | }
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| 206 |
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| 207 |
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| 208 | /// return a vector of all subtracted jets, using area_4vector, given rho.
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| 209 | /// Only inclusive_jets above ptmin are subtracted and returned.
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| 210 | /// the ordering is the same as that of sorted_by_pt(cs.inclusive_jets()),
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| 211 | /// i.e. not necessarily ordered in pt once subtracted
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| 212 | vector<PseudoJet> ClusterSequenceAreaBase::subtracted_jets(const double rho,
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| 213 | const double ptmin)
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| 214 | const {
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| 215 | vector<PseudoJet> sub_jets;
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| 216 | vector<PseudoJet> jets = sorted_by_pt(inclusive_jets(ptmin));
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| 217 | for (unsigned i=0; i<jets.size(); i++) {
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| 218 | PseudoJet sub_jet = subtracted_jet(jets[i],rho);
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| 219 | sub_jets.push_back(sub_jet);
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| 220 | }
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| 221 | return sub_jets;
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| 222 | }
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| 223 |
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| 224 | /// return a vector of subtracted jets, using area_4vector.
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| 225 | /// Only inclusive_jets above ptmin are subtracted and returned.
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| 226 | /// the ordering is the same as that of sorted_by_pt(cs.inclusive_jets()),
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| 227 | /// i.e. not necessarily ordered in pt once subtracted
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| 228 | vector<PseudoJet> ClusterSequenceAreaBase::subtracted_jets(
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| 229 | const RangeDefinition & range,
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| 230 | const double ptmin)
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| 231 | const {
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| 232 | double rho = median_pt_per_unit_area_4vector(range);
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| 233 | return subtracted_jets(rho,ptmin);
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| 234 | }
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| 235 |
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| 236 |
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| 237 | /// return a subtracted jet, using area_4vector, given rho
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| 238 | PseudoJet ClusterSequenceAreaBase::subtracted_jet(const PseudoJet & jet,
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| 239 | const double rho) const {
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| 240 | PseudoJet area4vect = area_4vector(jet);
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| 241 | PseudoJet sub_jet;
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| 242 | // sanity check
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| 243 | if (rho*area4vect.perp() < jet.perp() ) {
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| 244 | sub_jet = jet - rho*area4vect;
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| 245 | } else { sub_jet = PseudoJet(0.0,0.0,0.0,0.0); }
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| 246 |
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| 247 | // make sure the subtracted jet has the same index
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| 248 | // (i.e. "looks like") the original jet
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| 249 | sub_jet.set_cluster_hist_index(jet.cluster_hist_index());
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| 250 |
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| 251 | return sub_jet;
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| 252 | }
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| 253 |
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| 254 |
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| 255 | /// return a subtracted jet, using area_4vector; note that this is
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| 256 | /// potentially inefficient if repeatedly used for many different
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| 257 | /// jets, because rho will be recalculated each time around.
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| 258 | PseudoJet ClusterSequenceAreaBase::subtracted_jet(const PseudoJet & jet,
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| 259 | const RangeDefinition & range) const {
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| 260 | double rho = median_pt_per_unit_area_4vector(range);
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| 261 | PseudoJet sub_jet = subtracted_jet(jet, rho);
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| 262 | return sub_jet;
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| 263 | }
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| 264 |
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| 265 |
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| 266 | /// return the subtracted pt, given rho
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| 267 | double ClusterSequenceAreaBase::subtracted_pt(const PseudoJet & jet,
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| 268 | const double rho,
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| 269 | bool use_area_4vector) const {
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| 270 | if ( use_area_4vector ) {
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| 271 | PseudoJet sub_jet = subtracted_jet(jet,rho);
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| 272 | return sub_jet.perp();
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| 273 | } else {
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| 274 | return jet.perp() - rho*area(jet);
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| 275 | }
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| 276 | }
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| 277 |
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| 278 |
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| 279 | /// return the subtracted pt; note that this is
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| 280 | /// potentially inefficient if repeatedly used for many different
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| 281 | /// jets, because rho will be recalculated each time around.
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| 282 | double ClusterSequenceAreaBase::subtracted_pt(const PseudoJet & jet,
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| 283 | const RangeDefinition & range,
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| 284 | bool use_area_4vector) const {
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| 285 | if ( use_area_4vector ) {
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| 286 | PseudoJet sub_jet = subtracted_jet(jet,range);
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| 287 | return sub_jet.perp();
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| 288 | } else {
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| 289 | double rho = median_pt_per_unit_area(range);
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| 290 | return subtracted_pt(jet,rho,false);
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| 291 | }
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| 292 | }
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| 293 |
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| 294 |
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| 295 | /// check the jet algorithm is suitable (and if not issue a warning)
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| 296 | void ClusterSequenceAreaBase::_check_jet_alg_good_for_median() const {
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| 297 | if (jet_def().jet_algorithm() != kt_algorithm
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| 298 | && jet_def().jet_algorithm() != cambridge_algorithm
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| 299 | && jet_def().jet_algorithm() != cambridge_for_passive_algorithm) {
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| 300 | _warnings.warn("ClusterSequenceAreaBase: jet_def being used may not be suitable for estimating diffuse backgrounds (good options are kt, cam)");
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| 301 | }
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| 302 | }
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| 303 |
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| 304 |
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| 305 |
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| 306 | FASTJET_END_NAMESPACE
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