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source: git/external/fastjet/ClusterSequence_Delaunay.cc@ be6c1c8

ImprovedOutputFile Timing dual_readout llp
Last change on this file since be6c1c8 was d69dfe4, checked in by pavel <pavel@…>, 11 years ago

upgrade fastjet to 3.0.6

  • Property mode set to 100644
File size: 9.2 KB
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1//STARTHEADER
2// $Id$
3//
4// Copyright (c) 2005-2011, Matteo Cacciari, Gavin P. Salam and Gregory Soyez
5//
6//----------------------------------------------------------------------
7// This file is part of FastJet.
8//
9// FastJet is free software; you can redistribute it and/or modify
10// it under the terms of the GNU General Public License as published by
11// the Free Software Foundation; either version 2 of the License, or
12// (at your option) any later version.
13//
14// The algorithms that underlie FastJet have required considerable
15// development and are described in hep-ph/0512210. If you use
16// FastJet as part of work towards a scientific publication, please
17// include a citation to the FastJet paper.
18//
19// FastJet is distributed in the hope that it will be useful,
20// but WITHOUT ANY WARRANTY; without even the implied warranty of
21// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
22// GNU General Public License for more details.
23//
24// You should have received a copy of the GNU General Public License
25// along with FastJet. If not, see <http://www.gnu.org/licenses/>.
26//----------------------------------------------------------------------
27//ENDHEADER
28
29
30#include "fastjet/Error.hh"
31#include "fastjet/PseudoJet.hh"
32#include "fastjet/ClusterSequence.hh"
33#include "fastjet/internal/DynamicNearestNeighbours.hh"
34#include<iostream>
35#include<sstream>
36#include<cmath>
37#include <cstdlib>
38#include<cassert>
39#include<memory>
40//
41#ifndef DROP_CGAL // in case we do not have the code for CGAL
42#include "fastjet/internal/Dnn4piCylinder.hh"
43#include "fastjet/internal/Dnn3piCylinder.hh"
44#include "fastjet/internal/Dnn2piCylinder.hh"
45#endif // DROP_CGAL
46
47FASTJET_BEGIN_NAMESPACE // defined in fastjet/internal/base.hh
48
49using namespace std;
50
51
52//----------------------------------------------------------------------
53/// Run the clustering using a Hierarchical Delaunay triangulation and
54/// STL maps to achieve O(N*ln N) behaviour.
55///
56/// There may be internally asserted assumptions about absence of
57/// points with coincident eta-phi coordinates.
58void ClusterSequence::_delaunay_cluster () {
59
60 int n = _jets.size();
61
62 vector<EtaPhi> points(n); // recall EtaPhi is just a typedef'd pair<double>
63 for (int i = 0; i < n; i++) {
64 points[i] = EtaPhi(_jets[i].rap(),_jets[i].phi_02pi());
65 points[i].sanitize(); // make sure things are in the right range
66 }
67
68 // initialise our DNN structure with the set of points
69 auto_ptr<DynamicNearestNeighbours> DNN;
70#ifndef DROP_CGAL // strategy = NlnN* are not supported if we drop CGAL...
71 bool verbose = false;
72 bool ignore_nearest_is_mirror = (_Rparam < twopi);
73 if (_strategy == NlnN4pi) {
74 DNN.reset(new Dnn4piCylinder(points,verbose));
75 } else if (_strategy == NlnN3pi) {
76 DNN.reset(new Dnn3piCylinder(points,ignore_nearest_is_mirror,verbose));
77 } else if (_strategy == NlnN) {
78 DNN.reset(new Dnn2piCylinder(points,ignore_nearest_is_mirror,verbose));
79 } else
80#else
81 if (_strategy == NlnN4pi || _strategy == NlnN3pi || _strategy == NlnN) {
82 ostringstream err;
83 err << "ERROR: Requested strategy "<<strategy_string()<<" but it is not"<<endl;
84 err << " supported because FastJet was compiled without CGAL"<<endl;
85 throw Error(err.str());
86 //assert(false);
87 }
88#endif // DROP_CGAL
89 {
90 ostringstream err;
91 err << "ERROR: Unrecognized value for strategy: "<<_strategy<<endl;
92 assert(false);
93 throw Error(err.str());
94 }
95
96 // We will find nearest neighbour for each vertex, and include
97 // distance in map (NB DistMap is a typedef given in the .h file)
98 DistMap DijMap;
99
100 // fill the map with the minimal (as far as we know) subset of Dij
101 // distances (i.e. nearest neighbour ones).
102 for (int ii = 0; ii < n; ii++) {
103 _add_ktdistance_to_map(ii, DijMap, DNN.get());
104 }
105
106 // run the clustering (go up to i=n-1, but then will stop half-way down,
107 // when we reach that point -- it will be the final beam jet and there
108 // will be no nearest neighbours to find).
109 for (int i=0;i<n;i++) {
110 // find nearest vertices
111 // NB: skip cases where the point is not there anymore!
112 TwoVertices SmallestDijPair;
113 int jet_i, jet_j;
114 double SmallestDij;
115 bool Valid2;
116 bool recombine_with_beam;
117 do {
118 SmallestDij = DijMap.begin()->first;
119 SmallestDijPair = DijMap.begin()->second;
120 jet_i = SmallestDijPair.first;
121 jet_j = SmallestDijPair.second;
122 // distance is immediately removed regardless of whether or not
123 // it is used.
124 // Some temporary testing code relating to problems with the gcc-3.2 compiler
125 //cout << "got here and size is "<< DijMap.size()<< " and it is "<<SmallestDij <<"\n";
126 //cout << jet_i << " "<< jet_j<<"\n";
127 DijMap.erase(DijMap.begin());
128 //cout << "got beyond here\n";
129
130 // need to "prime" the validity of jet_j in such a way that
131 // if it corresponds to the beam then it is automatically valid.
132 recombine_with_beam = (jet_j == BeamJet);
133 if (!recombine_with_beam) {Valid2 = DNN->Valid(jet_j);}
134 else {Valid2 = true;}
135
136 } while ( !DNN->Valid(jet_i) || !Valid2);
137
138
139 // The following part acts just on jet momenta and on the history.
140 // The action on the nearest-neighbour structures takes place
141 // later (only if at least 2 jets are around).
142 if (! recombine_with_beam) {
143 int nn; // will be index of new jet
144 _do_ij_recombination_step(jet_i, jet_j, SmallestDij, nn);
145 //OBS // merge the two jets, add new jet, remove old ones
146 //OBS _jets.push_back(_jets[jet_i] + _jets[jet_j]);
147 //OBS
148 //OBS int nn = _jets.size()-1;
149 //OBS _jets[nn].set_cluster_hist_index(n+i);
150 //OBS
151 //OBS // get corresponding indices in history structure
152 //OBS int hist_i = _jets[jet_i].cluster_hist_index();
153 //OBS int hist_j = _jets[jet_j].cluster_hist_index();
154 //OBS
155 //OBS
156 //OBS _add_step_to_history(n+i,min(hist_i,hist_j), max(hist_i,hist_j),
157 //OBS _jets.size()-1, SmallestDij);
158
159 // add new point to points vector
160 EtaPhi newpoint(_jets[nn].rap(), _jets[nn].phi_02pi());
161 newpoint.sanitize(); // make sure it is in correct range
162 points.push_back(newpoint);
163 } else {
164 // recombine the jet with the beam
165 _do_iB_recombination_step(jet_i, SmallestDij);
166 //OBS _add_step_to_history(n+i,_jets[jet_i].cluster_hist_index(),BeamJet,
167 //OBS Invalid, SmallestDij);
168 }
169
170 // exit the loop because we do not want to look for nearest neighbours
171 // etc. of zero partons
172 if (i == n-1) {break;}
173
174 vector<int> updated_neighbours;
175 if (! recombine_with_beam) {
176 // update DNN
177 int point3;
178 DNN->RemoveCombinedAddCombination(jet_i, jet_j,
179 points[points.size()-1], point3,
180 updated_neighbours);
181 // C++ beginners' comment: static_cast to unsigned int is necessary
182 // to do away with warnings about type mismatch between point3 (int)
183 // and points.size (unsigned int)
184 if (static_cast<unsigned int> (point3) != points.size()-1) {
185 throw Error("INTERNAL ERROR: point3 != points.size()-1");}
186 } else {
187 // update DNN
188 DNN->RemovePoint(jet_i, updated_neighbours);
189 }
190
191 // update map
192 vector<int>::iterator it = updated_neighbours.begin();
193 for (; it != updated_neighbours.end(); ++it) {
194 int ii = *it;
195 _add_ktdistance_to_map(ii, DijMap, DNN.get());
196 }
197
198 } // end clustering loop
199
200}
201
202
203//----------------------------------------------------------------------
204/// Add the current kt distance for particle ii to the map (DijMap)
205/// using information from the DNN object. Work as follows:
206///
207/// . if the kt is zero then it's nearest neighbour is taken to be the
208/// the beam jet and the distance is zero.
209///
210/// . if cylinder distance to nearest neighbour > _Rparam then it is
211/// yiB that is smallest and this is added to map.
212///
213/// . otherwise if the nearest neighbour jj has a larger kt then add
214/// dij to the map.
215///
216/// . otherwise do nothing
217///
218void ClusterSequence::_add_ktdistance_to_map(
219 const int & ii,
220 DistMap & DijMap,
221 const DynamicNearestNeighbours * DNN) {
222
223 double yiB = jet_scale_for_algorithm(_jets[ii]);
224 if (yiB == 0.0) {
225 // in this case convention is that we do not worry about distances
226 // but directly state that nearest neighbour is beam
227 DijMap.insert(DijEntry(yiB, TwoVertices(ii,-1)));
228 } else {
229 double DeltaR2 = DNN->NearestNeighbourDistance(ii) * _invR2;
230 // Logic of following bit is: only add point to map if it has
231 // smaller kt2 than nearest neighbour j (if it has larger kt,
232 // then: either it is j's nearest neighbour and then we will
233 // include dij when we come to j; or it is not j's nearest
234 // neighbour and j will recombine with someone else).
235
236 // If DeltaR2 > 1.0 then in any case it will recombine with beam rather
237 // than with any neighbours.
238 // (put general normalisation here at some point)
239 if (DeltaR2 > 1.0) {
240 DijMap.insert(DijEntry(yiB, TwoVertices(ii,-1)));
241 } else {
242 double kt2i = jet_scale_for_algorithm(_jets[ii]);
243 int jj = DNN->NearestNeighbourIndex(ii);
244 if (kt2i <= jet_scale_for_algorithm(_jets[jj])) {
245 double dij = DeltaR2 * kt2i;
246 DijMap.insert(DijEntry(dij, TwoVertices(ii,jj)));
247 }
248 }
249 }
250}
251
252
253FASTJET_END_NAMESPACE
254
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