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Vx3DHLTAnalyzer.cc
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1 /*
2  \File Vx3DHLTAnalyzer.cc
3  \Display Beam-spot monitor entirely based on pixel detector information
4  the monitoring is based on a 3D fit to the vertex cloud
5  \Author Mauro Dinardo
6  \Version $ Revision: 3.5 $
7  \Date $ Date: 2010/23/02 13:15:00 $
8 */
9 
10 
11 #include "DQM/BeamMonitor/plugins/Vx3DHLTAnalyzer.h"
12 
13 #include "FWCore/ServiceRegistry/interface/Service.h"
14 #include "FWCore/Utilities/interface/isFinite.h"
15 
16 #include <Math/Minimizer.h>
17 #include <Math/Factory.h>
18 #include <Math/Functor.h>
19 
20 
21 // ### Calling namespaces ###
22 using namespace std;
23 using namespace edm;
24 using namespace reco;
25 
26 
27 Vx3DHLTAnalyzer::Vx3DHLTAnalyzer (const ParameterSet& iConfig)
28 {
29  debugMode = true;
30  nLumiFit = 2; // Number of integrated lumis to perform the fit
31  maxLumiIntegration = 15; // If failing fits, this is the maximum number of integrated lumis after which a reset is issued
32  nLumiXaxisRange = 5000; // Correspond to about 32h of data taking: 32h * 60min * 60s / 23s per lumi-block = 5009
33  dataFromFit = true; // The Beam Spot data can be either taken from the histograms or from the fit results
34  minNentries = 20; // Minimum number of good vertices to perform the fit
35  xRange = 0.8; // [cm]
36  xStep = 0.001; // [cm]
37  yRange = 0.8; // [cm]
38  yStep = 0.001; // [cm]
39  zRange = 30.; // [cm]
40  zStep = 0.04; // [cm]
41  VxErrCorr = 1.3;
42  minVxDoF = 10.; // Good-vertex selection cut
43  // For vertex fitter without track-weight: d.o.f. = 2*NTracks - 3
44  // For vertex fitter with track-weight: d.o.f. = sum_NTracks(2*track_weight) - 3
45  minVxWgt = 0.5; // Good-vertex selection cut
46  fileName = "BeamPixelResults.txt";
47 
48  vertexCollection = consumes<VertexCollection> (iConfig.getUntrackedParameter<InputTag>("vertexCollection", InputTag("pixelVertices")));
49  pixelHitCollection = consumes<SiPixelRecHitCollection>(iConfig.getUntrackedParameter<InputTag>("pixelHitCollection", InputTag("siPixelRecHits")));
50 
51  debugMode = iConfig.getParameter<bool>("debugMode");
52  nLumiFit = iConfig.getParameter<unsigned int>("nLumiFit");
53  maxLumiIntegration = iConfig.getParameter<unsigned int>("maxLumiIntegration");
54  nLumiXaxisRange = iConfig.getParameter<unsigned int>("nLumiXaxisRange");
55  dataFromFit = iConfig.getParameter<bool>("dataFromFit");
56  minNentries = iConfig.getParameter<unsigned int>("minNentries");
57  xRange = iConfig.getParameter<double>("xRange");
58  xStep = iConfig.getParameter<double>("xStep");
59  yRange = iConfig.getParameter<double>("yRange");
60  yStep = iConfig.getParameter<double>("yStep");
61  zRange = iConfig.getParameter<double>("zRange");
62  zStep = iConfig.getParameter<double>("zStep");
63  VxErrCorr = iConfig.getParameter<double>("VxErrCorr");
64  minVxDoF = iConfig.getParameter<double>("minVxDoF");
65  minVxWgt = iConfig.getParameter<double>("minVxWgt");
66  fileName = iConfig.getParameter<string>("fileName");
67 
68 
69  // ### Set internal variables ###
70  nParams = 9; // Number of free parameters in the fit
71  internalDebug = false;
72  considerVxCovariance = true; // Deconvolute vertex covariance matrix
73  pi = 3.141592653589793238;
74  // ##############################
75 }
76 
77 
78 Vx3DHLTAnalyzer::~Vx3DHLTAnalyzer ()
79 {
80  reset("scratch");
81 }
82 
83 
84 void Vx3DHLTAnalyzer::analyze (const Event& iEvent, const EventSetup& iSetup)
85 {
86  Handle<VertexCollection> Vx3DCollection;
87  iEvent.getByToken(vertexCollection, Vx3DCollection);
88 
89  unsigned int i,j;
90  double det;
91  VertexType MyVertex;
92 
93  if (runNumber != iEvent.id().run())
94  {
95  reset("scratch");
96  runNumber = iEvent.id().run();
97 
98  if (debugMode == true)
99  {
100  stringstream debugFile;
101  string tmp(fileName);
102 
103  if (outputDebugFile.is_open() == true) outputDebugFile.close();
104  tmp.erase(strlen(fileName.c_str())-4,4);
105  debugFile << tmp.c_str() << "_Run" << iEvent.id().run() << ".txt";
106  outputDebugFile.open(debugFile.str().c_str(), ios::out);
107  outputDebugFile.close();
108  outputDebugFile.open(debugFile.str().c_str(), ios::app);
109  }
110 
111  beginLuminosityBlock(iEvent.getLuminosityBlock(),iSetup);
112  }
113  else if (beginTimeOfFit != 0)
114  {
115  totalHits += HitCounter(iEvent);
116 
117  if (internalDebug == true)
118  {
119  cout << "[Vx3DHLTAnalyzer]::\tI found " << totalHits << " pixel hits until now" << endl;
120  cout << "[Vx3DHLTAnalyzer]::\tIn this event there are " << Vx3DCollection->size() << " vertex cadidates" << endl;
121  }
122 
123  for (vector<Vertex>::const_iterator it3DVx = Vx3DCollection->begin(); it3DVx != Vx3DCollection->end(); it3DVx++)
124  {
125  if (internalDebug == true)
126  {
127  cout << "[Vx3DHLTAnalyzer]::\tVertex selections:" << endl;
128  cout << "[Vx3DHLTAnalyzer]::\tEvent ID = " << iEvent.id() << endl;
129  cout << "[Vx3DHLTAnalyzer]::\tVertex number = " << it3DVx - Vx3DCollection->begin() << endl;
130  cout << "[Vx3DHLTAnalyzer]::\tisValid = " << it3DVx->isValid() << endl;
131  cout << "[Vx3DHLTAnalyzer]::\tisFake = " << it3DVx->isFake() << endl;
132  cout << "[Vx3DHLTAnalyzer]::\tnodof = " << it3DVx->ndof() << endl;
133  cout << "[Vx3DHLTAnalyzer]::\ttracksSize = " << it3DVx->tracksSize() << endl;
134  }
135 
136  if ((it3DVx->isValid() == true) &&
137  (it3DVx->isFake() == false) &&
138  (it3DVx->ndof() >= minVxDoF) &&
139  (it3DVx->tracksSize() > 0) &&
140  ((it3DVx->ndof()+3.) / ((double)it3DVx->tracksSize()) >= 2.*minVxWgt))
141  {
142  for (i = 0; i < DIM; i++)
143  {
144  for (j = 0; j < DIM; j++)
145  {
146  MyVertex.Covariance[i][j] = it3DVx->covariance(i,j);
147  if (isNotFinite(MyVertex.Covariance[i][j]) == true) break;
148  }
149 
150  if (j != DIM) break;
151  }
152 
153  if (i == DIM)
154  det = std::fabs(MyVertex.Covariance[0][0])*(std::fabs(MyVertex.Covariance[1][1])*std::fabs(MyVertex.Covariance[2][2]) - MyVertex.Covariance[1][2]*MyVertex.Covariance[1][2]) -
155  MyVertex.Covariance[0][1]*(MyVertex.Covariance[0][1]*std::fabs(MyVertex.Covariance[2][2]) - MyVertex.Covariance[0][2]*MyVertex.Covariance[1][2]) +
156  MyVertex.Covariance[0][2]*(MyVertex.Covariance[0][1]*MyVertex.Covariance[1][2] - MyVertex.Covariance[0][2]*std::fabs(MyVertex.Covariance[1][1]));
157 
158  if ((i == DIM) && (det > 0.))
159  {
160  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tVertex accepted !" << endl;
161 
162  MyVertex.x = it3DVx->x();
163  MyVertex.y = it3DVx->y();
164  MyVertex.z = it3DVx->z();
165  Vertices.push_back(MyVertex);
166 
167  Vx_X->Fill(it3DVx->x());
168  Vx_Y->Fill(it3DVx->y());
169  Vx_Z->Fill(it3DVx->z());
170 
171  Vx_ZX->Fill(it3DVx->z(), it3DVx->x());
172  Vx_ZY->Fill(it3DVx->z(), it3DVx->y());
173  Vx_XY->Fill(it3DVx->x(), it3DVx->y());
174 
175  Vx_X_Cum->Fill(it3DVx->x());
176  Vx_Y_Cum->Fill(it3DVx->y());
177  Vx_Z_Cum->Fill(it3DVx->z());
178 
179  Vx_ZX_Cum->Fill(it3DVx->z(), it3DVx->x());
180  Vx_ZY_Cum->Fill(it3DVx->z(), it3DVx->y());
181  Vx_XY_Cum->Fill(it3DVx->x(), it3DVx->y());
182  }
183  else if (internalDebug == true)
184  {
185  cout << "[Vx3DHLTAnalyzer]::\tVertex discarded !" << endl;
186 
187  for (i = 0; i < DIM; i++)
188  for (j = 0; j < DIM; j++)
189  cout << "(i,j) --> " << i << "," << j << " --> " << MyVertex.Covariance[i][j] << endl;
190  }
191  }
192  else if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tVertex discarded !" << endl;
193  }
194  }
195 }
196 
197 
198 unsigned int Vx3DHLTAnalyzer::HitCounter (const Event& iEvent)
199 {
200  Handle<SiPixelRecHitCollection> rechitspixel;
201  iEvent.getByToken(pixelHitCollection, rechitspixel);
202 
203  unsigned int counter = 0;
204 
205  for (SiPixelRecHitCollection::const_iterator j = rechitspixel->begin(); j != rechitspixel->end(); j++)
206  for (edmNew::DetSet<SiPixelRecHit>::const_iterator h = j->begin(); h != j->end(); h++) counter += h->cluster()->size();
207 
208  return counter;
209 }
210 
211 
212 string Vx3DHLTAnalyzer::formatTime (const time_t& t)
213 {
214  char ts[25];
215  strftime(ts, sizeof(ts), "%Y.%m.%d %H:%M:%S %Z", gmtime(&t));
216 
217  string ts_string(ts);
218 
219  return ts_string;
220 }
221 
222 
223 double Vx3DHLTAnalyzer::Gauss3DFunc (const double* par)
224 {
225  double K[DIM][DIM]; // Covariance Matrix
226  double M[DIM][DIM]; // K^-1
227  double det;
228  double sumlog = 0.;
229 
230 // par[0] = K(0,0) --> Var[X]
231 // par[1] = K(1,1) --> Var[Y]
232 // par[2] = K(2,2) --> Var[Z]
233 // par[3] = K(0,1) = K(1,0) --> Cov[X,Y]
234 // par[4] = K(1,2) = K(2,1) --> Cov[Y,Z] --> dy/dz
235 // par[5] = K(0,2) = K(2,0) --> Cov[X,Z] --> dx/dz
236 // par[6] = mean x
237 // par[7] = mean y
238 // par[8] = mean z
239 
240  counterVx = 0;
241  for (unsigned int i = 0; i < Vertices.size(); i++)
242  {
243  if ((std::sqrt((Vertices[i].x-xPos)*(Vertices[i].x-xPos) + (Vertices[i].y-yPos)*(Vertices[i].y-yPos)) <= maxTransRadius) &&
244  (std::fabs(Vertices[i].z-zPos) <= maxLongLength))
245  {
246  if (considerVxCovariance == true)
247  {
248  K[0][0] = std::fabs(par[0]) + VxErrCorr*VxErrCorr * std::fabs(Vertices[i].Covariance[0][0]);
249  K[1][1] = std::fabs(par[1]) + VxErrCorr*VxErrCorr * std::fabs(Vertices[i].Covariance[1][1]);
250  K[2][2] = std::fabs(par[2]) + VxErrCorr*VxErrCorr * std::fabs(Vertices[i].Covariance[2][2]);
251  K[0][1] = K[1][0] = par[3] + VxErrCorr*VxErrCorr * Vertices[i].Covariance[0][1];
252  K[1][2] = K[2][1] = par[4]*(std::fabs(par[2])-std::fabs(par[1])) - par[5]*par[3] + VxErrCorr*VxErrCorr * Vertices[i].Covariance[1][2];
253  K[0][2] = K[2][0] = par[5]*(std::fabs(par[2])-std::fabs(par[0])) - par[4]*par[3] + VxErrCorr*VxErrCorr * Vertices[i].Covariance[0][2];
254  }
255  else
256  {
257  K[0][0] = std::fabs(par[0]);
258  K[1][1] = std::fabs(par[1]);
259  K[2][2] = std::fabs(par[2]);
260  K[0][1] = K[1][0] = par[3];
261  K[1][2] = K[2][1] = par[4]*(std::fabs(par[2])-std::fabs(par[1])) - par[5]*par[3];
262  K[0][2] = K[2][0] = par[5]*(std::fabs(par[2])-std::fabs(par[0])) - par[4]*par[3];
263  }
264 
265  det = K[0][0]*(K[1][1]*K[2][2] - K[1][2]*K[1][2]) -
266  K[0][1]*(K[0][1]*K[2][2] - K[0][2]*K[1][2]) +
267  K[0][2]*(K[0][1]*K[1][2] - K[0][2]*K[1][1]);
268 
269  M[0][0] = (K[1][1]*K[2][2] - K[1][2]*K[1][2]) / det;
270  M[1][1] = (K[0][0]*K[2][2] - K[0][2]*K[0][2]) / det;
271  M[2][2] = (K[0][0]*K[1][1] - K[0][1]*K[0][1]) / det;
272  M[0][1] = M[1][0] = (K[0][2]*K[1][2] - K[0][1]*K[2][2]) / det;
273  M[1][2] = M[2][1] = (K[0][2]*K[0][1] - K[1][2]*K[0][0]) / det;
274  M[0][2] = M[2][0] = (K[0][1]*K[1][2] - K[0][2]*K[1][1]) / det;
275 
276  sumlog += double(DIM)*std::log(2.*pi) + std::log(std::fabs(det)) +
277  (M[0][0]*(Vertices[i].x-par[6])*(Vertices[i].x-par[6]) +
278  M[1][1]*(Vertices[i].y-par[7])*(Vertices[i].y-par[7]) +
279  M[2][2]*(Vertices[i].z-par[8])*(Vertices[i].z-par[8]) +
280  2.*M[0][1]*(Vertices[i].x-par[6])*(Vertices[i].y-par[7]) +
281  2.*M[1][2]*(Vertices[i].y-par[7])*(Vertices[i].z-par[8]) +
282  2.*M[0][2]*(Vertices[i].x-par[6])*(Vertices[i].z-par[8]));
283 
284  counterVx++;
285  }
286  }
287 
288  return sumlog;
289 }
290 
291 
292 int Vx3DHLTAnalyzer::MyFit (vector<double>* vals)
293 {
294  // ############################################
295  // # RETURN CODE: #
296  // # >0 == NO OK - fit status (MINUIT manual) #
297  // # 0 == OK #
298  // # -1 == NO OK - not finite edm #
299  // # -2 == NO OK - not enough "minNentries" #
300  // # -3 == NO OK - not finite errors #
301  // # -4 == NO OK - negative determinant #
302  // # -5 == NO OK - maxLumiIntegration reached #
303  // ############################################
304 
305  if ((vals != NULL) && (vals->size() == nParams*2))
306  {
307  double nSigmaXY = 10.;
308  double nSigmaZ = 10.;
309  double parDistanceXY = 1e-3; // Unit: [cm]
310  double parDistanceZ = 1e-2; // Unit: [cm]
311  double parDistanceddZ = 1e-3; // Unit: [rad]
312  double parDistanceCxy = 1e-5; // Unit: [cm^2]
313  double bestEdm;
314 
315  const unsigned int trials = 4;
316  double largerDist[trials] = {0.1, 5., 10., 100.};
317 
318  double covxz,covyz,det;
319  double deltaMean;
320  int bestMovementX = 1;
321  int bestMovementY = 1;
322  int bestMovementZ = 1;
323  int goodData;
324 
325  double edm;
326 
327  vector<double>::const_iterator it = vals->begin();
328 
329  ROOT::Math::Minimizer* Gauss3D = ROOT::Math::Factory::CreateMinimizer("Minuit2","Migrad");
330  Gauss3D->SetErrorDef(1.0);
331  if (internalDebug == true) Gauss3D->SetPrintLevel(3);
332  else Gauss3D->SetPrintLevel(0);
333 
334  ROOT::Math::Functor _Gauss3DFunc(this, &Vx3DHLTAnalyzer::Gauss3DFunc, nParams);
335  Gauss3D->SetFunction(_Gauss3DFunc);
336 
337  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\t@@@ START FITTING @@@" << endl;
338 
339  // @@@ Fit at X-deltaMean | X | X+deltaMean @@@
340  bestEdm = 1.;
341  for (int i = 0; i < 3; i++)
342  {
343  deltaMean = (double(i)-1.)*std::sqrt(*(it+0));
344  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tdeltaMean --> " << deltaMean << endl;
345 
346  Gauss3D->Clear();
347 
348  Gauss3D->SetVariable(0,"var x ", *(it+0), parDistanceXY * parDistanceXY);
349  Gauss3D->SetVariable(1,"var y ", *(it+1), parDistanceXY * parDistanceXY);
350  Gauss3D->SetVariable(2,"var z ", *(it+2), parDistanceZ * parDistanceZ);
351  Gauss3D->SetVariable(3,"cov xy", *(it+3), parDistanceCxy);
352  Gauss3D->SetVariable(4,"dydz ", *(it+4), parDistanceddZ);
353  Gauss3D->SetVariable(5,"dxdz ", *(it+5), parDistanceddZ);
354  Gauss3D->SetVariable(6,"mean x", *(it+6)+deltaMean, parDistanceXY);
355  Gauss3D->SetVariable(7,"mean y", *(it+7), parDistanceXY);
356  Gauss3D->SetVariable(8,"mean z", *(it+8), parDistanceZ);
357 
358  // Set the central positions of the centroid for vertex rejection
359  xPos = Gauss3D->X()[6];
360  yPos = Gauss3D->X()[7];
361  zPos = Gauss3D->X()[8];
362 
363  // Set dimensions of the centroid for vertex rejection
364  maxTransRadius = nSigmaXY * std::sqrt(std::fabs(Gauss3D->X()[0]) + std::fabs(Gauss3D->X()[1])) / 2.;
365  maxLongLength = nSigmaZ * std::sqrt(std::fabs(Gauss3D->X()[2]));
366 
367  Gauss3D->Minimize();
368  goodData = Gauss3D->Status();
369  edm = Gauss3D->Edm();
370 
371  if (counterVx < minNentries) goodData = -2;
372  else if (isNotFinite(edm) == true) { goodData = -1; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite edm !" << endl; }
373  else for (unsigned int j = 0; j < nParams; j++)
374  if (isNotFinite(Gauss3D->Errors()[j]) == true)
375  {
376  goodData = -3;
377  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite errors !" << endl;
378  break;
379  }
380  if (goodData == 0)
381  {
382  covyz = Gauss3D->X()[4]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[1])) - Gauss3D->X()[5]*Gauss3D->X()[3];
383  covxz = Gauss3D->X()[5]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[0])) - Gauss3D->X()[4]*Gauss3D->X()[3];
384 
385  det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1])*std::fabs(Gauss3D->X()[2]) - covyz*covyz) -
386  Gauss3D->X()[3] * (Gauss3D->X()[3]*std::fabs(Gauss3D->X()[2]) - covxz*covyz) +
387  covxz * (Gauss3D->X()[3]*covyz - covxz*std::fabs(Gauss3D->X()[1]));
388  if (det < 0.) { goodData = -4; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNegative determinant !" << endl; }
389  }
390 
391  if ((goodData == 0) && (std::fabs(edm) < bestEdm)) { bestEdm = edm; bestMovementX = i; }
392  }
393  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tFound bestMovementX --> " << bestMovementX << endl;
394 
395  // @@@ Fit at Y-deltaMean | Y | Y+deltaMean @@@
396  bestEdm = 1.;
397  for (int i = 0; i < 3; i++)
398  {
399  deltaMean = (double(i)-1.)*std::sqrt(*(it+1));
400  if (internalDebug == true)
401  {
402  cout << "[Vx3DHLTAnalyzer]::\tdeltaMean --> " << deltaMean << endl;
403  cout << "[Vx3DHLTAnalyzer]::\tdeltaMean X --> " << (double(bestMovementX)-1.)*std::sqrt(*(it+0)) << endl;
404  }
405 
406  Gauss3D->Clear();
407 
408  Gauss3D->SetVariable(0,"var x ", *(it+0), parDistanceXY * parDistanceXY);
409  Gauss3D->SetVariable(1,"var y ", *(it+1), parDistanceXY * parDistanceXY);
410  Gauss3D->SetVariable(2,"var z ", *(it+2), parDistanceZ * parDistanceZ);
411  Gauss3D->SetVariable(3,"cov xy", *(it+3), parDistanceCxy);
412  Gauss3D->SetVariable(4,"dydz ", *(it+4), parDistanceddZ);
413  Gauss3D->SetVariable(5,"dxdz ", *(it+5), parDistanceddZ);
414  Gauss3D->SetVariable(6,"mean x", *(it+6)+(double(bestMovementX)-1.)*std::sqrt(*(it+0)), parDistanceXY);
415  Gauss3D->SetVariable(7,"mean y", *(it+7)+deltaMean, parDistanceXY);
416  Gauss3D->SetVariable(8,"mean z", *(it+8), parDistanceZ);
417 
418  // Set the central positions of the centroid for vertex rejection
419  xPos = Gauss3D->X()[6];
420  yPos = Gauss3D->X()[7];
421  zPos = Gauss3D->X()[8];
422 
423  // Set dimensions of the centroid for vertex rejection
424  maxTransRadius = nSigmaXY * std::sqrt(std::fabs(Gauss3D->X()[0]) + std::fabs(Gauss3D->X()[1])) / 2.;
425  maxLongLength = nSigmaZ * std::sqrt(std::fabs(Gauss3D->X()[2]));
426 
427  Gauss3D->Minimize();
428  goodData = Gauss3D->Status();
429  edm = Gauss3D->Edm();
430 
431  if (counterVx < minNentries) goodData = -2;
432  else if (isNotFinite(edm) == true) { goodData = -1; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite edm !" << endl; }
433  else for (unsigned int j = 0; j < nParams; j++)
434  if (isNotFinite(Gauss3D->Errors()[j]) == true)
435  {
436  goodData = -3;
437  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite errors !" << endl;
438  break;
439  }
440  if (goodData == 0)
441  {
442  covyz = Gauss3D->X()[4]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[1])) - Gauss3D->X()[5]*Gauss3D->X()[3];
443  covxz = Gauss3D->X()[5]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[0])) - Gauss3D->X()[4]*Gauss3D->X()[3];
444 
445  det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1])*std::fabs(Gauss3D->X()[2]) - covyz*covyz) -
446  Gauss3D->X()[3] * (Gauss3D->X()[3]*std::fabs(Gauss3D->X()[2]) - covxz*covyz) +
447  covxz * (Gauss3D->X()[3]*covyz - covxz*std::fabs(Gauss3D->X()[1]));
448  if (det < 0.) { goodData = -4; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNegative determinant !" << endl; }
449  }
450 
451  if ((goodData == 0) && (std::fabs(edm) < bestEdm)) { bestEdm = edm; bestMovementY = i; }
452  }
453  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tFound bestMovementY --> " << bestMovementY << endl;
454 
455  // @@@ Fit at Z-deltaMean | Z | Z+deltaMean @@@
456  bestEdm = 1.;
457  for (int i = 0; i < 3; i++)
458  {
459  deltaMean = (double(i)-1.)*std::sqrt(*(it+2));
460  if (internalDebug == true)
461  {
462  cout << "[Vx3DHLTAnalyzer]::\tdeltaMean --> " << deltaMean << endl;
463  cout << "[Vx3DHLTAnalyzer]::\tdeltaMean X --> " << (double(bestMovementX)-1.)*std::sqrt(*(it+0)) << endl;
464  cout << "[Vx3DHLTAnalyzer]::\tdeltaMean Y --> " << (double(bestMovementY)-1.)*std::sqrt(*(it+1)) << endl;
465  }
466 
467  Gauss3D->Clear();
468 
469  Gauss3D->SetVariable(0,"var x ", *(it+0), parDistanceXY * parDistanceXY);
470  Gauss3D->SetVariable(1,"var y ", *(it+1), parDistanceXY * parDistanceXY);
471  Gauss3D->SetVariable(2,"var z ", *(it+2), parDistanceZ * parDistanceZ);
472  Gauss3D->SetVariable(3,"cov xy", *(it+3), parDistanceCxy);
473  Gauss3D->SetVariable(4,"dydz ", *(it+4), parDistanceddZ);
474  Gauss3D->SetVariable(5,"dxdz ", *(it+5), parDistanceddZ);
475  Gauss3D->SetVariable(6,"mean x", *(it+6)+(double(bestMovementX)-1.)*std::sqrt(*(it+0)), parDistanceXY);
476  Gauss3D->SetVariable(7,"mean y", *(it+7)+(double(bestMovementY)-1.)*std::sqrt(*(it+1)), parDistanceXY);
477  Gauss3D->SetVariable(8,"mean z", *(it+8)+deltaMean, parDistanceZ);
478 
479  // Set the central positions of the centroid for vertex rejection
480  xPos = Gauss3D->X()[6];
481  yPos = Gauss3D->X()[7];
482  zPos = Gauss3D->X()[8];
483 
484  // Set dimensions of the centroid for vertex rejection
485  maxTransRadius = nSigmaXY * std::sqrt(std::fabs(Gauss3D->X()[0]) + std::fabs(Gauss3D->X()[1])) / 2.;
486  maxLongLength = nSigmaZ * std::sqrt(std::fabs(Gauss3D->X()[2]));
487 
488  Gauss3D->Minimize();
489  goodData = Gauss3D->Status();
490  edm = Gauss3D->Edm();
491 
492  if (counterVx < minNentries) goodData = -2;
493  else if (isNotFinite(edm) == true) { goodData = -1; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite edm !" << endl; }
494  else for (unsigned int j = 0; j < nParams; j++)
495  if (isNotFinite(Gauss3D->Errors()[j]) == true)
496  {
497  goodData = -3;
498  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite errors !" << endl;
499  break;
500  }
501  if (goodData == 0)
502  {
503  covyz = Gauss3D->X()[4]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[1])) - Gauss3D->X()[5]*Gauss3D->X()[3];
504  covxz = Gauss3D->X()[5]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[0])) - Gauss3D->X()[4]*Gauss3D->X()[3];
505 
506  det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1])*std::fabs(Gauss3D->X()[2]) - covyz*covyz) -
507  Gauss3D->X()[3] * (Gauss3D->X()[3]*std::fabs(Gauss3D->X()[2]) - covxz*covyz) +
508  covxz * (Gauss3D->X()[3]*covyz - covxz*std::fabs(Gauss3D->X()[1]));
509  if (det < 0.) { goodData = -4; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNegative determinant !" << endl; }
510  }
511 
512  if ((goodData == 0) && (std::fabs(edm) < bestEdm)) { bestEdm = edm; bestMovementZ = i; }
513  }
514  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tFound bestMovementZ --> " << bestMovementZ << endl;
515 
516  Gauss3D->Clear();
517 
518  // @@@ FINAL FIT @@@
519  Gauss3D->SetVariable(0,"var x ", *(it+0), parDistanceXY * parDistanceXY);
520  Gauss3D->SetVariable(1,"var y ", *(it+1), parDistanceXY * parDistanceXY);
521  Gauss3D->SetVariable(2,"var z ", *(it+2), parDistanceZ * parDistanceZ);
522  Gauss3D->SetVariable(3,"cov xy", *(it+3), parDistanceCxy);
523  Gauss3D->SetVariable(4,"dydz ", *(it+4), parDistanceddZ);
524  Gauss3D->SetVariable(5,"dxdz ", *(it+5), parDistanceddZ);
525  Gauss3D->SetVariable(6,"mean x", *(it+6)+(double(bestMovementX)-1.)*std::sqrt(*(it+0)), parDistanceXY);
526  Gauss3D->SetVariable(7,"mean y", *(it+7)+(double(bestMovementY)-1.)*std::sqrt(*(it+1)), parDistanceXY);
527  Gauss3D->SetVariable(8,"mean z", *(it+8)+(double(bestMovementZ)-1.)*std::sqrt(*(it+2)), parDistanceZ);
528 
529  // Set the central positions of the centroid for vertex rejection
530  xPos = Gauss3D->X()[6];
531  yPos = Gauss3D->X()[7];
532  zPos = Gauss3D->X()[8];
533 
534  // Set dimensions of the centroid for vertex rejection
535  maxTransRadius = nSigmaXY * std::sqrt(std::fabs(Gauss3D->X()[0]) + std::fabs(Gauss3D->X()[1])) / 2.;
536  maxLongLength = nSigmaZ * std::sqrt(std::fabs(Gauss3D->X()[2]));
537 
538  Gauss3D->Minimize();
539  goodData = Gauss3D->Status();
540  edm = Gauss3D->Edm();
541 
542  if (counterVx < minNentries) goodData = -2;
543  else if (isNotFinite(edm) == true) { goodData = -1; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite edm !" << endl; }
544  else for (unsigned int j = 0; j < nParams; j++)
545  if (isNotFinite(Gauss3D->Errors()[j]) == true)
546  {
547  goodData = -3;
548  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite errors !" << endl;
549  break;
550  }
551  if (goodData == 0)
552  {
553  covyz = Gauss3D->X()[4]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[1])) - Gauss3D->X()[5]*Gauss3D->X()[3];
554  covxz = Gauss3D->X()[5]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[0])) - Gauss3D->X()[4]*Gauss3D->X()[3];
555 
556  det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1])*std::fabs(Gauss3D->X()[2]) - covyz*covyz) -
557  Gauss3D->X()[3] * (Gauss3D->X()[3]*std::fabs(Gauss3D->X()[2]) - covxz*covyz) +
558  covxz * (Gauss3D->X()[3]*covyz - covxz*std::fabs(Gauss3D->X()[1]));
559  if (det < 0.) { goodData = -4; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNegative determinant !" << endl; }
560  }
561 
562  // @@@ FIT WITH DIFFERENT PARAMETER DISTANCES @@@
563  for (unsigned int i = 0; i < trials; i++)
564  {
565  if ((goodData != 0) && (goodData != -2))
566  {
567  Gauss3D->Clear();
568 
569  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tFIT WITH DIFFERENT PARAMETER DISTANCES - STEP " << i+1 << endl;
570 
571  Gauss3D->SetVariable(0,"var x ", *(it+0), parDistanceXY * parDistanceXY * largerDist[i]);
572  Gauss3D->SetVariable(1,"var y ", *(it+1), parDistanceXY * parDistanceXY * largerDist[i]);
573  Gauss3D->SetVariable(2,"var z ", *(it+2), parDistanceZ * parDistanceZ * largerDist[i]);
574  Gauss3D->SetVariable(3,"cov xy", *(it+3), parDistanceCxy * largerDist[i]);
575  Gauss3D->SetVariable(4,"dydz ", *(it+4), parDistanceddZ * largerDist[i]);
576  Gauss3D->SetVariable(5,"dxdz ", *(it+5), parDistanceddZ * largerDist[i]);
577  Gauss3D->SetVariable(6,"mean x", *(it+6)+(double(bestMovementX)-1.)*std::sqrt(*(it+0)), parDistanceXY * largerDist[i]);
578  Gauss3D->SetVariable(7,"mean y", *(it+7)+(double(bestMovementY)-1.)*std::sqrt(*(it+1)), parDistanceXY * largerDist[i]);
579  Gauss3D->SetVariable(8,"mean z", *(it+8)+(double(bestMovementZ)-1.)*std::sqrt(*(it+2)), parDistanceZ * largerDist[i]);
580 
581  // Set the central positions of the centroid for vertex rejection
582  xPos = Gauss3D->X()[6];
583  yPos = Gauss3D->X()[7];
584  zPos = Gauss3D->X()[8];
585 
586  // Set dimensions of the centroid for vertex rejection
587  maxTransRadius = nSigmaXY * std::sqrt(std::fabs(Gauss3D->X()[0]) + std::fabs(Gauss3D->X()[1])) / 2.;
588  maxLongLength = nSigmaZ * std::sqrt(std::fabs(Gauss3D->X()[2]));
589 
590  Gauss3D->Minimize();
591  goodData = Gauss3D->Status();
592  edm = Gauss3D->Edm();
593 
594  if (counterVx < minNentries) goodData = -2;
595  else if (isNotFinite(edm) == true) { goodData = -1; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite edm !" << endl; }
596  else for (unsigned int j = 0; j < nParams; j++)
597  if (isNotFinite(Gauss3D->Errors()[j]) == true)
598  {
599  goodData = -3;
600  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNot finite errors !" << endl;
601  break;
602  }
603  if (goodData == 0)
604  {
605  covyz = Gauss3D->X()[4]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[1])) - Gauss3D->X()[5]*Gauss3D->X()[3];
606  covxz = Gauss3D->X()[5]*(std::fabs(Gauss3D->X()[2])-std::fabs(Gauss3D->X()[0])) - Gauss3D->X()[4]*Gauss3D->X()[3];
607 
608  det = std::fabs(Gauss3D->X()[0]) * (std::fabs(Gauss3D->X()[1])*std::fabs(Gauss3D->X()[2]) - covyz*covyz) -
609  Gauss3D->X()[3] * (Gauss3D->X()[3]*std::fabs(Gauss3D->X()[2]) - covxz*covyz) +
610  covxz * (Gauss3D->X()[3]*covyz - covxz*std::fabs(Gauss3D->X()[1]));
611  if (det < 0.) { goodData = -4; if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tNegative determinant !" << endl; }
612  }
613  } else break;
614  }
615 
616  if (goodData == 0)
617  for (unsigned int i = 0; i < nParams; i++)
618  {
619  vals->operator[](i) = Gauss3D->X()[i];
620  vals->operator[](i+nParams) = Gauss3D->Errors()[i];
621  }
622 
623  delete Gauss3D;
624  return goodData;
625  }
626 
627  return -1;
628 }
629 
630 
631 void Vx3DHLTAnalyzer::reset (string ResetType)
632 {
633  if ((debugMode == true) && (outputDebugFile.is_open() == true))
634  {
635  outputDebugFile << "Runnumber " << runNumber << endl;
636  outputDebugFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
637  outputDebugFile << "BeginLumiRange " << beginLumiOfFit << endl;
638  outputDebugFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
639  outputDebugFile << "EndLumiRange " << endLumiOfFit << endl;
640  outputDebugFile << "LumiCounter " << lumiCounter << endl;
641  outputDebugFile << "LastLumiOfFit " << lastLumiOfFit << endl;
642  }
643 
644 
645  if (ResetType.compare("scratch") == 0)
646  {
647  runNumber = 0;
648  numberGoodFits = 0;
649  numberFits = 0;
650  lastLumiOfFit = 0;
651 
652  Vx_X->Reset();
653  Vx_Y->Reset();
654  Vx_Z->Reset();
655 
656  Vx_ZX->Reset();
657  Vx_ZY->Reset();
658  Vx_XY->Reset();
659 
660  Vx_X_Cum->Reset();
661  Vx_Y_Cum->Reset();
662  Vx_Z_Cum->Reset();
663 
664  Vx_ZX_Cum->Reset();
665  Vx_ZY_Cum->Reset();
666  Vx_XY_Cum->Reset();
667 
668  mXlumi->Reset();
669  mYlumi->Reset();
670  mZlumi->Reset();
671 
672  sXlumi->Reset();
673  sYlumi->Reset();
674  sZlumi->Reset();
675 
676  dxdzlumi->Reset();
677  dydzlumi->Reset();
678 
679  hitCounter->Reset();
680  goodVxCounter->Reset();
681  statusCounter->Reset();
682  fitResults->Reset();
683 
684  reportSummary->Fill(-1);
685  reportSummaryMap->getTH1()->SetBinContent(1, 1, -1);
686 
687  Vertices.clear();
688 
689  lumiCounter = 0;
690  totalHits = 0;
691  beginTimeOfFit = 0;
692  endTimeOfFit = 0;
693  beginLumiOfFit = 0;
694  endLumiOfFit = 0;
695 
696  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tReset issued: scratch" << endl;
697  if ((debugMode == true) && (outputDebugFile.is_open() == true)) outputDebugFile << "Reset -scratch- issued\n" << endl;
698  }
699  else if (ResetType.compare("whole") == 0)
700  {
701  Vx_X->Reset();
702  Vx_Y->Reset();
703  Vx_Z->Reset();
704 
705  Vx_ZX->Reset();
706  Vx_ZY->Reset();
707  Vx_XY->Reset();
708 
709  Vertices.clear();
710 
711  lumiCounter = 0;
712  totalHits = 0;
713  beginTimeOfFit = 0;
714  endTimeOfFit = 0;
715  beginLumiOfFit = 0;
716  endLumiOfFit = 0;
717 
718  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tReset issued: whole" << endl;
719  if ((debugMode == true) && (outputDebugFile.is_open() == true)) outputDebugFile << "Reset -whole- issued\n" << endl;
720  }
721  else if (ResetType.compare("hitCounter") == 0)
722  {
723  totalHits = 0;
724 
725  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tReset issued: hitCounter" << endl;
726  if ((debugMode == true) && (outputDebugFile.is_open() == true)) outputDebugFile << "Reset -hitCounter- issued\n" << endl;
727  }
728 }
729 
730 
731 void Vx3DHLTAnalyzer::writeToFile (vector<double>* vals,
732  TimeValue_t BeginTimeOfFit,
733  TimeValue_t EndTimeOfFit,
734  unsigned int BeginLumiOfFit,
735  unsigned int EndLumiOfFit,
736  int dataType)
737 {
738  stringstream BufferString;
739  BufferString.precision(5);
740 
741  outputFile.open(fileName.c_str(), ios::out);
742 
743  if ((outputFile.is_open() == true) && (vals != NULL) && (vals->size() == (nParams-1)*2))
744  {
745  vector<double>::const_iterator it = vals->begin();
746 
747  outputFile << "Runnumber " << runNumber << endl;
748  outputFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
749  outputFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
750  outputFile << "LumiRange " << beginLumiOfFit << " - " << endLumiOfFit << endl;
751  outputFile << "Type " << dataType << endl;
752  // 3D Vertexing with Pixel Tracks:
753  // Good data = Type 3
754  // Bad data = Type -1
755 
756  BufferString << *(it+0);
757  outputFile << "X0 " << BufferString.str().c_str() << endl;
758  BufferString.str("");
759 
760  BufferString << *(it+1);
761  outputFile << "Y0 " << BufferString.str().c_str() << endl;
762  BufferString.str("");
763 
764  BufferString << *(it+2);
765  outputFile << "Z0 " << BufferString.str().c_str() << endl;
766  BufferString.str("");
767 
768  BufferString << *(it+5);
769  outputFile << "sigmaZ0 " << BufferString.str().c_str() << endl;
770  BufferString.str("");
771 
772  BufferString << *(it+6);
773  outputFile << "dxdz " << BufferString.str().c_str() << endl;
774  BufferString.str("");
775 
776  BufferString << *(it+7);
777  outputFile << "dydz " << BufferString.str().c_str() << endl;
778  BufferString.str("");
779 
780  BufferString << *(it+3);
781  outputFile << "BeamWidthX " << BufferString.str().c_str() << endl;
782  BufferString.str("");
783 
784  BufferString << *(it+4);
785  outputFile << "BeamWidthY " << BufferString.str().c_str() << endl;
786  BufferString.str("");
787 
788  outputFile << "Cov(0,j) " << *(it+8) << " 0 0 0 0 0 0" << endl;
789  outputFile << "Cov(1,j) 0 " << *(it+9) << " 0 0 0 0 0" << endl;
790  outputFile << "Cov(2,j) 0 0 " << *(it+10) << " 0 0 0 0" << endl;
791  outputFile << "Cov(3,j) 0 0 0 " << *(it+13) << " 0 0 0" << endl;
792  outputFile << "Cov(4,j) 0 0 0 0 " << *(it+14) << " 0 0" << endl;
793  outputFile << "Cov(5,j) 0 0 0 0 0 " << *(it+15) << " 0" << endl;
794  outputFile << "Cov(6,j) 0 0 0 0 0 0 " << ((*(it+11)) + (*(it+12)) + 2.*std::sqrt((*(it+11))*(*(it+12)))) / 4. << endl;
795 
796  outputFile << "EmittanceX 0" << endl;
797  outputFile << "EmittanceY 0" << endl;
798  outputFile << "BetaStar 0" << endl;
799  outputFile << "events 0" << endl;
800  outputFile << "meanPV 0" << endl;
801  outputFile << "meanErrPV 0" << endl;
802  outputFile << "rmsPV 0" << endl;
803  outputFile << "rmsErrPV 0" << endl;
804  outputFile << "maxPV 0" << endl;
805  outputFile << "nPV " << counterVx << endl;
806  }
807  outputFile.close();
808 
809  if ((debugMode == true) && (outputDebugFile.is_open() == true) && (vals != NULL) && (vals->size() == (nParams-1)*2))
810  {
811  vector<double>::const_iterator it = vals->begin();
812 
813  outputDebugFile << "Runnumber " << runNumber << endl;
814  outputDebugFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
815  outputDebugFile << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
816  outputDebugFile << "LumiRange " << beginLumiOfFit << " - " << endLumiOfFit << endl;
817  outputDebugFile << "Type " << dataType << endl;
818  // 3D Vertexing with Pixel Tracks:
819  // Good data = Type 3
820  // Bad data = Type -1
821 
822  BufferString << *(it+0);
823  outputDebugFile << "X0 " << BufferString.str().c_str() << endl;
824  BufferString.str("");
825 
826  BufferString << *(it+1);
827  outputDebugFile << "Y0 " << BufferString.str().c_str() << endl;
828  BufferString.str("");
829 
830  BufferString << *(it+2);
831  outputDebugFile << "Z0 " << BufferString.str().c_str() << endl;
832  BufferString.str("");
833 
834  BufferString << *(it+5);
835  outputDebugFile << "sigmaZ0 " << BufferString.str().c_str() << endl;
836  BufferString.str("");
837 
838  BufferString << *(it+6);
839  outputDebugFile << "dxdz " << BufferString.str().c_str() << endl;
840  BufferString.str("");
841 
842  BufferString << *(it+7);
843  outputDebugFile << "dydz " << BufferString.str().c_str() << endl;
844  BufferString.str("");
845 
846  BufferString << *(it+3);
847  outputDebugFile << "BeamWidthX " << BufferString.str().c_str() << endl;
848  BufferString.str("");
849 
850  BufferString << *(it+4);
851  outputDebugFile << "BeamWidthY " << BufferString.str().c_str() << endl;
852  BufferString.str("");
853 
854  outputDebugFile << "Cov(0,j) " << *(it+8) << " 0 0 0 0 0 0" << endl;
855  outputDebugFile << "Cov(1,j) 0 " << *(it+9) << " 0 0 0 0 0" << endl;
856  outputDebugFile << "Cov(2,j) 0 0 " << *(it+10) << " 0 0 0 0" << endl;
857  outputDebugFile << "Cov(3,j) 0 0 0 " << *(it+13) << " 0 0 0" << endl;
858  outputDebugFile << "Cov(4,j) 0 0 0 0 " << *(it+14) << " 0 0" << endl;
859  outputDebugFile << "Cov(5,j) 0 0 0 0 0 " << *(it+15) << " 0" << endl;
860  outputDebugFile << "Cov(6,j) 0 0 0 0 0 0 " << ((*(it+11)) + (*(it+12)) + 2.*std::sqrt((*(it+11))*(*(it+12)))) / 4. << endl;
861 
862  outputDebugFile << "EmittanceX 0" << endl;
863  outputDebugFile << "EmittanceY 0" << endl;
864  outputDebugFile << "BetaStar 0" << endl;
865  outputDebugFile << "events 0" << endl;
866  outputDebugFile << "meanPV 0" << endl;
867  outputDebugFile << "meanErrPV 0" << endl;
868  outputDebugFile << "rmsPV 0" << endl;
869  outputDebugFile << "rmsErrPV 0" << endl;
870  outputDebugFile << "maxPV 0" << endl;
871  outputDebugFile << "nPV " << counterVx << endl;
872 
873  outputDebugFile << "\n" << "Used vertices: " << counterVx << "\n" << endl;
874  }
875 }
876 
877 
878 void Vx3DHLTAnalyzer::printFitParams (const vector<double>& fitResults)
879 {
880  cout << "var x --> " << fitResults[0] << " +/- " << fitResults[0+nParams] << endl;
881  cout << "var y --> " << fitResults[1] << " +/- " << fitResults[1+nParams] << endl;
882  cout << "var z --> " << fitResults[2] << " +/- " << fitResults[2+nParams] << endl;
883  cout << "cov xy --> " << fitResults[3] << " +/- " << fitResults[3+nParams] << endl;
884  cout << "dydz --> " << fitResults[4] << " +/- " << fitResults[4+nParams] << endl;
885  cout << "dxdz --> " << fitResults[5] << " +/- " << fitResults[5+nParams] << endl;
886  cout << "mean x --> " << fitResults[6] << " +/- " << fitResults[6+nParams] << endl;
887  cout << "mean y --> " << fitResults[7] << " +/- " << fitResults[7+nParams] << endl;
888  cout << "mean z --> " << fitResults[8] << " +/- " << fitResults[8+nParams] << endl;
889 }
890 
891 
892 void Vx3DHLTAnalyzer::beginLuminosityBlock (const LuminosityBlock& lumiBlock, const EventSetup& iSetup)
893 {
894  // @@@ If statement to avoid problems with non-sequential lumisections @@@
895  if ((lumiCounter == 0) && (lumiBlock.luminosityBlock() > lastLumiOfFit))
896  {
897  beginTimeOfFit = lumiBlock.beginTime().value();
898  beginLumiOfFit = lumiBlock.luminosityBlock();
899  lumiCounter++;
900  }
901  else if ((lumiCounter != 0) && (lumiBlock.luminosityBlock() >= (beginLumiOfFit+lumiCounter))) lumiCounter++;
902  else reset("scratch");
903 }
904 
905 
906 void Vx3DHLTAnalyzer::endLuminosityBlock (const LuminosityBlock& lumiBlock, const EventSetup& iSetup)
907 {
908  stringstream histTitle;
909  int goodData;
910 
911  if ((nLumiFit != 0) && (lumiCounter%nLumiFit == 0) && (beginTimeOfFit != 0) && (runNumber != 0))
912  {
913  endTimeOfFit = lumiBlock.endTime().value();
914  endLumiOfFit = lumiBlock.luminosityBlock();
915  lastLumiOfFit = endLumiOfFit;
916  vector<double> vals;
917 
918  hitCounter->getTH1()->SetBinContent(lastLumiOfFit, (double)totalHits);
919  hitCounter->getTH1()->SetBinError(lastLumiOfFit, (totalHits != 0 ? 1. : 0.)); // It's not sqrt(n) because we want to weight all entries in the same way for the fit
920 
921  if (dataFromFit == true)
922  {
923  vector<double> fitResults;
924 
925  fitResults.push_back(Vx_X->getTH1()->GetRMS()*Vx_X->getTH1()->GetRMS());
926  fitResults.push_back(Vx_Y->getTH1()->GetRMS()*Vx_Y->getTH1()->GetRMS());
927  fitResults.push_back(Vx_Z->getTH1()->GetRMS()*Vx_Z->getTH1()->GetRMS());
928  fitResults.push_back(0.0);
929  fitResults.push_back(0.0);
930  fitResults.push_back(0.0);
931  fitResults.push_back(Vx_X->getTH1()->GetMean());
932  fitResults.push_back(Vx_Y->getTH1()->GetMean());
933  fitResults.push_back(Vx_Z->getTH1()->GetMean());
934  for (unsigned int i = 0; i < nParams; i++) fitResults.push_back(0.0);
935 
936  if (internalDebug == true)
937  {
938  cout << "[Vx3DHLTAnalyzer]::\t@@@ Beam Spot parameters - prefit @@@" << endl;
939 
940  printFitParams(fitResults);
941 
942  cout << "Runnumber " << runNumber << endl;
943  cout << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
944  cout << "EndTimeOfFit " << formatTime(endTimeOfFit >> 32) << " " << (endTimeOfFit >> 32) << endl;
945  cout << "LumiRange " << beginLumiOfFit << " - " << endLumiOfFit << endl;
946  }
947 
948  goodData = MyFit(&fitResults);
949 
950  if (internalDebug == true)
951  {
952  cout << "[Vx3DHLTAnalyzer]::\t@@@ Beam Spot parameters - postfit @@@" << endl;
953 
954  printFitParams(fitResults);
955 
956  cout << "goodData --> " << goodData << endl;
957  cout << "Used vertices --> " << counterVx << endl;
958  }
959 
960  if (goodData == 0)
961  {
962  vals.push_back(fitResults[6]);
963  vals.push_back(fitResults[7]);
964  vals.push_back(fitResults[8]);
965  vals.push_back(std::sqrt(std::fabs(fitResults[0])));
966  vals.push_back(std::sqrt(std::fabs(fitResults[1])));
967  vals.push_back(std::sqrt(std::fabs(fitResults[2])));
968  vals.push_back(fitResults[5]);
969  vals.push_back(fitResults[4]);
970 
971  vals.push_back(std::pow(fitResults[6+nParams],2.));
972  vals.push_back(std::pow(fitResults[7+nParams],2.));
973  vals.push_back(std::pow(fitResults[8+nParams],2.));
974  vals.push_back(std::pow(std::fabs(fitResults[0+nParams]) / (2.*std::sqrt(std::fabs(fitResults[0]))),2.));
975  vals.push_back(std::pow(std::fabs(fitResults[1+nParams]) / (2.*std::sqrt(std::fabs(fitResults[1]))),2.));
976  vals.push_back(std::pow(std::fabs(fitResults[2+nParams]) / (2.*std::sqrt(std::fabs(fitResults[2]))),2.));
977  vals.push_back(std::pow(fitResults[5+nParams],2.));
978  vals.push_back(std::pow(fitResults[4+nParams],2.));
979  }
980  else for (unsigned int i = 0; i < (nParams-1)*2; i++) vals.push_back(0.0);
981 
982  fitResults.clear();
983  }
984  else
985  {
986  counterVx = Vx_X->getTH1F()->GetEntries();
987 
988  if (Vx_X->getTH1F()->GetEntries() >= minNentries)
989  {
990  goodData = 0;
991 
992  vals.push_back(Vx_X->getTH1F()->GetMean());
993  vals.push_back(Vx_Y->getTH1F()->GetMean());
994  vals.push_back(Vx_Z->getTH1F()->GetMean());
995  vals.push_back(Vx_X->getTH1F()->GetRMS());
996  vals.push_back(Vx_Y->getTH1F()->GetRMS());
997  vals.push_back(Vx_Z->getTH1F()->GetRMS());
998  vals.push_back(0.0);
999  vals.push_back(0.0);
1000 
1001  vals.push_back(std::pow(Vx_X->getTH1F()->GetMeanError(),2.));
1002  vals.push_back(std::pow(Vx_Y->getTH1F()->GetMeanError(),2.));
1003  vals.push_back(std::pow(Vx_Z->getTH1F()->GetMeanError(),2.));
1004  vals.push_back(std::pow(Vx_X->getTH1F()->GetRMSError(),2.));
1005  vals.push_back(std::pow(Vx_Y->getTH1F()->GetRMSError(),2.));
1006  vals.push_back(std::pow(Vx_Z->getTH1F()->GetRMSError(),2.));
1007  vals.push_back(0.0);
1008  vals.push_back(0.0);
1009  }
1010  else
1011  {
1012  goodData = -2;
1013  for (unsigned int i = 0; i < (nParams-1)*2; i++) vals.push_back(0.0);
1014  }
1015  }
1016 
1017  // vals[0] = X0
1018  // vals[1] = Y0
1019  // vals[2] = Z0
1020  // vals[3] = sigmaX0
1021  // vals[4] = sigmaY0
1022  // vals[5] = sigmaZ0
1023  // vals[6] = dxdz
1024  // vals[7] = dydz
1025 
1026  // vals[8] = err^2 X0
1027  // vals[9] = err^2 Y0
1028  // vals[10] = err^2 Z0
1029  // vals[11] = err^2 sigmaX0
1030  // vals[12] = err^2 sigmaY0
1031  // vals[13] = err^2 sigmaZ0
1032  // vals[14] = err^2 dxdz
1033  // vals[15] = err^2 dydz
1034 
1035  numberFits++;
1036  writeToFile(&vals, beginTimeOfFit, endTimeOfFit, beginLumiOfFit, endLumiOfFit, 3);
1037  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tUsed vertices: " << counterVx << endl;
1038 
1039  statusCounter->getTH1()->SetBinContent(lastLumiOfFit, (double)goodData);
1040  statusCounter->getTH1()->SetBinError(lastLumiOfFit, 1e-3);
1041 
1042  if (goodData == 0)
1043  {
1044  numberGoodFits++;
1045 
1046  histTitle << "Ongoing: fitted lumis " << beginLumiOfFit << " - " << endLumiOfFit;
1047  reset("whole");
1048  }
1049  else
1050  {
1051  if (goodData == -2) histTitle << "Ongoing: not enough evts (" << lumiCounter << " - " << maxLumiIntegration << " lumis)";
1052  else histTitle << "Ongoing: temporary problems (" << lumiCounter << " - " << maxLumiIntegration << " lumis)";
1053 
1054  if (lumiCounter >= maxLumiIntegration)
1055  {
1056  statusCounter->getTH1()->SetBinContent(lastLumiOfFit, -5);
1057  statusCounter->getTH1()->SetBinError(lastLumiOfFit, 1e-3);
1058  reset("whole");
1059  }
1060  else reset("hitCounter");
1061  }
1062 
1063  reportSummary->Fill((numberFits != 0 ? ((double)numberGoodFits) / ((double)numberFits) : -1));
1064  reportSummaryMap->getTH1()->SetBinContent(1, 1, (numberFits != 0 ? ((double)numberGoodFits) / ((double)numberFits) : -1));
1065 
1066  fitResults->setAxisTitle(histTitle.str().c_str(), 1);
1067 
1068  fitResults->setBinContent(1, 9, vals[0]);
1069  fitResults->setBinContent(1, 8, vals[1]);
1070  fitResults->setBinContent(1, 7, vals[2]);
1071  fitResults->setBinContent(1, 6, vals[3]);
1072  fitResults->setBinContent(1, 5, vals[4]);
1073  fitResults->setBinContent(1, 4, vals[5]);
1074  fitResults->setBinContent(1, 3, vals[6]);
1075  fitResults->setBinContent(1, 2, vals[7]);
1076  fitResults->setBinContent(1, 1, counterVx);
1077 
1078  fitResults->setBinContent(2, 9, std::sqrt(vals[8]));
1079  fitResults->setBinContent(2, 8, std::sqrt(vals[9]));
1080  fitResults->setBinContent(2, 7, std::sqrt(vals[10]));
1081  fitResults->setBinContent(2, 6, std::sqrt(vals[11]));
1082  fitResults->setBinContent(2, 5, std::sqrt(vals[12]));
1083  fitResults->setBinContent(2, 4, std::sqrt(vals[13]));
1084  fitResults->setBinContent(2, 3, std::sqrt(vals[14]));
1085  fitResults->setBinContent(2, 2, std::sqrt(vals[15]));
1086  fitResults->setBinContent(2, 1, std::sqrt(counterVx));
1087 
1088  // Linear fit to the historical plots
1089  TF1* myLinFit = new TF1("myLinFit", "[0] + [1]*x", mXlumi->getTH1()->GetXaxis()->GetXmin(), mXlumi->getTH1()->GetXaxis()->GetXmax());
1090  myLinFit->SetLineColor(2);
1091  myLinFit->SetLineWidth(2);
1092  myLinFit->SetParName(0,"Inter.");
1093  myLinFit->SetParName(1,"Slope");
1094 
1095  mXlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[0]);
1096  mXlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[8]));
1097  myLinFit->SetParameter(0, mXlumi->getTH1()->GetMean(2));
1098  myLinFit->SetParameter(1, 0.0);
1099  mXlumi->getTH1()->Fit(myLinFit,"QR");
1100 
1101  mYlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[1]);
1102  mYlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[9]));
1103  myLinFit->SetParameter(0, mYlumi->getTH1()->GetMean(2));
1104  myLinFit->SetParameter(1, 0.0);
1105  mYlumi->getTH1()->Fit(myLinFit,"QR");
1106 
1107  mZlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[2]);
1108  mZlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[10]));
1109  myLinFit->SetParameter(0, mZlumi->getTH1()->GetMean(2));
1110  myLinFit->SetParameter(1, 0.0);
1111  mZlumi->getTH1()->Fit(myLinFit,"QR");
1112 
1113  sXlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[3]);
1114  sXlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[11]));
1115  myLinFit->SetParameter(0, sXlumi->getTH1()->GetMean(2));
1116  myLinFit->SetParameter(1, 0.0);
1117  sXlumi->getTH1()->Fit(myLinFit,"QR");
1118 
1119  sYlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[4]);
1120  sYlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[12]));
1121  myLinFit->SetParameter(0, sYlumi->getTH1()->GetMean(2));
1122  myLinFit->SetParameter(1, 0.0);
1123  sYlumi->getTH1()->Fit(myLinFit,"QR");
1124 
1125  sZlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[5]);
1126  sZlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[13]));
1127  myLinFit->SetParameter(0, sZlumi->getTH1()->GetMean(2));
1128  myLinFit->SetParameter(1, 0.0);
1129  sZlumi->getTH1()->Fit(myLinFit,"QR");
1130 
1131  dxdzlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[6]);
1132  dxdzlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[14]));
1133  myLinFit->SetParameter(0, dxdzlumi->getTH1()->GetMean(2));
1134  myLinFit->SetParameter(1, 0.0);
1135  dxdzlumi->getTH1()->Fit(myLinFit,"QR");
1136 
1137  dydzlumi->getTH1()->SetBinContent(lastLumiOfFit, vals[7]);
1138  dydzlumi->getTH1()->SetBinError(lastLumiOfFit, std::sqrt(vals[15]));
1139  myLinFit->SetParameter(0, dydzlumi->getTH1()->GetMean(2));
1140  myLinFit->SetParameter(1, 0.0);
1141  dydzlumi->getTH1()->Fit(myLinFit,"QR");
1142 
1143  myLinFit->SetParameter(0, hitCounter->getTH1()->GetMean(2));
1144  myLinFit->SetParameter(1, 0.0);
1145  hitCounter->getTH1()->Fit(myLinFit,"QR");
1146 
1147  goodVxCounter->getTH1()->SetBinContent(lastLumiOfFit, (double)counterVx);
1148  goodVxCounter->getTH1()->SetBinError(lastLumiOfFit, (counterVx != 0 ? 1. : 0.)); // It's not sqrt(n) because we want to weight all entries in the same way for the fit
1149  myLinFit->SetParameter(0, goodVxCounter->getTH1()->GetMean(2));
1150  myLinFit->SetParameter(1, 0.0);
1151  goodVxCounter->getTH1()->Fit(myLinFit,"QR");
1152 
1153  delete myLinFit;
1154  vals.clear();
1155  }
1156  else if ((nLumiFit != 0) && (lumiCounter%nLumiFit != 0) && (beginTimeOfFit != 0) && (runNumber != 0))
1157  {
1158  histTitle << "Ongoing: accumulating evts (" << lumiCounter%nLumiFit << " - " << nLumiFit << " in " << lumiCounter << " - " << maxLumiIntegration << " lumis)";
1159  fitResults->setAxisTitle(histTitle.str().c_str(), 1);
1160  if ((debugMode == true) && (outputDebugFile.is_open() == true))
1161  {
1162  outputDebugFile << "\n" << "Runnumber " << runNumber << endl;
1163  outputDebugFile << "BeginTimeOfFit " << formatTime(beginTimeOfFit >> 32) << " " << (beginTimeOfFit >> 32) << endl;
1164  outputDebugFile << "BeginLumiRange " << beginLumiOfFit << endl;
1165  outputDebugFile << histTitle.str().c_str() << "\n" << endl;
1166  }
1167  }
1168  else if ((nLumiFit == 0) || (beginTimeOfFit == 0) || (runNumber == 0))
1169  {
1170  histTitle << "Ongoing: no ongoing fits";
1171  fitResults->setAxisTitle(histTitle.str().c_str(), 1);
1172  if ((debugMode == true) && (outputDebugFile.is_open() == true)) outputDebugFile << histTitle.str().c_str() << "\n" << endl;
1173 
1174  endLumiOfFit = lumiBlock.luminosityBlock();
1175 
1176  hitCounter->getTH1()->SetBinContent(endLumiOfFit, (double)totalHits);
1177  hitCounter->getTH1()->SetBinError(endLumiOfFit, std::sqrt((double)totalHits));
1178 
1179  reset("whole");
1180  }
1181 
1182  if (internalDebug == true) cout << "[Vx3DHLTAnalyzer]::\tHistogram title: " << histTitle.str() << endl;
1183 }
1184 
1185 
1186 void Vx3DHLTAnalyzer::bookHistograms(DQMStore::IBooker & ibooker, Run const & iRun, EventSetup const & /* iSetup */)
1187 {
1188  ibooker.setCurrentFolder("BeamPixel");
1189 
1190  Vx_X = ibooker.book1D("F - vertex x", "Primary Vertex X Distribution", int(rint(xRange/xStep)), -xRange/2., xRange/2.);
1191  Vx_Y = ibooker.book1D("F - vertex y", "Primary Vertex Y Distribution", int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1192  Vx_Z = ibooker.book1D("F - vertex z", "Primary Vertex Z Distribution", int(rint(zRange/zStep)), -zRange/2., zRange/2.);
1193  Vx_X->setAxisTitle("Primary Vertices X [cm]",1);
1194  Vx_X->setAxisTitle("Entries [#]",2);
1195  Vx_Y->setAxisTitle("Primary Vertices Y [cm]",1);
1196  Vx_Y->setAxisTitle("Entries [#]",2);
1197  Vx_Z->setAxisTitle("Primary Vertices Z [cm]",1);
1198  Vx_Z->setAxisTitle("Entries [#]",2);
1199 
1200  Vx_X_Cum = ibooker.book1D("H - vertex x cum", "Primary Vertex X Distribution (Cumulative)", int(rint(xRange/xStep)), -xRange/2., xRange/2.);
1201  Vx_Y_Cum = ibooker.book1D("H - vertex y cum", "Primary Vertex Y Distribution (Cumulative)", int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1202  Vx_Z_Cum = ibooker.book1D("H - vertex z cum", "Primary Vertex Z Distribution (Cumulative)", int(rint(zRange/zStep)), -zRange/2., zRange/2.);
1203  Vx_X_Cum->setAxisTitle("Primary Vertices X [cm]",1);
1204  Vx_X_Cum->setAxisTitle("Entries [#]",2);
1205  Vx_Y_Cum->setAxisTitle("Primary Vertices Y [cm]",1);
1206  Vx_Y_Cum->setAxisTitle("Entries [#]",2);
1207  Vx_Z_Cum->setAxisTitle("Primary Vertices Z [cm]",1);
1208  Vx_Z_Cum->setAxisTitle("Entries [#]",2);
1209 
1210  mXlumi = ibooker.book1D("B - muX vs lumi", "#mu_{x} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1211  mYlumi = ibooker.book1D("B - muY vs lumi", "#mu_{y} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1212  mZlumi = ibooker.book1D("B - muZ vs lumi", "#mu_{z} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1213  mXlumi->setAxisTitle("Lumisection [#]",1);
1214  mXlumi->setAxisTitle("#mu_{x} [cm]",2);
1215  mXlumi->getTH1()->SetOption("E1");
1216  mYlumi->setAxisTitle("Lumisection [#]",1);
1217  mYlumi->setAxisTitle("#mu_{y} [cm]",2);
1218  mYlumi->getTH1()->SetOption("E1");
1219  mZlumi->setAxisTitle("Lumisection [#]",1);
1220  mZlumi->setAxisTitle("#mu_{z} [cm]",2);
1221  mZlumi->getTH1()->SetOption("E1");
1222 
1223  sXlumi = ibooker.book1D("C - sigmaX vs lumi", "#sigma_{x} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1224  sYlumi = ibooker.book1D("C - sigmaY vs lumi", "#sigma_{y} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1225  sZlumi = ibooker.book1D("C - sigmaZ vs lumi", "#sigma_{z} vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1226  sXlumi->setAxisTitle("Lumisection [#]",1);
1227  sXlumi->setAxisTitle("#sigma_{x} [cm]",2);
1228  sXlumi->getTH1()->SetOption("E1");
1229  sYlumi->setAxisTitle("Lumisection [#]",1);
1230  sYlumi->setAxisTitle("#sigma_{y} [cm]",2);
1231  sYlumi->getTH1()->SetOption("E1");
1232  sZlumi->setAxisTitle("Lumisection [#]",1);
1233  sZlumi->setAxisTitle("#sigma_{z} [cm]",2);
1234  sZlumi->getTH1()->SetOption("E1");
1235 
1236  dxdzlumi = ibooker.book1D("D - dxdz vs lumi", "dX/dZ vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1237  dydzlumi = ibooker.book1D("D - dydz vs lumi", "dY/dZ vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1238  dxdzlumi->setAxisTitle("Lumisection [#]",1);
1239  dxdzlumi->setAxisTitle("dX/dZ [rad]",2);
1240  dxdzlumi->getTH1()->SetOption("E1");
1241  dydzlumi->setAxisTitle("Lumisection [#]",1);
1242  dydzlumi->setAxisTitle("dY/dZ [rad]",2);
1243  dydzlumi->getTH1()->SetOption("E1");
1244 
1245  Vx_ZX = ibooker.book2D("E - vertex zx", "Primary Vertex ZX Distribution", int(rint(zRange/zStep)), -zRange/2., zRange/2., int(rint(xRange/xStep)), -xRange/2., xRange/2.);
1246  Vx_ZY = ibooker.book2D("E - vertex zy", "Primary Vertex ZY Distribution", int(rint(zRange/zStep)), -zRange/2., zRange/2., int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1247  Vx_XY = ibooker.book2D("E - vertex xy", "Primary Vertex XY Distribution", int(rint(xRange/xStep)), -xRange/2., xRange/2., int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1248  Vx_ZX->setAxisTitle("Primary Vertices Z [cm]",1);
1249  Vx_ZX->setAxisTitle("Primary Vertices X [cm]",2);
1250  Vx_ZX->setAxisTitle("Entries [#]",3);
1251  Vx_ZY->setAxisTitle("Primary Vertices Z [cm]",1);
1252  Vx_ZY->setAxisTitle("Primary Vertices Y [cm]",2);
1253  Vx_ZY->setAxisTitle("Entries [#]",3);
1254  Vx_XY->setAxisTitle("Primary Vertices X [cm]",1);
1255  Vx_XY->setAxisTitle("Primary Vertices Y [cm]",2);
1256  Vx_XY->setAxisTitle("Entries [#]",3);
1257 
1258  Vx_ZX_Cum = ibooker.book2D("G - vertex zx cum", "Primary Vertex ZX Distribution (Cumulative)", int(rint(zRange/zStep)), -zRange/2., zRange/2., int(rint(xRange/xStep)), -xRange/2., xRange/2.);
1259  Vx_ZY_Cum = ibooker.book2D("G - vertex zy cum", "Primary Vertex ZY Distribution (Cumulative)", int(rint(zRange/zStep)), -zRange/2., zRange/2., int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1260  Vx_XY_Cum = ibooker.book2D("G - vertex xy cum", "Primary Vertex XY Distribution (Cumulative)", int(rint(xRange/xStep)), -xRange/2., xRange/2., int(rint(yRange/yStep)), -yRange/2., yRange/2.);
1261  Vx_ZX_Cum->setAxisTitle("Primary Vertices Z [cm]",1);
1262  Vx_ZX_Cum->setAxisTitle("Primary Vertices X [cm]",2);
1263  Vx_ZX_Cum->setAxisTitle("Entries [#]",3);
1264  Vx_ZY_Cum->setAxisTitle("Primary Vertices Z [cm]",1);
1265  Vx_ZY_Cum->setAxisTitle("Primary Vertices Y [cm]",2);
1266  Vx_ZY_Cum->setAxisTitle("Entries [#]",3);
1267  Vx_XY_Cum->setAxisTitle("Primary Vertices X [cm]",1);
1268  Vx_XY_Cum->setAxisTitle("Primary Vertices Y [cm]",2);
1269  Vx_XY_Cum->setAxisTitle("Entries [#]",3);
1270 
1271  hitCounter = ibooker.book1D("J - pixelHits vs lumi", "# Pixel-Hits vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1272  hitCounter->setAxisTitle("Lumisection [#]",1);
1273  hitCounter->setAxisTitle("Pixel-Hits [#]",2);
1274  hitCounter->getTH1()->SetOption("E1");
1275 
1276  goodVxCounter = ibooker.book1D("I - good vertices vs lumi", "# Good vertices vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1277  goodVxCounter->setAxisTitle("Lumisection [#]",1);
1278  goodVxCounter->setAxisTitle("Good vertices [#]",2);
1279  goodVxCounter->getTH1()->SetOption("E1");
1280 
1281  statusCounter = ibooker.book1D("K - status vs lumi", "App. Status vs. Lumisection", nLumiXaxisRange, 0.5, ((double)nLumiXaxisRange)+0.5);
1282  statusCounter->setAxisTitle("Lumisection [#]",1);
1283  statusCounter->getTH1()->SetOption("E1");
1284  statusCounter->getTH1()->GetYaxis()->Set(11,-5.5,5.5);
1285  statusCounter->getTH1()->GetYaxis()->SetBinLabel(1, "Max Lumi.");
1286  statusCounter->getTH1()->GetYaxis()->SetBinLabel(2, "Neg. det.");
1287  statusCounter->getTH1()->GetYaxis()->SetBinLabel(3, "Infinite err.");
1288  statusCounter->getTH1()->GetYaxis()->SetBinLabel(4, "No vtx.");
1289  statusCounter->getTH1()->GetYaxis()->SetBinLabel(5, "Infinite EDM");
1290  statusCounter->getTH1()->GetYaxis()->SetBinLabel(6, "OK");
1291  statusCounter->getTH1()->GetYaxis()->SetBinLabel(7, "MINUIT stat.");
1292  statusCounter->getTH1()->GetYaxis()->SetBinLabel(8, "MINUIT stat.");
1293  statusCounter->getTH1()->GetYaxis()->SetBinLabel(9, "MINUIT stat.");
1294  statusCounter->getTH1()->GetYaxis()->SetBinLabel(10, "MINUIT stat.");
1295  statusCounter->getTH1()->GetYaxis()->SetBinLabel(11, "MINUIT stat.");
1296 
1297  fitResults = ibooker.book2D("A - fit results","Results of Beam Spot Fit", 2, 0., 2., 9, 0., 9.);
1298  fitResults->setAxisTitle("Ongoing: bootstrapping", 1);
1299  fitResults->setBinLabel(9, "X[cm]", 2);
1300  fitResults->setBinLabel(8, "Y[cm]", 2);
1301  fitResults->setBinLabel(7, "Z[cm]", 2);
1302  fitResults->setBinLabel(6, "#sigma_{X}[cm]", 2);
1303  fitResults->setBinLabel(5, "#sigma_{Y}[cm]", 2);
1304  fitResults->setBinLabel(4, "#sigma_{Z}[cm]", 2);
1305  fitResults->setBinLabel(3, "#frac{dX}{dZ}[rad]", 2);
1306  fitResults->setBinLabel(2, "#frac{dY}{dZ}[rad]", 2);
1307  fitResults->setBinLabel(1, "Vtx[#]", 2);
1308  fitResults->setBinLabel(1, "Value", 1);
1309  fitResults->setBinLabel(2, "Error (stat)", 1);
1310  fitResults->getTH1()->SetOption("text");
1311 
1312 
1313  ibooker.setCurrentFolder("BeamPixel/EventInfo");
1314 
1315  reportSummary = ibooker.bookFloat("reportSummary");
1316  reportSummary->Fill(-1);
1317  reportSummaryMap = ibooker.book2D("reportSummaryMap","Pixel-Vertices Beam Spot: % Good Fits", 1, 0., 1., 1, 0., 1.);
1318  reportSummaryMap->getTH1()->SetBinContent(1, 1, -1);
1319 
1320  ibooker.setCurrentFolder("BeamPixel/EventInfo/reportSummaryContents");
1321 
1322  // Convention for reportSummary and reportSummaryMap:
1323  // - -1% at the moment of creation of the histogram (i.e. white histogram)
1324  // - n% numberGoodFits / numberFits
1325 
1326 
1327  reset("scratch"); // Initialize histograms after creation
1328 }
1329 
1330 
1331 // Define this as a plug-in
1332 DEFINE_FWK_MODULE(Vx3DHLTAnalyzer);
edm::EventID::run
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Definition: EventID.h:39
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Definition: DetSetVectorNew.h:188
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Definition: Vx3DHLTAnalyzer.cc:84
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Definition: Vx3DHLTAnalyzer.cc:906
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Definition: Vx3DHLTAnalyzer.cc:892
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Definition: Vx3DHLTAnalyzer.cc:223
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Cartesian x coordinate.
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Definition: Vx3DHLTAnalyzer.cc:27
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set x-, y- or z-axis title (axis=1, 2, 3 respectively)
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