ATLAS Offline Software
NewLikelihoodTool.cxx
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1 /*
2  Copyright (C) 2002-2024 CERN for the benefit of the ATLAS collaboration
3 */
4 
5 #include "JetTagTools/NewLikelihoodTool.h"
6 
7 #include "JetTagTools/HistoHelperRoot.h"
8 
9 #include <cmath>
10 #include <string>
11 #include <utility>
12 #include <vector>
13 
14 #include "TH1.h"
15 #include "TH2.h"
16 #include "TH3.h"
17 
18 namespace Analysis {
19 
20  NewLikelihoodTool::NewLikelihoodTool(const std::string& t, const std::string& n, const IInterface* p) :
21  AthAlgTool(t,n,p),
22  m_taggerName("undefined"),
23  m_hypotheses(std::vector<std::string>()),
24  m_normalizedProb(true),
25  m_interpolate(false),
26  m_smoothNTimes(1),
27  m_vetoSmoothingOf(std::vector<std::string>()),
28  m_histograms(std::vector<std::string>()) {
29 
30  declareInterface<NewLikelihoodTool>(this);
31  declareProperty("taggerName", m_taggerName);
32  declareProperty("hypotheses", m_hypotheses);
33  declareProperty("normalizedProb", m_normalizedProb);
34  declareProperty("interpolate",m_interpolate);
35  declareProperty("smoothNTimes",m_smoothNTimes);
36  declareProperty("vetoSmoothingOf", m_vetoSmoothingOf);
37  m_hypotheses.push_back("B");
38  m_hypotheses.push_back("U");
39  m_hypotheses.push_back("C");
40  m_vetoSmoothingOf.push_back("/N2T");
41  m_vetoSmoothingOf.push_back("/N2TEffSV2");
42  m_vetoSmoothingOf.push_back("/Sip3D");
43  }
44 
45  StatusCode NewLikelihoodTool::initialize() {
46  ATH_CHECK(m_readKey.initialize());
47  return StatusCode::SUCCESS;
48  }
49 
50  void NewLikelihoodTool::defineHypotheses(const std::vector<std::string>& hyp) {
51  m_hypotheses = hyp;
52  }
53 
54  void NewLikelihoodTool::printStatus() const {
55  msg(MSG::INFO) << "#BTAG# - hypotheses : ";
56  for(const auto& hypo : m_hypotheses) msg(MSG::INFO) << hypo << ", ";
57  msg(MSG::INFO) << endmsg;
58  msg(MSG::INFO) << "#BTAG# - histograms : " << endmsg;
59  for(const auto& histo : m_histograms) msg(MSG::INFO) << histo << endmsg;
60  }
61 
62  std::vector<std::string> NewLikelihoodTool::gradeList(const std::string& histoName) const {
63  ATH_MSG_VERBOSE("#BTAG# gradeList() called for " << histoName);
64  const std::string delimSlash("/");
65  // first count slashes:
66  unsigned int nSlash = 0;
67  std::string::size_type slashPos;
68  for( unsigned int i = 0;
69  (slashPos = histoName.find(delimSlash, i)) != std::string::npos;
70  i = slashPos + 1) nSlash++;
71  // extract string before the 2nd / sign: this is for the grades, the rest is the histogram name
72  slashPos = histoName.find_first_of(delimSlash);
73  std::string newName = histoName.substr(slashPos+1);
74  slashPos = newName.find_first_of(delimSlash);
75  std::string grades = newName.substr(0,slashPos);
76  std::string hhname = newName.substr(slashPos+1);
77  if(nSlash<2) grades = "";
78  ATH_MSG_VERBOSE("#BTAG# -> grades: " << grades);
79  ATH_MSG_VERBOSE("#BTAG# -> hhname: " << hhname);
80  // now decode the grades:
81  std::vector<std::string> gradeList;
82  if(grades!="") {
83  const std::string delimUds("_");
84  std::string::size_type sPos, sEnd, sLen;
85  sPos = grades.find_first_not_of(delimUds);
86  while ( sPos != std::string::npos ) {
87  sEnd = grades.find_first_of(delimUds, sPos);
88  if(sEnd==std::string::npos) sEnd = grades.length();
89  sLen = sEnd - sPos;
90  std::string word = grades.substr(sPos,sLen);
91  ATH_MSG_DEBUG("#BTAG# --> grade = " << word);
92  gradeList.push_back(word);
93  sPos = grades.find_first_not_of(delimUds, sEnd);
94  }
95  }
96  // add the histogram name at the end of the list:
97  gradeList.push_back(hhname);
98  return gradeList;
99  }
100 
101  TH1* NewLikelihoodTool::prepareHistogram(const std::string& hypo, const std::string& hname) const {
102  TH1* histoSum = nullptr;
103 
104  SG::ReadCondHandle<JetTagCalibCondData> readCdo(m_readKey);
105  std::string channelName = readCdo->channelName(hname);
106  std::string histoName = readCdo->histoName(hname);
107  std::string actualName = hypo + "/" + histoName;
108  std::string longName = channelName + "#" + actualName;
109  ATH_MSG_VERBOSE("#BTAG# preparing histogram " << longName);
110  ATH_MSG_VERBOSE("#BTAG# -> channel is " << channelName);
111  ATH_MSG_VERBOSE("#BTAG# -> histo is " << histoName);
112  // now decode the grades:
113  std::vector<std::string> gradeList = this->gradeList(histoName);
114  // - case with no grade:
115  if(1==gradeList.size()) {
116  ATH_MSG_DEBUG("#BTAG# Histo "<<actualName<<" has no grade: direct retrieval");
117  histoSum = readCdo->retrieveHistogram(m_taggerName,
118  channelName,
119  actualName);
120  }
121  // - case with 1 grade:
122  if(2==gradeList.size()) {
123  ATH_MSG_DEBUG("#BTAG# Histo "<<actualName<<" has only one grade: direct retrieval");
124  histoSum = readCdo->retrieveHistogram(m_taggerName,
125  channelName,
126  actualName);
127  //Part not fully migrated
128  //smoothAndNormalizeHistogram should not be called here but in condition algorithm
129  ATH_MSG_VERBOSE("#BTAG# Smoothing histogram " << longName << " ...");
130  this->smoothAndNormalizeHistogram(histoSum, longName);
131  }
132  // - for many grades, get individual histos and sum them up:
133  if(gradeList.size()>2) {
134  TH1* histo = nullptr;
135  ATH_MSG_DEBUG("Histo " << actualName << " has " << (gradeList.size()-1) << " grades:");
136  for(unsigned int i=0;i<(gradeList.size()-1);i++) {
137  actualName = hypo+"/"+gradeList[i]+gradeList[gradeList.size()-1];
138  ATH_MSG_VERBOSE("#BTAG# -> retrieving histo for grade " << i << " " << gradeList[i] << ": ");
139  histo = readCdo->retrieveHistogram(m_taggerName,
140  channelName,
141  actualName);
142  if(histo) ATH_MSG_VERBOSE("#BTAG# histo " << actualName
143  << " has " << histo->GetEntries() << " entries.");
144  if(0==i) {
145  histoSum = histo;
146  } else {
147  if(histo&&histoSum) histoSum->Add(histo,1.);
148  }
149  }
150  //Part not fully migrated
151  //smoothAndNormalizeHistogram should not be called here but in condition algorithm
152  ATH_MSG_VERBOSE("#BTAG# Smoothing histogram " << longName << " ...");
153  this->smoothAndNormalizeHistogram(histoSum, longName);
154  }
155  return histoSum;
156  }
157 
158  void NewLikelihoodTool::smoothAndNormalizeHistogram(TH1* h, const std::string& hname = "") const {
159  if(h) {
160  double norm = h->Integral();
161  if(norm) {
162  // check if smoothing of histogram is not vetoed:
163  bool veto = false;
164  for(const auto& v : m_vetoSmoothingOf) {
165  if(hname.find(v)!=std::string::npos) {
166  veto = true;
167  ATH_MSG_VERBOSE("#BTAG# Smoothing of " << hname << " is vetoed !");
168  break;
169  }
170  }
171  if(1==h->GetDimension() && m_smoothNTimes) {
172  if(!veto) {
173  if(norm>10000)h->Smooth(m_smoothNTimes);
174  else h->Smooth((int)(m_smoothNTimes*100./sqrt(norm)));
175  }
176  }
177  if(2==h->GetDimension()) {
178  int m2d=3;
179  //if(hname.find("#B/")==std::string::npos) m2d=5; //VK oversmoothing!!!
180  if(!veto) {
181  TH2 * dc_tmp = dynamic_cast<TH2*>(h);
182  if (dc_tmp) {
183  HistoHelperRoot::smoothASH2D(dc_tmp, m2d, m2d, msgLvl(MSG::DEBUG));
184  }
185  }
186  }
187  if(3==h->GetDimension()) {
188  int m3d1=3;
189  int m3d3=2;
190  if(!veto) {
191  TH3 * dc_tmp = dynamic_cast<TH3*>(h);
192  if (dc_tmp) {
193  int Nx=dc_tmp->GetNbinsX();
194  int Ny=dc_tmp->GetNbinsY();
195  int Nz=dc_tmp->GetNbinsZ();
196  if(Nz == 7) //==========Old SV2
197  HistoHelperRoot::smoothASH3D(dc_tmp, m3d1, m3d1, m3d3, msgLvl(MSG::DEBUG));
198  else if(Nz == 6){ //==========New SV2Pt
199  double total=dc_tmp->Integral(1,Nx,1,Ny,1,Nz,"");
200  for(int iz=1; iz<=Nz; iz++){
201  double content=dc_tmp->Integral(1,Nx,1,Ny,iz,iz,""); if(content==0.)content=Nz;
202  double dnorm=total/content/Nz;
203  for(int ix=1; ix<=Nx; ix++){
204  for(int iy=1; iy<=Ny; iy++){
205  double cbin=dc_tmp->GetBinContent(ix,iy,iz)*dnorm; cbin= cbin>0. ? cbin : 0.1; //Protection against empty bins
206  dc_tmp->SetBinContent(ix,iy,iz, cbin);
207  }
208  }
209  }
210  HistoHelperRoot::smoothASH3D(dc_tmp, m3d1, m3d1, m3d3, msgLvl(MSG::DEBUG));
211  }
212  }
213  }
214  }
215  // normalize:
216  norm = h->Integral();
217  h->Scale(1./norm);
218  } else {
219  ATH_MSG_DEBUG("#BTAG# Histo "<<h<<" is empty!");
220  }
221  }
222  }
223 
224  std::vector<double> NewLikelihoodTool::calculateLikelihood(const std::vector<Slice>& lhVariableValues) const
225  {
226  ATH_MSG_VERBOSE("#BTAG# calculate called for " << m_hypotheses.size() << " hypotheses.");
227  std::vector<double> probDensityPerEventClassAllVariables;
228  probDensityPerEventClassAllVariables.resize(m_hypotheses.size());
229  for (unsigned int i = 0 ; i < m_hypotheses.size(); ++i) {
230  probDensityPerEventClassAllVariables[i]=1.;
231  }
232  ATH_MSG_VERBOSE("#BTAG# -- lhVarVal size= " << lhVariableValues.size());
233  // loop on Tracks in the Jet (IP) / Vertices in the Jet (SV)
234  for (const auto& value : lhVariableValues) {
235  ATH_MSG_VERBOSE( "#BTAG# -- element " << value.name );
236  int ncompo = value.composites.size();
237  ATH_MSG_VERBOSE( "#BTAG# -- element " << value.name
238  << " has " << ncompo << " composites." );
239  // loop on variables that make up the Tag, e.g.
240  // one 1D for IP2D, one 2D for IP3D, one 1D and one 2D for SV1, one 3D for SV2
241  for (const auto& compo : value.composites) {
242  double sum(0.);
243  std::vector<double> tmpVector;
244  std::string histName = compo.name;
245  int idim = compo.atoms.size();
246  ATH_MSG_VERBOSE( "#BTAG# -- composite histo= "
247  << histName << " dim= " << idim );
248  for (const auto& hypo : m_hypotheses) {
249  TH1* tmpHisto = this->prepareHistogram(hypo,histName);
250  if(tmpHisto) {
251  if(1==idim) {
252  double valuex = compo.atoms[0].value;
253  int binx = (tmpHisto->GetXaxis())->FindBin(valuex);
254  if(valuex >= tmpHisto->GetXaxis()->GetXmax()) binx = tmpHisto->GetXaxis()->GetNbins();
255  if(valuex <= tmpHisto->GetXaxis()->GetXmin()) binx = 1;
256  double tmp = tmpHisto->GetBinContent(binx);
257  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << "#BTAG# For hypothesis= " << hypo
258  << " (1D) actual value= " << valuex
259  << " --> bin= " << binx << " f = " << tmp;
260  if(m_interpolate) {
261  TH1* dc_tmp = dynamic_cast<TH1*>(tmpHisto);
262  if (dc_tmp) {
263  tmp = HistoHelperRoot::Interpol1d(valuex, dc_tmp);
264  if( msgLvl(MSG::VERBOSE) )msg(MSG::VERBOSE) << " interpolated f = " << tmp;
265  }
266  }
267  if(m_normalizedProb) { // pdf are already normalized
268  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " (normalized)" << endmsg;
269  } else {
270  double binw = tmpHisto->GetBinWidth(binx);
271  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " binw= " << binw;
272  if(0==binw) {
273  msg(MSG::ERROR) << "bin width is 0" << endmsg;
274  } else {
275  tmp /= binw;
276  }
277  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " normalized f = " << tmp << endmsg;
278  }
279  tmpVector.push_back(tmp);
280  sum += tmp;
281  }
282  if(2==idim) {
283  double valuex = compo.atoms[0].value;
284  double valuey = compo.atoms[1].value;
285  int binx = (tmpHisto->GetXaxis())->FindBin(valuex);
286  int biny = (tmpHisto->GetYaxis())->FindBin(valuey);
287  if(valuex >= tmpHisto->GetXaxis()->GetXmax()) binx = tmpHisto->GetXaxis()->GetNbins();
288  if(valuex <= tmpHisto->GetXaxis()->GetXmin()) binx = 1;
289  if(valuey >= tmpHisto->GetYaxis()->GetXmax()) biny = tmpHisto->GetYaxis()->GetNbins();
290  if(valuey <= tmpHisto->GetYaxis()->GetXmin()) biny = 1;
291  double tmp = tmpHisto->GetBinContent(binx, biny);
292  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << "#BTAG# For hypothesis= " << hypo
293  << " (2D) actual value= " << valuex << " " << valuey
294  << " --> bin= " << binx << " " << biny << " f = " << tmp;
295  if(m_interpolate) {
296  TH2* dc_tmp = dynamic_cast<TH2*>(tmpHisto);
297  if (dc_tmp) {
298  tmp = HistoHelperRoot::Interpol2d(valuex, valuey, dc_tmp);
299  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " interpolated f = " << tmp;
300  }
301  }
302  if(m_normalizedProb) { // pdf are already normalized
303  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " (normalized)" << endmsg;
304  } else {
305  double binw = tmpHisto->GetXaxis()->GetBinWidth(binx)
306  * tmpHisto->GetYaxis()->GetBinWidth(biny);
307  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " binw= " << binw;
308  if(0==binw) {
309  msg(MSG::ERROR) << "bin width is 0" << endmsg;
310  } else {
311  tmp /= binw;
312  }
313  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " normalized f = " << tmp << endmsg;
314  }
315  tmpVector.push_back(tmp);
316  sum += tmp;
317  }
318  if(3==idim) {
319  double valuex = compo.atoms[0].value;
320  double valuey = compo.atoms[1].value;
321  double valuez = compo.atoms[2].value;
322  int binx = (tmpHisto->GetXaxis())->FindBin(valuex);
323  int biny = (tmpHisto->GetYaxis())->FindBin(valuey);
324  int binz = (tmpHisto->GetZaxis())->FindBin(valuez);
325  if(valuex >= tmpHisto->GetXaxis()->GetXmax()) binx = tmpHisto->GetXaxis()->GetNbins();
326  if(valuex <= tmpHisto->GetXaxis()->GetXmin()) binx = 1;
327  if(valuey >= tmpHisto->GetYaxis()->GetXmax()) biny = tmpHisto->GetYaxis()->GetNbins();
328  if(valuey <= tmpHisto->GetYaxis()->GetXmin()) biny = 1;
329  if(valuez >= tmpHisto->GetZaxis()->GetXmax()) binz = tmpHisto->GetZaxis()->GetNbins();
330  if(valuez <= tmpHisto->GetZaxis()->GetXmin()) binz = 1;
331  double tmp = tmpHisto->GetBinContent(binx, biny, binz);
332  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << "#BTAG# For hypothesis= " << hypo
333  << " (3D) actual value= " << valuex
334  << " " << valuey << " " << valuez
335  << " --> bin= " << binx << " " << biny
336  << " " << binz << " f = " << tmp;
337  if(m_interpolate) {
338  TH3* dc_tmp = dynamic_cast<TH3*>(tmpHisto);
339  if (dc_tmp) {
340  tmp = HistoHelperRoot::Interpol3d(valuex, valuey, valuez, dc_tmp);
341  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " interpolated f = " << tmp;
342  }
343  }
344  if(m_normalizedProb) { // pdf are already normalized
345  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " (normalized)" << endmsg;
346  } else {
347  double binw = tmpHisto->GetXaxis()->GetBinWidth(binx)
348  * tmpHisto->GetYaxis()->GetBinWidth(biny)
349  * tmpHisto->GetZaxis()->GetBinWidth(binz);
350  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " binw= " << binw;
351  if(0==binw) {
352  msg(MSG::ERROR) << "bin width is 0" << endmsg;
353  } else {
354  tmp /= binw;
355  }
356  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << " normalized f = " << tmp << endmsg;
357  }
358  tmpVector.push_back(tmp);
359  sum += tmp;
360  }
361  if(idim>3 || idim<1 ) msg(MSG::DEBUG) << "#BTAG# " << idim
362  << " is not a correct dimensionality for pdfs !"
363  << endmsg;
364  }
365  } // endloop on hypotheses (B,U,C..)
366  unsigned int classCount(0);
367  for (const auto& f : tmpVector) {
368  if(sum != 0.) {
369  if( msgLvl(MSG::DEBUG) ) msg(MSG::DEBUG) << "#BTAG# sum of pX = " << sum << endmsg;
370  double p = f;
371  if(m_normalizedProb) p /= sum;
372  probDensityPerEventClassAllVariables[classCount] *= p;
373  } else {
374  msg(MSG::DEBUG) << "#BTAG# Empty bins for all hypothesis... "
375  << "The discriminating variables are not taken into "
376  << "account in this jet." << endmsg;
377  msg(MSG::DEBUG) << "#BTAG# Please check your inputs" << endmsg;
378  }
379  if( msgLvl(MSG::DEBUG) ) msg(MSG::DEBUG) << "#BTAG# probDensity= "
380  << probDensityPerEventClassAllVariables[classCount]
381  << " ic= " << classCount << endmsg;
382  classCount++;
383  }
384  if( msgLvl(MSG::DEBUG) ) msg(MSG::DEBUG) << "#BTAG# Final probDensity= "
385  << probDensityPerEventClassAllVariables
386  << endmsg;
387  }
388  }
389  if( msgLvl(MSG::DEBUG) ) msg(MSG::DEBUG) << "#BTAG# Ending ..." << endmsg;
390  return probDensityPerEventClassAllVariables;
391  }
392 
393  double NewLikelihoodTool::getEff(const std::string& hypo, const std::string& hname, const std::string& suffix) const {
394  double eff(0.);
395  TH1* numH = this->prepareHistogram(hypo, hname+"Eff"+suffix);
396  TH1* denH = this->prepareHistogram(hypo, hname+"Norm"+suffix);
397  if(numH && denH) {
398  double nnum = numH->GetEntries();
399  double nden = denH->GetEntries();
400  if(nden!=0) {
401  eff = nnum / nden;
402  if( msgLvl(MSG::VERBOSE) ) msg(MSG::VERBOSE) << "#BTAG# Efficiency for " << hypo << "#" << hname << " "
403  << suffix << ": " << nnum << "/" << nden << "= " << eff << endmsg;
404  } else {
405  msg(MSG::DEBUG) << "#BTAG# Problem with Efficiency for " << hypo << "#" << hname << " "
406  << suffix << ": " << nnum << "/" << nden << "= " << eff << endmsg;
407  }
408  } else {
409  msg(MSG::DEBUG) << "#BTAG# Unknown histogram for Efficiency for " << hypo
410  << "#" << hname << " " << suffix << endmsg;
411  }
412  return eff;
413  }
414 
415 
416 }
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