ATLAS Offline Software
run_EoverP.cxx
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1 /*
2  Copyright (C) 2002-2023 CERN for the benefit of the ATLAS collaboration
3 */
4 
5 #ifndef __CINT__
6 
7 #include "RooGlobalFunc.h"
8 #endif
9 #include "RooRealVar.h"
10 #include "RooDataSet.h"
11 #include "RooAbsData.h"
12 #include "RooDataHist.h"
13 #include "RooGaussian.h"
14 #include "RooLandau.h"
15 #include "RooChebychev.h"
16 #include "RooAddPdf.h"
17 #include "RooExtendPdf.h"
18 #include "RooCBShape.h"
19 #include "RooNovosibirsk.h"
20 #include "RooFFTConvPdf.h"
21 #include "RooExponential.h"
22 #include "RooSimultaneous.h"
23 #include "RooPolynomial.h"
24 #include "RooFitResult.h"
25 #include "RooCategory.h"
26 #include "RooBinning.h"
27 #include "RooWorkspace.h"
28 #include "RooChi2Var.h"
29 #include "RooMinuit.h"
30 #include "RooFormulaVar.h"
31 #include "RooPlot.h"
32 
33 
34 
35 #include<TFile.h>
36 #include<TH2F.h>
37 #include<TH3F.h>
38 #include<TH1D.h>
39 #include<TF1.h>
40 #include<TMath.h>
41 #include<TTree.h>
42 #include<TChain.h>
43 #include<TColor.h>
44 #include<TGraphErrors.h>
45 #include<TCanvas.h>
46 #include<TProfile.h>
47 #include<TString.h>
48 #include<iostream>
49 #include<TLegend.h>
50 #include <iomanip>
51 #include <cmath>
52 
53 #include "TROOT.h"
54 #include "THStack.h"
55 #include "AtlasStyle.C"
56 
57 using namespace RooFit ;
58 
59 // general functions
60 void initialize();
61 int main(){
62  return 0;
63 }
64 
65 // plotting functions
66 void makePlots( RooAbsData* originalDataSet,
67  RooRealVar& eOverP,
68  RooRealVar& eta,
69  int nBinsEta,
70  RooRealVar& phi,
71  int nBinsPhi,
72  RooRealVar& Et,
73  TString extraCuts = "");
74 void makeFits( RooAbsData* originalDataSet,
75  RooRealVar& eOverP,
76  RooRealVar& eta,
77  RooRealVar& phi,
78  TH2F* meanPlotPos,
79  TH2F* meanPlotNeg,
80  TString additionalCut = "" );
81 void makeSlicePlots(TH2F* pos, TH2F* neg, bool sliceInEta);
82 void makeRatioPlots(TH1D* h1, TH1D* h2, TString name);
83 
84 // corrections functions
85 TH2F* makeCorrectionHist();
86 double getCorrections(TH2F* corrections, double eta, double phi, double Et, double charge);
87 //void makeEtMeans(RooDataSet* dataSet,RooRealVar& Et,RooRealVar& ClusterEta,int nBinsEats);
88 void makeScalingHist(TString inputDir);
89 
90 // derpy global variable
91 TString PATH = "./Results/";
92 
93 void run_EoverP(TString fileName = "../share/eoverpValidationOut.root", int refit=2, int netabins=12, int nphibins=12){
94 
95  // ----------
96  // initialize
97  // ----------
98  initialize();
99 
100  // ----------
101  // check validity of input vars
102  // ----------
103  if( !((refit >= 0) && (refit <= 2)) ){
104  std::cout << "ERROR :: Input parameter 'refit' must be equal to 0, 1, or 2!" << std::endl;
105  std::exit(0);
106  }
107  if( (netabins < 1) || (nphibins < 1) ){
108  std::cout << "ERROR :: Can't have less than one bin in eta/phi!" << std::endl;
109  std::exit(0);
110  }
111 
112  // ----------
113  // set up our RooFit variables
114  // ----------
115  RooRealVar ClusterEnergy("ClusterEnergy","ClusterEnergy",0,1e10,"MeV") ;
116  RooRealVar ClusterPhi("ClusterPhi","#phi",0);
117  RooRealVar ClusterEta("ClusterEta","#eta",0);
118  RooRealVar charge("charge","charge",0);
119  RooRealVar TrackTheta("TrackTheta","TrackTheta",0);
120  RooRealVar TrackQoverP("QoverP","QoverP",-1e10,1e10,"MeV^{-1}");
121  RooRealVar EoverP("EoverP","E/p",0,5,"");
122  RooRealVar Et("Et","E_{T}",0,1e10,"GeV");
123  RooRealVar Eta("Eta","#eta",-3,3,"");
124 
125  RooArgSet arg;
126  arg.add(ClusterEnergy);
127  arg.add(ClusterPhi);
128  arg.add(ClusterEta);
129  arg.add(charge);
130  arg.add(TrackTheta);
131  arg.add(TrackQoverP);
132  arg.add(EoverP);
133  arg.add(Et);
134  arg.add(Eta);
135 
136  // ---------
137  // Open our TFile(s) and set up our event variables
138  // (in this format, each "event" is one electron)
139  // ---------
140  TChain *eoverpTree = new TChain("EGrefitterSmall");
141  eoverpTree->Add(fileName);
142 
143  Double_t el_ClusterEnergy;
144  Double_t el_ClusterPhi;
145  Double_t el_ClusterEta;
146  Double_t el_charge;
147  Double_t el_TrackTheta;
148  Double_t el_QoverP;
149  Double_t el_QoverP1;
150  Double_t el_QoverP2;
151  eoverpTree->SetBranchAddress("ClusterEnergy", &el_ClusterEnergy);
152  eoverpTree->SetBranchAddress("ClusterPhi", &el_ClusterPhi);
153  eoverpTree->SetBranchAddress("ClusterEta", &el_ClusterEta);
154  eoverpTree->SetBranchAddress("charge", &el_charge);
155  eoverpTree->SetBranchAddress("TrackTheta", &el_TrackTheta);
156  eoverpTree->SetBranchAddress("Default_QoverP", &el_QoverP);
157  eoverpTree->SetBranchAddress("Refitted1_QoverP", &el_QoverP1);
158  eoverpTree->SetBranchAddress("Refitted2_QoverP", &el_QoverP2);
159 
160  RooDataSet* dataSet = new RooDataSet("DataSet","DataSet",arg);
161 
162  // which refit QoverP do we want? -- Hardcoded for now...
163  //Int_t refit = 2 // 0 = original; 1 = refit1; 2 = refit2
164 
165  // ----------
166  // Loop over the events and fill the variables
167  // ----------
168  Int_t nEl = eoverpTree->GetEntries();
169  for (Int_t i=0; i<nEl; i++){
170  if( (i%10000) == 0 )
171  std::cout << "Filling variables for electron #" << i << std::endl;
172  eoverpTree->GetEntry(i);
173 
174  charge.setVal(el_charge);
175  Et.setVal(el_ClusterEnergy*sin(el_TrackTheta)*1e-3);
176  Eta.setVal(-log(tan(el_TrackTheta/2)) );
177  ClusterPhi.setVal(el_ClusterPhi);
178  ClusterEnergy.setVal(el_ClusterEnergy);
179  ClusterEta.setVal(el_ClusterEta);
180  //std::cout << "default: " << el_QoverP*el_ClusterEnergy << " refit1: " << el_QoverP1*el_ClusterEnergy << " refit2: " << el_QoverP2*el_ClusterEnergy << std::endl;
181  if(refit == 0){
182  EoverP.setVal(fabs(el_QoverP)*el_ClusterEnergy);
183  //std::cout << "refit = " << refit << " Using " << 1./el_QoverP << std::endl;
184  }
185  else if(refit == 1){
186  EoverP.setVal(fabs(el_QoverP1)*el_ClusterEnergy);
187  //std::cout << "refit = " << refit << " Using " << 1./el_QoverP1 << std::endl;
188  }
189  else{
190  EoverP.setVal(fabs(el_QoverP2)*el_ClusterEnergy);
191  //std::cout << "refit = " << refit << " Using " << 1./el_QoverP2 << std::endl;
192  }
193 
194  dataSet->add(arg);
195 
196  }
197 
198  TCanvas c; // put a blank page at the start of the output. because reasons.
199  c.Print(PATH+"new_eoverp_plots.pdf(");
200 
201  // ----------
202  // Pass the data off to the plotting functions
203  // ----------
204  makePlots(dataSet,
205  EoverP,
206  ClusterEta,
207  netabins,
208  ClusterPhi,
209  nphibins,
210  Et);
211 
212  c.Print(PATH+"new_eoverp_plots.pdf)"); // put a blank page at the end of the output. yup.
213 
214  makeScalingHist(PATH);
215 
216  return;
217 
218 }
219 
220 void makePlots( RooAbsData* originalDataSet,
221  RooRealVar& eOverP,
222  RooRealVar& eta,
223  int nBinsEta,
224  RooRealVar& phi,
225  int nBinsPhi,
226  RooRealVar& Et,
227  TString extraCuts )
228 {
229  // Set up ranges
230  double etaRange[nBinsEta+1];
231  double stepSize = 5./nBinsEta;
232  for (int i(0); i<= nBinsEta; ++i){
233  etaRange[i] = -2.5+stepSize*(double)i;
234  }
235 
236  double phiRange[nBinsPhi+1];
237  stepSize = 2 * TMath::Pi()/nBinsPhi;
238  for (int i(0); i<= nBinsPhi; ++i){
239  phiRange[i] = -TMath::Pi()+stepSize*(double)i;
240  }
241 
242 
243  TH2F *meanPlotPos = new TH2F("meanPlotPos"+extraCuts,"meanPlotPos"+extraCuts,nBinsEta,etaRange,nBinsPhi,phiRange );
244  meanPlotPos->SetTitle("Mean Plot Positive "+extraCuts);
245  meanPlotPos->GetXaxis()->SetTitle("#eta");
246  meanPlotPos->GetYaxis()->SetTitle("#phi [rad]");
247  TH2F *meanPlotNeg = new TH2F("meanPlotNeg"+extraCuts,"meanPlotNeg"+extraCuts,nBinsEta,etaRange,nBinsPhi,phiRange );
248  meanPlotNeg->SetTitle("Mean Plot Negative "+extraCuts);
249  meanPlotNeg->GetXaxis()->SetTitle("#eta");
250  meanPlotNeg->GetYaxis()->SetTitle("#phi [rad]");
251 
252  makeFits(originalDataSet,
253  eOverP,
254  eta,
255  phi,
256  meanPlotPos,
257  meanPlotNeg,
258  extraCuts);
259 
260  TFile f(PATH+"fitEoverP.root","Recreate");
261  meanPlotPos->Write();
262  meanPlotNeg->Write();
263 
264 
265  //if(Et != NULL ){
266  double ptRange[102];
267  stepSize = 1500;
268  for (int i=0; i<= 100; i++){
269  ptRange[i] = (20e3+stepSize*(double)i)/1000.; // GeV
270  //std::cout << ptRange[i] << std::endl;
271  }
272 
273  double eopRange[102];
274  stepSize = 0.05;
275  for (int i=0; i<= 100; i++){
276  eopRange[i] = 0.8+stepSize*(double)i;
277  }
278 
279  TH2F *ptvsEta = new TH2F("meanPtVsEta"+extraCuts,"meanPtVsEta"+extraCuts,nBinsEta,etaRange,100,ptRange);
280  TH2F *eoverPvsEta = new TH2F("eoverPvsEta"+extraCuts,"eoverPvsEta"+extraCuts,nBinsEta,etaRange,100,eopRange);
281 
282  RooArgSet vars(Et,eOverP,eta);
283  for(int i=0; i < originalDataSet->numEntries(); i++){
284  // wkd2 -- this is giving the same value of all the parameters for all i, need to fix it!
285  const RooArgSet* args = originalDataSet->get(i);
286  vars = *args;
287  //originalDataSet->get(i);
288  double valEt = Et.getVal();
289  double valeOverP = eOverP.getVal();
290  double valEta = eta.getVal();
291 
292  //std::cout << "valEta: " << valEta << " valEt: " << valEt << std::endl;
293 
294  ptvsEta->Fill(valEta,valEt);
295  eoverPvsEta->Fill(valEta,valeOverP);
296  }
297 
298  ptvsEta->Write();
299  eoverPvsEta->Write();
300  //} // end if(Et != NULL)
301 
302  //f.Write();
303  f.Close();
304 }
305 
306 
307 void makeFits( RooAbsData* originalDataSet,
308  RooRealVar& eOverP,
309  RooRealVar& xvar,
310  RooRealVar& yvar,
311  TH2F* meanPlotPos,
312  TH2F* meanPlotNeg,
313  TString additionalCut )
314 {
315 
316  //----------
317  // Initialize canvas
318  //----------
319  TCanvas *c = new TCanvas();
320  SetAtlasStyle();
321 
322  //----------
323  // Set up variables for the fits
324  //----------
325  // Variables
326  RooRealVar meanPos("<E/p>+","meanPos",1,0.,2.8,"") ;
327  RooRealVar meanNeg("<E/p>-","meanNeg",1,0.,2.8,"") ;
328  RooRealVar sigma("#sigma","sigma",0.1,0,5,"") ;
329  RooRealVar alpha("#alpha","alpha",-1,-100,-0.0001,"") ;
330  RooRealVar n("n","n",1,0.1,1000,"") ;
331 
332  // Landau parameters
333  RooRealVar LandauMeanPos ("LandauM+", "LandauMeanPos", 1,0.7,1.5,"");
334  LandauMeanPos.setConstant(kFALSE);
335  RooRealVar LandauMeanNeg ("LandauM-", "LandauMeanNeg", 1,0.7,1.5,"");
336  LandauMeanNeg.setConstant(kFALSE);
337  RooRealVar LandauS ("Landau #sigma", "Landau Sigma", 0.1,0,5,"");
338  LandauS.setConstant(kFALSE);
339 
340  // Functions
341  RooGaussian gaussianPos("PosGauss", "Initial Gauss", eOverP, meanPos, sigma);
342  RooGaussian gaussianNeg("NegGauss", "Initial Gauss", eOverP, meanNeg, sigma);
343  RooCBShape crystalBallPos("PosCB", "Crystal Ball shape", eOverP, meanPos, sigma, alpha, n);
344  RooCBShape crystalBallNeg("NegCB", "Crystal Ball shape", eOverP, meanNeg, sigma, alpha, n);
345  RooLandau LandauPos ("PosLandau", "Initial Landau", eOverP, LandauMeanPos, LandauS);
346  RooLandau LandauNeg ("NegLandau", "Initial Landau", eOverP, LandauMeanNeg, LandauS);
347 
348  // Landau-Gaussian convolution
349  RooFFTConvPdf LcwGPos ("LcwG_Pos", "Landau (x) Gauss", eOverP, LandauPos, gaussianPos);
350  RooFFTConvPdf LcwGNeg ("LcwG_Neg", "Landau (x) Gauss", eOverP, LandauNeg, gaussianNeg);
351 
352  // Setup fit ranges for eOverP variable we filled earlier
353  eOverP.setBins(50);
354  eOverP.setRange("fitGauss",0.5,1.5);
355  eOverP.setRange("fitLandau",0.5,1.5);
356  eOverP.setRange("final",0.0,3.0);
357  eOverP.setRange("finalFit",0.8,2.5);
358 
359  //----------
360  // Set up separate eta/phi binned data sets for positive/negative electrons
361  //----------
362  // get number of bins in eta(x)/phi(y)
363  static const int nBinsX = meanPlotPos->GetXaxis()->GetNbins();
364  static const int nBinsY = meanPlotPos->GetYaxis()->GetNbins();
365 
366  RooAbsData* absDataSetPos = originalDataSet->reduce( Cut("charge > 0"+ additionalCut) );
367  RooAbsData* absDataSetNeg = originalDataSet->reduce( Cut("charge < 0"+ additionalCut) );
368  RooDataSet* dataSetPos = dynamic_cast<RooDataSet*>( absDataSetPos ); // positron data set
369  RooDataSet* dataSetNeg = dynamic_cast<RooDataSet*>( absDataSetNeg ); // electron data set
370  RooArgSet vars(xvar,yvar,eOverP);
371 
372  RooDataSet* binnedDataPos[nBinsX][nBinsY]; // positron data set broken up by eta/phi bin
373  RooDataSet* binnedDataNeg[nBinsX][nBinsY]; // electron data set broken up by eta/phi bin
374 
375  // name each of our eta/phi bins in binnedDataPos/Neg
376  for(int xvarStep = 0; xvarStep<nBinsX; xvarStep++){ // eta
377  for(int yvarStep = 0; yvarStep<nBinsY; yvarStep++){ // phi
378 
379  TString rangeName = xvar.getTitle() + "Bin";
380  rangeName += xvarStep;
381  rangeName += "_"+yvar.getTitle()+"Bin";
382  rangeName += yvarStep;
383 
384  binnedDataPos[xvarStep][yvarStep] = (RooDataSet*)originalDataSet->emptyClone() ;
385  binnedDataNeg[xvarStep][yvarStep] = (RooDataSet*)originalDataSet->emptyClone() ;
386 
387  binnedDataPos[xvarStep][yvarStep]->SetName(rangeName+"_Pos");
388  binnedDataNeg[xvarStep][yvarStep]->SetName(rangeName+"_Neg");
389 
390  }
391  }
392 
393  //----------
394  // Fill pos/neg binned data sets
395  //----------
396  // positive
397  for (int i=0; i<dataSetPos->numEntries(); i++) {
398  const RooArgSet* args = dataSetPos->get(i);
399  vars= *args;
400  int globalbin = meanPlotPos->FindBin(xvar.getVal(),yvar.getVal());
401  int binx,biny,binz;
402  meanPlotPos->GetBinXYZ(globalbin,binx,biny,binz);
403  binnedDataPos[binx-1][biny-1]->add(*args);
404  }
405  // negative
406  for (int i=0; i<dataSetNeg->numEntries(); i++) {
407  const RooArgSet* args = dataSetNeg->get(i);
408  vars= *args;
409  int globalbin = meanPlotNeg->FindBin(xvar.getVal(),yvar.getVal());
410  int binx,biny,binz;
411  meanPlotNeg->GetBinXYZ(globalbin,binx,biny,binz);
412  binnedDataNeg[binx-1][biny-1]->add(*args);
413  }
414 
415  //----------
416  // Time to make the donuts
417  //----------
418  for(int xvarStep = 0; xvarStep<nBinsX; xvarStep++){ // eta
419  for(int yvarStep = 0; yvarStep<nBinsY; yvarStep++){ // phi
420  // some naming like we did before
421  TString rangeName = xvar.getTitle() + "Bin";
422  rangeName += xvarStep;
423  rangeName += "_"+yvar.getTitle()+"Bin";
424  rangeName += yvarStep;
425 
426  // set up the framse for pos/neg plots
427  RooPlot* framePos = eOverP.frame(Title("E/P pos"),Range("final"));
428  RooPlot* frameNeg = eOverP.frame(Title("E/P neg"),Range("final"));
429 
430  // make data sets from the relevent bin of the binned sets to be easier to work with
431  RooDataSet* smallDataSetPos = binnedDataPos[xvarStep][yvarStep];
432  RooDataSet* smallDataSetNeg = binnedDataNeg[xvarStep][yvarStep];
433 
434  // plot the smallDataSet on the corresponding frame: -- Pos(Blue) & Neg(Red)
435  smallDataSetPos->plotOn(framePos,LineColor(kBlue),MarkerColor(kBlue));
436  smallDataSetNeg->plotOn(frameNeg,LineColor(kRed),MarkerColor(kRed));
437 
438  // reset the fit paramaters
439  meanPos.setVal(1);
440  meanNeg.setVal(1);
441  sigma.setVal(0.1);
442  alpha.setVal(-1);
443  n.setVal(1);
444 
445  //----------
446  // Set up samples
447  //----------
448  RooCategory sample("sample","sample"); // separate positive and negative
449  sample.defineType("Pos");
450  sample.defineType("Neg");
451  RooDataSet combData("combData","combined data",eOverP,Index(sample),Import("Pos",*smallDataSetPos),Import("Neg",*smallDataSetNeg)); // combined data set in (x, sample)
452 
453  //----------
454  // Set up simultaneous pdfs in (x,sample)
455  //----------
456  // gaussian
457  RooSimultaneous simPdfGS("simPdfGS","simultaneous pdf",sample);
458  simPdfGS.addPdf(gaussianPos,"Pos");
459  simPdfGS.addPdf(gaussianNeg,"Neg");
460  // cristal ball
461  RooSimultaneous simPdfCB("simPdfCB","simultaneous pdf",sample);
462  simPdfCB.addPdf(crystalBallPos,"Pos");
463  simPdfCB.addPdf(crystalBallNeg,"Neg");
464  // landau
465  RooSimultaneous simPdfLnd("simPdfLnd","simultaneous pdf",sample);
466  simPdfLnd.addPdf(LandauPos,"Pos");
467  simPdfLnd.addPdf(LandauNeg,"Neg");
468  // landau-gaussian convolution
469  RooSimultaneous simPdfLcwG("simPdfLcwG","simultaneous pdf",sample);
470  simPdfLcwG.addPdf(LcwGPos,"Pos");
471  simPdfLcwG.addPdf(LcwGNeg,"Neg");
472 
473  //----------
474  // Perform simultaneous fit
475  //----------
476  // some fit vars
477  double fitMeanPos = -999.;
478  double fitMeanNeg = -999.;
479  double fitSigma = -999.;
480 
481  // set up ranges for first fit
482  eOverP.setRange("fitGauss_Pos",0.5,1.5);
483  eOverP.setRange("fitGauss_Neg",0.5,1.5);
484  // fit the gaussian & check if it produced a result
485  RooFitResult* fitResult = simPdfGS.fitTo(combData,Range("fitGauss"),SplitRange(),Save());
486  if(fitResult)
487  std::cout << "WARNING:: FIRST GAUSSIAN FIT PRODUCED A FIT RESULT" <<std::endl;
488  else
489  std::cout << "WARNING:: FIRST GAUSSIAN FIT DID NOT PRODUCE A FIT RESULT" <<std::endl;
490  // update fit vars
491  fitMeanPos = meanPos.getVal();
492  fitMeanNeg = meanNeg.getVal();
493  fitSigma = sigma.getVal();
494  // set up for 2nd fit
495  eOverP.setRange("fitGauss_Pos",fitMeanPos-2*fitSigma,fitMeanPos+2*fitSigma);
496  eOverP.setRange("fitGauss_Neg",fitMeanNeg-2*fitSigma,fitMeanNeg+2*fitSigma);
497  if ( fitResult && fitResult->status() != 0){
498  std::cout << "WARNING:: FIRST GAUSSIAN FIT DID NOT CONVERGE" <<std::endl;
499  meanPos.setVal(1);
500  meanNeg.setVal(1);
501  sigma.setVal(0.2);
502  eOverP.setRange("fitGauss_Pos",0.1,1.9);
503  eOverP.setRange("fitGauss_Neg",0.1,1.9);
504  }
505  // will ---
506 
507  fitResult = simPdfGS.fitTo(combData,Range("fitGauss"),SplitRange(),Save() );
508  if ( fitResult && fitResult->status() != 0){
509  std::cout << "WARNING::SECOND GAUSSIAN FIT DID NOT CONVERGE" <<std::endl;
510  meanPos.setVal(1);
511  meanNeg.setVal(1);
512  sigma.setVal(0.2);
513  }
514 
515  //if (fitResult) delete fitResult;
516 
517  /*
518  // do some more fits
519  int counter = 0;
520  do{
521  if(counter > 5){
522  std::cout<< "WARNING:: REACHED MAX FIT ATTEMPTS WITH NO CONVERGENCE" << std::endl;
523  break;
524  }
525  std::cout << "INFO:: TRYING GAUSSIAN FIT #"<< counter+2 << std::endl;
526 
527  fitResult = simPdfGS.fitTo(combData,Range("fitGauss"),SplitRange(),Save() );
528  if ( fitResult && fitResult->status() != 0){
529  std::cout << "WARNING:: GAUSSIAN FIT #"<< counter+2 << " DID NOT CONVERGE" <<std::endl;
530  meanPos.setVal(1.);
531  meanNeg.setVal(1.);
532  sigma.setVal(0.2+0.2*counter);
533  }
534  counter++;
535  } while(fitResult && fitResult->status() != 0);*/
536  // --- will
537 
538  if (fitResult) delete fitResult;
539  fitMeanPos = meanPos.getVal();
540  fitMeanNeg = meanNeg.getVal();
541  fitSigma = sigma.getVal();
542 
543  eOverP.setRange("fitGauss_Pos",fitMeanPos-1.25*fitSigma,fitMeanPos+1*fitSigma);
544  eOverP.setRange("fitGauss_Neg",fitMeanNeg-1.25*fitSigma,fitMeanNeg+1*fitSigma);
545 
546  // do final fit
547  fitResult = simPdfGS.fitTo(combData,Range("fitGauss"),SplitRange(), Save() );
548  if ( fitResult && fitResult->status() != 0){
549  std::cout << "WARNING::FINAL GAUSSIAN FIT DID NOT CONVERGE" <<std::endl;
550  meanPos.setVal(1);
551  meanNeg.setVal(1);
552  sigma.setVal(0.2);
553  fitSigma = 0.3;
554  }
555  if(fitResult) delete fitResult;
556 
557  //std::cout << "INFO: meanPos = " << meanPos.getVal() << " meanNeg = " << meanNeg.getVal() << " sigma = " << sigma.getVal() << std::endl;
558 
559  /*
560  //Fit with Landau
561  fitResult = simPdfLnd.fitTo(combData, Range("fitLandau"),SplitRange(), Save() ) ;
562  if ( fitResult && fitResult->status() != 0){
563  std::cout << "WARNING::TEST LANDAU FIT DID NOT CONVERGE" <<std::endl;
564  LandauMeanPos.setVal(1);
565  LandauMeanNeg.setVal(1);
566  LandauS.setVal(0.2);
567  //fitSigma = 0.3;
568  }
569  if(fitResult) delete fitResult;
570 
571  fitMeanPos = (meanPos.getVal()+LandauMeanPos.getVal())/2.;
572  fitMeanNeg = (meanNeg.getVal()+LandauMeanNeg.getVal())/2.;
573  fitSigma = sigma.getVal() > LandauS.getVal() ? sigma.getVal() : LandauS.getVal();
574 
575  std::cout << "INFO: meanPos = " << meanPos.getVal() << " meanNeg = " << meanNeg.getVal() << " sigma = " << sigma.getVal() << std::endl;
576  std::cout << "INFO: LandauMeanPos = " << LandauMeanPos.getVal() << " LandauMeanNeg = " << LandauMeanNeg.getVal() << " LandauS = " << LandauS.getVal() << std::endl;
577  std::cout << "INFO: Fit Mean Pos: " << fitMeanPos << " Fit Mean Pos: " << fitMeanNeg << "Fit Sigma: " << fitSigma << std::endl;
578  */
579 
580  //Perform simultaneous fit of model to data and model_ctl to data_ctl
581  eOverP.setRange("finalFit_Pos",fitMeanPos-1.5*fitSigma,2.5);
582  eOverP.setRange("finalFit_Neg",fitMeanNeg-1.5*fitSigma,2.5);
583 
584  if (fitMeanPos-1.5*fitSigma > 1.4 )
585  eOverP.setRange("finalFit_Pos",1.2,2.5);
586  if (fitMeanNeg-1.5*fitSigma > 1.4 )
587  eOverP.setRange("finalFit_Neg",1.2,2.5);
588 
589  //Here the range is fixed instead of using all teh above (25/Feb/14, S. Marti)
590  eOverP.setRange("finalFit_Pos",0.8,2.5);
591  eOverP.setRange("finalFit_Neg",0.8,2.5);
592  //LandauMeanPos.setVal(1.);//LandauMeanPos.setConstant(kTRUE);
593  //LandauMeanNeg.setVal(1.);//LandauMeanNeg.setConstant(kTRUE);
594  //meanPos.setVal(0.);meanPos.setConstant(kTRUE);
595  //meanNeg.setVal(0.);meanNeg.setConstant(kTRUE);
596  //sigma.setVal(0.2);
597 
598 
599 //***** Choose one, CB, Landau or LcwG
600  //Fit with CrystalBall
601  alpha.setVal(1.2);
602  meanPos.setVal(1.);
603  meanNeg.setVal(1.);
604  fitResult = simPdfCB.fitTo(combData, Range("finalFit"),SplitRange(), Save() ) ;
605  crystalBallPos.plotOn(framePos,LineColor(kAzure-2),Range("finalFit_Pos"),NormRange("finalFit_Pos"));
606  crystalBallNeg.plotOn(frameNeg,LineColor(kRed-7),Range("finalFit_Neg"),NormRange("finalFit_Neg"));
607 
608 
609  //Fit with Landau
610  /* fitResult = simPdfLnd.fitTo(combData, Range("finalFit"),SplitRange(), Save() ) ;
611  LandauPos.plotOn(framePos,LineColor(kOrange+1),Range("finalFit_Pos"),NormRange("finalFit_Pos"));
612  LandauNeg.plotOn(frameNeg,LineColor(kGreen+1),Range("finalFit_Neg"),NormRange("finalFit_Neg")); */
613 
614 
615  //Fit with Landau convoluted with Gaussian
616  if(false){
617  int simCount = 0;
618  do{
619  if(simCount > 5) break;
620  fitResult = simPdfLcwG.fitTo(combData, Range("finalFit"),SplitRange(), Save() ) ;
621  simCount++;
622  } while(fitResult && ( fitResult->status() != 0 || fitResult->covQual() != 3 ));
623 
624  LcwGPos.plotOn(framePos,LineColor(kAzure-2),Range("finalFit_Pos"),NormRange("finalFit_Pos"));
625  LcwGNeg.plotOn(frameNeg,LineColor(kRed-7),Range("finalFit_Neg"),NormRange("finalFit_Neg"));
626  }
627 
628  // hold on
629  if (false) {
630  string input = "";
631  cout << " ** fit_EoverP ** Please type RETURN to continue:\n>";
632  getline(cin, input);
633  }
634 
635 //*****
636 
637  meanPlotPos->SetBinContent(xvarStep+1,yvarStep+1,meanPos.getVal());
638  meanPlotPos->SetBinError (xvarStep+1,yvarStep+1,meanPos.getError());
639  meanPlotNeg->SetBinContent(xvarStep+1,yvarStep+1,meanNeg.getVal());
640  meanPlotNeg->SetBinError (xvarStep+1,yvarStep+1,meanNeg.getError());
641 
642  if( fitResult && ( fitResult->status() != 0 || fitResult->covQual() != 3 ) ){
643  std::cout << "WARNING::FINAL SIM FIT DID NOT CONVERGE FULLY" <<std::endl;
644  meanPlotPos->SetBinContent(xvarStep+1,yvarStep+1,1);
645  meanPlotPos->SetBinError (xvarStep+1,yvarStep+1,0.5);
646  meanPlotNeg->SetBinContent(xvarStep+1,yvarStep+1,1);
647  meanPlotNeg->SetBinError (xvarStep+1,yvarStep+1,0.5);
648  }
649 
650  if(fitResult) delete fitResult;
651 
652  c->Clear();
653  c->SetLogy(false);
654 
655  framePos->Draw();
656  frameNeg->Draw("same");
657 
658  //ATLASPRELIM_LABEL(0.25,0.88,0.03,1);
659  TString* xvarTString = new TString(xvar.getTitle());
660  TString* yvarTString = new TString(yvar.getTitle());
661 
662  const char *yvarChar = *yvarTString;
663  const char *xvarChar = *xvarTString;
664 
665 
666  myText(0.25,0.96,kBlack,Form("Slice %01.2f< %s <%01.2f, %01.2f< %s <%01.2f"
667  ,meanPlotPos->GetXaxis()->GetBinLowEdge(xvarStep+1)
668  ,xvarChar
669  ,meanPlotPos->GetXaxis()->GetBinLowEdge(xvarStep+2)
670  ,meanPlotPos->GetYaxis()->GetBinLowEdge(yvarStep+1)
671  ,yvarChar
672  ,meanPlotPos->GetYaxis()->GetBinLowEdge(yvarStep+2)) );
673 
674  myMarkerText(0.65,0.85,kBlue,20,Form("e^{+}, <E/p> %01.3f #pm %01.3f",meanPlotPos->GetBinContent(xvarStep+1,yvarStep+1), meanPlotNeg->GetBinError(xvarStep+1,yvarStep+1) ),1.0,0.03);
675  myMarkerText(0.65,0.80,kRed,20,Form("e^{-}, <E/p> %01.3f #pm %01.3f",meanPlotNeg->GetBinContent(xvarStep+1,yvarStep+1), meanPlotPos->GetBinError(xvarStep+1,yvarStep+1) ),1.0,0.03);
676 
677 
678  c->Print(PATH+"new_eoverp_plots.pdf");
679 
680  delete framePos;
681  delete frameNeg;
682  delete smallDataSetPos;
683  delete smallDataSetNeg;
684  }
685  }
686 
687  makeSlicePlots(meanPlotPos ,meanPlotNeg, false);
688  makeSlicePlots(meanPlotPos ,meanPlotNeg, true);
689 
690  const UInt_t Number = 3;
691  Double_t Green[Number] = { 0.00, 1.00, 0.00};
692  Double_t Red[Number] = { 1.00, 0.10, 0.00};
693  Double_t Blue[Number] = { 0.10, 0.10, 1.00};
694  Double_t Length[Number] = { 0.00, 0.50, 1.00 };
695  Int_t nb=50;
696  //TColor::CreateGradientColorTable(Number,Length,Red,Green,Blue,nb);
697 
698 
699  TH2F* clone =(TH2F*) meanPlotPos->Clone();
700  clone->Divide(meanPlotNeg);
701  clone->SetContour(nb);
702 
703  TH2F* clone2 =(TH2F*) meanPlotPos->Clone();
704  clone2->Add( meanPlotNeg, -1);
705  clone2->SetContour(nb);
706 
707  Double_t minPlot,maxPlot;
708 
709  c->Clear();
710  c->SetRightMargin(0.12);
711  c->SetLogy(false);
712  clone->Draw("colz");
713 
714  //Set Z axis centered in 1 so good points are in green
715  minPlot= clone->GetMinimum();
716  maxPlot= clone->GetMaximum();
717  if (maxPlot-1 > 1-minPlot) clone->SetMinimum(2-maxPlot);
718  else clone->SetMaximum(2-minPlot);
719 
720  c->Print(PATH+"new_eoverp_plots.pdf");
721 
722  meanPlotPos->Draw("colz");
723  meanPlotPos->SetContour(nb);
724 
725  //Set Z axis centered in 1 so good points are in green
726  minPlot= meanPlotPos->GetMinimum();
727  maxPlot= meanPlotPos->GetMaximum();
728  if (maxPlot-1 > 1-minPlot) meanPlotPos->SetMinimum(2-maxPlot);
729  else meanPlotPos->SetMaximum(2-minPlot);
730 
731  c->Print(PATH+"new_eoverp_plots.pdf");
732 
733  meanPlotNeg->Draw("colz");
734  meanPlotNeg->SetContour(nb);
735 
736  //Set Z axis centered in 1 so good points are in green
737  minPlot= meanPlotNeg->GetMinimum();
738  maxPlot= meanPlotNeg->GetMaximum();
739  if (maxPlot-1 > 1-minPlot) meanPlotNeg->SetMinimum(2-maxPlot);
740  else meanPlotNeg->SetMaximum(2-minPlot);
741 
742  c->Print(PATH+"new_eoverp_plots.pdf");
743 
744  TH1F* pull = new TH1F("pull","pull",50,-5,5);
745  pull->GetXaxis()->SetTitle("Fit Pull");
746  pull->GetYaxis()->SetTitle("Entries per 0.2");
747 
748  c->SetRightMargin(0.03);
749  TF1 myGauss("myGaus","gaus");
750  for(int xvarStep(0); xvarStep<nBinsX; ++xvarStep){
751  for(int yvarStep(0); yvarStep<nBinsY; ++yvarStep){
752  double R = clone->GetBinContent(xvarStep+1,yvarStep+1);
753  std::cout << "INFO : R "<< R << " Ratio delta " << (1-R)/(1+R) << " Diff Delta "<< clone2->GetBinContent(xvarStep+1,yvarStep+1)/-2. << " Diff Delta "<< 1-(clone2->GetBinContent(xvarStep+1,yvarStep+1)/-2.)/((1-R)/(1+R)) <<std::endl;
754  pull->Fill( ( 1-clone->GetBinContent(xvarStep+1,yvarStep+1))/clone->GetBinError (xvarStep+1,yvarStep+1) );
755  }
756  }
757  pull->Draw();
758  pull->Fit(&myGauss);
759  myMarkerText(0.7,0.85,kWhite,1,Form("Gaussian, #mu = %01.3f #pm %01.3f",myGauss.GetParameter(1), myGauss.GetParError(1) ),1.0,0.03);
760  myMarkerText(0.7,0.80,kWhite,1,Form("Gaussian, #sigma = %01.3f #pm %01.3f",myGauss.GetParameter(2), myGauss.GetParError(2) ),1.0,0.03);
761  myMarkerText(0.7,0.75,kWhite,1,Form("Mean, = %01.3f #pm %01.3f",pull->GetMean(), pull->GetMeanError() ),1.0,0.03);
762  myMarkerText(0.7,0.70,kWhite,1,Form("RMS, = %01.3f #pm %01.3f",pull->GetRMS(), pull->GetRMSError() ),1.0,0.03);
763 
764  c->Print(PATH+"new_eoverp_plots.pdf");
765 
766 
767  delete clone;
768  delete clone2;
769 
770 
771 }
772 
773 
774 void makeSlicePlots(TH2F* pos, TH2F* neg, bool sliceInEta)
775 {
776  std::cout << "INFO::makeSlicePlots()" << std::endl;
777 
778  int maxStep(1);
779 
780  if(sliceInEta){
781  maxStep = pos->GetNbinsX();
782  } else {
783  maxStep = pos->GetNbinsY();
784  }
785 
786  TString name;
787  for (int i(0); i <maxStep; ++i ){
788  TH1D* posProjection;
789  TH1D* negProjection;
790  name = pos->GetName();
791  name += "_Slice";
792 
793  if (sliceInEta){
794  posProjection = pos->ProjectionY( "_py", i+1 , i+1);
795  negProjection = neg->ProjectionY( "_py", i+1 , i+1);
796  name+="X";
797  name+=i;
798 
799  } else {
800  posProjection = pos->ProjectionX( "_px", i+1 , i+1);
801  negProjection = neg->ProjectionX( "_px", i+1 , i+1);
802  name+="Y";
803  name+=i;
804 
805  }
806 
807 
808 
809  makeRatioPlots(posProjection, negProjection, name );
810  delete posProjection;
811  delete negProjection;
812  }
813  std::cout << "INFO::Finished makeSlicePlots()" << std::endl;
814 }
815 
816 
817 
818 
819 void makeRatioPlots(TH1D* h1, TH1D* h2, TString name) {
820  std::cout << "INFO::Starting makeRatioPlots()" << std::endl;
821  TCanvas c1("C1","C1",600,600);
822  TPad *pad1 = new TPad("pad1","pad1",0,0.5,1,1);
823  pad1->SetTopMargin(0.05/0.5);
824  pad1->SetRightMargin(0.05);
825  pad1->SetBottomMargin(0.16);
826  pad1->SetLeftMargin(0.16);
827 
828  pad1->SetBottomMargin(0);
829  pad1->Draw();
830  pad1->cd();
831 
832  TH1D* h1clone = (TH1D*) h1->Clone();
833  h1->SetMarkerColor(kBlue);
834  h1->SetMarkerStyle(20);
835  h1->GetYaxis()->SetRangeUser(0.85,1.45);
836  h1->GetYaxis()->SetLabelSize(0.05/0.5);
837  h1->GetYaxis()->SetTitleSize(0.05/0.5);
838  h1->GetYaxis()->SetTitle("<E/p>");
839  h1->DrawCopy("pe");
840  h2->SetMarkerColor(kRed);
841  h2->SetMarkerStyle(22);
842  h2->Draw("samepe");
843  c1.cd();
844  TPad *pad2 = new TPad("pad2","pad2",0,0,1,0.5);
845  pad2->SetTopMargin(0.05);
846  pad2->SetRightMargin(0.05);
847  pad2->SetBottomMargin(0.16/0.5);
848  pad2->SetLeftMargin(0.16);
849 
850  //pad2->SetTopMargin(0);
851  pad2->Draw();
852  pad2->cd();
853  h1clone->Sumw2();
854  h1clone->SetStats(0);
855  h1clone->Divide(h2);
856  h1clone->SetMarkerColor(kBlack);
857  h1clone->SetMarkerStyle(20);
858  h1clone->GetYaxis()->SetLabelSize(0.05/0.5);
859  h1clone->GetXaxis()->SetLabelSize(0.05/0.5);
860  h1clone->GetYaxis()->SetTitleSize(0.05/0.5);
861  h1clone->GetXaxis()->SetTitleSize(0.05/0.5);
862  h1clone->GetYaxis()->SetRangeUser(0.8,1.2);
863  h1clone->GetYaxis()->SetTitle("<E/p>^{+}/<E/p>^{-}");
864 
865  h1clone->Draw("ep");
866  //h1->GetYaxis()->SetRangeUser(0.95,1.05);
867  c1.cd();
868 
869  // legend title setup
870  TString title;
871  if(name.Contains("Y",TString::kExact))
872  title += "Phi slice ";
873  else
874  title += "Eta slice ";
875  title += name[name.Length()-1];
876 
877  TLegend *leg1 = new TLegend(0.75,0.82,0.9,0.92);
878  leg1->SetBorderSize(0);
879  leg1->SetFillColor(0);
880  leg1->AddEntry("",title,"");
881  leg1->AddEntry(h1,"Positive","p");
882  leg1->AddEntry(h2,"Negative","p");
883  leg1->Draw();
884 
885  //c1.Print( PATH + name+".pdf");
886  c1.Print(PATH+"new_eoverp_plots.pdf");
887  delete h1clone;
888  delete pad1;
889  delete pad2;
890  std::cout << "INFO::Finished makeRatioPlots()" << std::endl;
891 
892 }
893 
894 void initialize(){
895  // Set up ATLAS style and other things before we get started
896  gROOT->LoadMacro("AtlasStyle.C");
897  SetAtlasStyle();
898  gROOT->SetBatch();
899  return;
900 }
901 
902 TH2F* makeCorrectionHist(){
903  TH2F *FinalCorrections = new TH2F("FinalCorrections","FinalCorrections",16,-2.5,2.5,16,-3.14159,3.14159);
904  return FinalCorrections;
905 }
906 
907 double getCorrections(TH2F* corrections, double eta, double phi, double Et, double charge){
908  //Q/p_constr=Q/p_recon*(1 + pT_recon*Q*delta)
909  if(!corrections)
910  return 1;
911 
912 
913  std::cout << "INFO :: GetCorrection -> Bin number "; //<< std::endl;
914 
915  int binNumber = corrections->FindBin(eta, phi);
916 
917  //std::cout<< binNumber << std::endl;
918 
919 
920  std::cout << "INFO :: GetCorrection -> delta" << std::endl;
921  double delta = corrections->GetBinContent(binNumber);
922 
923  return 1+charge*Et*delta;
924 }
925 
926 void makeScalingHist(TString inputDir)
927 {
928  std::cout << "INFO :: In makeScalingHist()" << std::endl;
929 
930  TString dir = PATH;
931  if(inputDir != "") dir = inputDir;
932  else{
933  std::cout << "ERROR :: makeScalingHist(): No input directory specified!" << std::endl;
934  return;
935  }
936 
937  TFile *file0 = TFile::Open(dir+"fitEoverP.root");
938  file0->ls();
939  TH2F* meanPlotNeg = (TH2F*) file0->Get("meanPlotNeg");
940  TH2F* meanPlotPos = (TH2F*) file0->Get("meanPlotPos");
941 
942 
943  if(!meanPlotNeg || !meanPlotNeg){
944  std::cout<< "ERROR :: makeScalingHist(): inputfile does not contain the desired histograms " << std::endl;
945  return;
946  }
947 
948  meanPlotNeg->Draw("colz");
949  meanPlotPos->Draw("colz");
950  meanPlotNeg->Sumw2();
951  meanPlotPos->Sumw2();
952 
953 
954  //Need to obtain the mean pt either from a histogram or from hardcoded values
955  double pt[1000]={};
956 
957  TH2F* meanPtVsEta = (TH2F*) file0->Get("meanPtVsEta");
958  if(!meanPtVsEta){
959  std::cout << "ERROR :: makeScalingHist(): inputfile does not contain the meanPtVsEta histogram " << std::endl;
960  return;
961  }
962  for(int i=1; i<=meanPtVsEta->GetNbinsX(); i++){
963  TH1D* projection = meanPtVsEta->ProjectionY( "_py", i , i);
964  pt[i-1] = (projection->GetMean()*1000.); //MeV
965  delete projection;
966  }
967 
968 
969  TH2F* a = (TH2F*) meanPlotPos->Clone();
970  a->Add(meanPlotNeg,-1);
971  a->Scale(-0.5); // divide by 2
972 
973  for(int i=1; i <= a->GetNbinsX(); i++){
974  for(int j=1; j <= a->GetNbinsY(); j++){
975  double temp = a->GetBinContent(i,j);
976  a->SetBinContent(i,j, temp/pt[i-1]*1e3);
977  temp = a->GetBinError(i,j);
978  a->SetBinError(i,j, temp/pt[i-1]*1e3);
979  }
980  }
981 
982  a->Draw("colz");
983 
984  TFile f(dir+"Scaling.root","RECREATE");
985  a->SetName("FinalCorrections");
986  a->SetTitle("FinalCorrections");
987  a->Write();
988  f.ls();
989  f.Close();
990 }
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A Range describes the possible ranges for the field values of an ExpandedIdentifier.
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TString PATH
Definition: run_EoverP.cxx:91
python.CaloCondTools.log
log
Definition: CaloCondTools.py:20
AllowedVariables::EoverP
@ EoverP
Definition: AsgElectronSelectorTool.cxx:56
python.TrigEgammaMonitorHelper.TH1F
def TH1F(name, title, nxbins, bins_par2, bins_par3=None, path='', **kwargs)
Definition: TrigEgammaMonitorHelper.py:24
LArCellBinning.phiRange
phiRange
Filling Phi ranges.
Definition: LArCellBinning.py:107
drawFromPickle.sin
sin
Definition: drawFromPickle.py:36
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void makeSlicePlots(TH2F *pos, TH2F *neg, bool sliceInEta)
Definition: run_EoverP.cxx:774
hotSpotInTAG.nb
nb
Definition: hotSpotInTAG.py:164
python.compressB64.c
def c
Definition: compressB64.py:93
Eta
@ Eta
Definition: RPCdef.h:8
python.CaloScaleNoiseConfig.args
args
Definition: CaloScaleNoiseConfig.py:80
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