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root/cvsroot/UserCode/cbrown/AnalysisFramework/Plotting/Modules/LimitCalculation.C
Revision: 1.31
Committed: Thu Nov 24 08:19:17 2011 UTC (13 years, 5 months ago) by buchmann
Content type: text/plain
Branch: MAIN
CVS Tags: cbaf_4_98ifb_paper, beforeFR20120418, cbaf_4p7ifb, HEAD
Changes since 1.30: +21 -8 lines
Error occurred while calculating annotation data.
Log Message:
Store predictions in new prediction library (don't do this though if we're in a hurry, say we're generating scan templates [i.e. last_configuration.C] )

File Contents

# Content
1 /****
2
3 Off peak status (RestrictToMassPeak) :
4
5 x Necessary adaptations identified
6 x Started working on necessary adaptations
7 x Necessary adaptations implemented
8 x Necessary adaptations tested
9
10 DONE!
11
12
13 ****/
14 #include <iostream>
15 #include <vector>
16 #include <sys/stat.h>
17 #include <fstream>
18
19 #include <TCut.h>
20 #include <TROOT.h>
21 #include <TCanvas.h>
22 #include <TMath.h>
23 #include <TColor.h>
24 #include <TPaveText.h>
25 #include <TRandom.h>
26 #include <TH1.h>
27 #include <TH2.h>
28 #include <TF1.h>
29 #include <TSQLResult.h>
30 #include <TProfile.h>
31 #include <TSystem.h>
32 #include "LimitDroplet.C"
33
34 //#include "TTbar_stuff.C"
35 using namespace std;
36
37 using namespace PlottingSetup;
38
39
40 void rediscover_the_top(string mcjzb, string datajzb) {
41 dout << "Hi! today we are going to (try to) rediscover the top!" << endl;
42 TCanvas *c3 = new TCanvas("c3","c3");
43 c3->SetLogy(1);
44 vector<float> binning;
45 //binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
46 /*
47 binning.push_back(50);
48 binning.push_back(100);
49 binning.push_back(150);
50 binning.push_back(200);
51 binning.push_back(500);
52
53
54 TH1F *dataprediction = allsamples.Draw("dataprediction", "-"+datajzb, binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
55 TH1F *puresignal = allsamples.Draw("puresignal", datajzb, binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
56 // TH1F *puresignal = allsamples.Draw("puresignal", mcjzb, binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc, luminosity,allsamples.FindSample("TTJets"));
57 TH1F *observed = allsamples.Draw("observed", datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
58 /*
59 ofstream myfile;
60 TH1F *ratio = (TH1F*)observed->Clone();
61 ratio->Divide(dataprediction);
62 ratio->GetYaxis()->SetTitle("Ratio obs/pred");
63 ratio->Draw();
64 c3->SaveAs("testratio.png");
65 myfile.open ("ShapeFit_log.txt");
66 establish_upper_limits(observed,dataprediction,puresignal,"LM4",myfile);
67 myfile.close();
68 */
69
70
71 int nbins=100;
72 float low=0;
73 float hi=500;
74 TCanvas *c4 = new TCanvas("c4","c4",900,900);
75 c4->Divide(2,2);
76 c4->cd(1);
77 c4->cd(1)->SetLogy(1);
78 TH1F *datapredictiont = allsamples.Draw("datapredictiont", "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
79 TH1F *datapredictiono = allsamples.Draw("datapredictiono", "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
80 datapredictiont->Add(datapredictiono,-1);
81 dout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
82 vector<TF1*> functions = do_cb_fit_to_plot(datapredictiont,10);
83 datapredictiont->SetMarkerColor(kRed);
84 datapredictiont->SetLineColor(kRed);
85 datapredictiont->Draw();
86 functions[1]->Draw("same");
87 TText *title1 = write_title("Top Background Prediction (JZB<0, with osof subtr)");
88 title1->Draw();
89
90 c4->cd(2);
91 c4->cd(2)->SetLogy(1);
92 TH1F *observedt = allsamples.Draw("observedt", datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
93 observedt->Draw();
94 datapredictiont->Draw("histo,same");
95 functions[1]->Draw("same");
96 TText *title2 = write_title("Observed and predicted background");
97 title2->Draw();
98
99 c4->cd(3);
100 c4->cd(3)->SetLogy(1);
101 // TH1F *ratio = (TH1F*)observedt->Clone();
102
103 TH1F *analytical_background_prediction= new TH1F("analytical_background_prediction","",nbins,low,hi);
104 for(int i=0;i<=nbins;i++) {
105 analytical_background_prediction->SetBinContent(i+1,functions[1]->Eval(((hi-low)/((float)nbins))*(i+0.5)));
106 analytical_background_prediction->SetBinError(i+1,TMath::Sqrt(functions[1]->Eval(((hi-low)/((float)nbins))*(i+0.5))));
107 }
108 analytical_background_prediction->GetYaxis()->SetTitle("JZB [GeV]");
109 analytical_background_prediction->GetYaxis()->CenterTitle();
110 TH1F *analyticaldrawonly = (TH1F*)analytical_background_prediction->Clone();
111 analytical_background_prediction->SetFillColor(TColor::GetColor("#3399FF"));
112 analytical_background_prediction->SetMarkerSize(0);
113 analytical_background_prediction->Draw("e5");
114 analyticaldrawonly->Draw("histo,same");
115 functions[1]->Draw("same");
116 TText *title3 = write_title("Analytical bg pred histo");
117 title3->Draw();
118
119 c4->cd(4);
120 // c4->cd(4)->SetLogy(1);
121 vector<float> ratio_binning;
122 ratio_binning.push_back(0);
123 ratio_binning.push_back(5);
124 ratio_binning.push_back(10);
125 ratio_binning.push_back(20);
126 ratio_binning.push_back(50);
127 // ratio_binning.push_back(60);
128 /*
129 ratio_binning.push_back(51);
130 ratio_binning.push_back(52);
131 ratio_binning.push_back(53);
132 ratio_binning.push_back(54);
133 ratio_binning.push_back(55);
134 ratio_binning.push_back(56);
135 ratio_binning.push_back(57);
136 ratio_binning.push_back(58);
137 ratio_binning.push_back(59);
138 ratio_binning.push_back(60);
139 // ratio_binning.push_back(70);*/
140 // ratio_binning.push_back(80);
141 // ratio_binning.push_back(90);
142 ratio_binning.push_back(80);
143 // ratio_binning.push_back(110);
144 ratio_binning.push_back(500);
145
146 TH1F *observedtb = allsamples.Draw("observedtb", datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
147 TH1F *datapredictiontb = allsamples.Draw("datapredictiontb", "-"+datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
148 TH1F *datapredictiontbo = allsamples.Draw("datapredictiontbo", "-"+datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
149 datapredictiontb->Add(datapredictiontbo,-1);
150 TH1F *analytical_background_predictionb = allsamples.Draw("analytical_background_predictionb",datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets&&"mll<2",data, luminosity);
151 for(int i=0;i<=ratio_binning.size();i++) {
152 analytical_background_predictionb->SetBinContent(i+1,functions[1]->Eval(analytical_background_predictionb->GetBinCenter(i)));
153 analytical_background_predictionb->SetBinError(i+1,TMath::Sqrt(functions[1]->Eval(analytical_background_predictionb->GetBinCenter(i))));
154 }
155
156 TH1F *ratio = (TH1F*) observedtb->Clone();
157 ratio->Divide(datapredictiontb);
158
159 for (int i=0;i<=ratio_binning.size();i++) {
160 dout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
161 }
162
163 // ratio->Divide(datapredictiontb);
164 // ratio->Divide(analytical_background_predictionb);
165 // TGraphAsymmErrors *JZBratio= histRatio(observedtb,analytical_background_predictionb,data,ratio_binning);
166 // ratio->Divide(analytical_background_prediction);
167 // ratio->Divide(datapredictiont);
168 // ratio->GetYaxis()->SetTitle("obs/pred");
169 // JZBratio->Draw("AP");
170 ratio->GetYaxis()->SetRangeUser(0,10);
171 ratio->Draw();
172 //analytical_background_predictionb->Draw();
173 // JZBratio->SetTitle("");
174 TText *title4 = write_title("Ratio of observed to predicted");
175 title4->Draw();
176
177 // CompleteSave(c4,"test/ttbar_discovery_dataprediction___analytical_function");
178 CompleteSave(c4,"test/ttbar_discovery_dataprediction__analytical__new_binning_one_huge_bin_from_80");
179
180
181
182
183
184 }
185
186 vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, string plotfilename, bool doexpected, int flipped) {
187 float sigma95=-9.9,sigma95A=-9.9;
188 /*
189 USAGE OF ROOSTATS_CL95
190 " Double_t limit = roostats_cl95(ilum, slum, eff, seff, bck, sbck, n, gauss = false, nuisanceModel, method, plotFileName, seed); \n"
191 " LimitResult expected_limit = roostats_clm(ilum, slum, eff, seff, bck, sbck, ntoys, nuisanceModel, method, seed); \n"
192 " Double_t average_limit = roostats_cla(ilum, slum, eff, seff, bck, sbck, nuisanceModel, method, seed); \n"
193 " \n"
194 "
195 " Double_t obs_limit = limit.GetObservedLimit(); \n"
196 " Double_t exp_limit = limit.GetExpectedLimit(); \n"
197 " Double_t exp_up = limit.GetOneSigmaHighRange(); \n"
198 " Double_t exp_down = limit.GetOneSigmaLowRange(); \n"
199 " Double_t exp_2up = limit.GetTwoSigmaHighRange(); \n"
200 " Double_t exp_2down = limit.GetTwoSigmaLowRange(); \n"
201 */
202 if(mceff<=0) {
203 write_warning(__FUNCTION__,"Cannot compute upper limit in this configuration as the efficiency is negative:");
204 dout << "mc efficiency=" << mceff << " +/- " << mcefferr;
205 vector<float> sigmas;
206 sigmas.push_back(-1);
207 sigmas.push_back(-1);
208 return sigmas;
209 } else {
210 int nlimittoysused=1;
211
212 ///------------------------------------------ < NEW > ----------------------------------------------------------
213
214 int secondssince1970=time(NULL);
215 stringstream repname;
216 repname << PlottingSetup::cbafbasedir << "/exchange/report_" << secondssince1970 << "_"<<plotfilename<< "__"<< ".txt";
217
218 /* - report filename [1]
219 - luminosity [2]
220 - lumi uncert [3]
221 - MC efficiency [4]
222 - MC efficiency error [5]
223 - Npred [6]
224 - Nprederr [7]
225 - Nobs [8]
226 - JZB cut [9]
227 - plot name [10]*/
228
229 if(flipped==0) dout << "Calling limit capsule instead of calling : CL95(" << luminosity << "," << lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
230 if(flipped>0) dout << "Calling limit capsule instead of calling : CL95(" << luminosity << "," << lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << flippedNpred[ibin] << "," << flippedNprederr[ibin] << "," << flippedNobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
231
232 stringstream command;
233 if(flipped==0) command << PlottingSetup::cbafbasedir << "/DistributedModelCalculations/Limits/TimedLimitCapsule.exec " << repname.str() << " " << luminosity << " " << luminosity*lumiuncert << " " << mceff << " " << mcefferr << " " << Npred[ibin] << " " << Nprederr[ibin] << " " << Nobs[ibin] << " " << -1 << " " << PlottingSetup::basedirectory << "/" << plotfilename << " " << doexpected;
234 if(flipped>0) command << PlottingSetup::cbafbasedir << "/DistributedModelCalculations/Limits/TimedLimitCapsule.exec " << repname.str() << " " << luminosity << " " << luminosity*lumiuncert << " " << mceff << " " << mcefferr << " " << flippedNpred[ibin] << " " << flippedNprederr[ibin] << " " << flippedNobs[ibin] << " " << -1 << " " << PlottingSetup::basedirectory << "/" << plotfilename << " " << doexpected;
235 dout << command.str() << endl;
236
237 int retval = 256;
238 int attempts=0;
239 while(!(retval==0||attempts>=3)) {//try up to 3 times
240 attempts++;
241 dout << "Starting limit calculation (TimedLimitCapsule) now : Attempt " << attempts << endl;
242 retval=gSystem->Exec(command.str().c_str());
243 }
244 char hostname[1023];
245 gethostname(hostname,1023);
246 if((!((Contains(hostname,"t3ui")||Contains(hostname,"t3wn"))))&&retval==256) {
247 //running via CRAB and encountered the same problem too often: place a problem file to mark this problem!
248 stringstream markproblem;
249 markproblem << "touch " << PlottingSetup::basedirectory << "/exchange/problemswhilesettinglimits.txt";
250 gSystem->Exec(markproblem.str().c_str());
251 }
252 LimitDroplet limres;
253 limres.readDroplet(repname.str());
254 dout << limres << endl;
255 remove(repname.str().c_str());
256 sigma95=limres.observed;
257
258
259 ///------------------------------------------ < /NEW > ----------------------------------------------------------
260 vector<float> sigmas;
261 sigmas.push_back(sigma95);
262 if(doexpected) {
263 sigmas.push_back(limres.expected);
264 sigmas.push_back(limres.upper68);
265 sigmas.push_back(limres.lower68);
266 sigmas.push_back(limres.upper95);
267 sigmas.push_back(limres.lower95);
268 }
269
270 return sigmas;
271
272
273 }//end of mc efficiency is ok
274 }
275
276 void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doexpected, int flipped) {
277 dout << "Doing counting experiment ... " << endl;
278 vector<vector<string> > limits;
279 vector<vector<float> > vlimits;
280
281
282 for(int isample=0;isample<signalsamples.collection.size();isample++) {
283 vector<string> rows;
284 vector<float> vrows;
285 dout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
286 rows.push_back(signalsamples.collection[isample].samplename);
287 for(int ibin=0;ibin<jzbcuts.size();ibin++) {
288 dout << "_________________________________________________________________________________" << endl;
289 float JZBcutat=uncertainties[isample*jzbcuts.size()+ibin][0];
290 float mceff=uncertainties[isample*jzbcuts.size()+ibin][1];
291 float staterr=uncertainties[isample*jzbcuts.size()+ibin][2];
292 float systerr=uncertainties[isample*jzbcuts.size()+ibin][3];
293 float toterr =uncertainties[isample*jzbcuts.size()+ibin][4];
294 float observed,observederr,null,result;
295
296 string plotfilename=(string)(TString(signalsamples.collection[isample].samplename)+TString("___JZB_geq_")+TString(any2string(JZBcutat))+TString(".png"));
297 dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
298 vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,plotfilename,doexpected,flipped);
299
300 tripple LibraryUpperLimits;
301 LibraryUpperLimits.name=signalsamples.collection[isample].samplename;
302 LibraryUpperLimits.first=mceff*signalsamples.collection[isample].xs * PlottingSetup::luminosity;
303 LibraryUpperLimits.second=staterr*signalsamples.collection[isample].xs * PlottingSetup::luminosity;
304 int resultindex=PlottingSetup::allresults.Find(jzbcuts[ibin]);
305 (allresults.predictions[resultindex]).SignalYield.push_back(LibraryUpperLimits);
306
307 if(doexpected) {
308 rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
309 vrows.push_back(sigmas[0]);
310 vrows.push_back(sigmas[1]);
311 vrows.push_back(signalsamples.collection[isample].xs);
312 }
313 else {
314 rows.push_back(any2string(sigmas[0]));
315 vrows.push_back(sigmas[0]);
316 vrows.push_back(signalsamples.collection[isample].xs);
317 }
318 }//end of bin loop
319 limits.push_back(rows);
320 vlimits.push_back(vrows);
321 }//end of sample loop
322
323 dout << endl << endl << "_______________________________________________________________________________________" << endl;
324 dout << "Going to store upper limit on event yield in result library: " << endl;
325 for(int ibin=0;ibin<jzbcuts.size();ibin++) {
326 int resultindex=PlottingSetup::allresults.Find(jzbcuts[ibin]);
327 vector<float> Normsigmas = compute_one_upper_limit(1.0,0.0, resultindex, mcjzb, "UPPERLIMIT", false, 0);
328 (allresults.predictions[resultindex]).UpperLimit=Normsigmas[0]*PlottingSetup::luminosity;
329 }
330 dout << endl << "_______________________________________________________________________________________" << endl;
331
332 dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
333 dout << endl << endl << "PAS table 3: (notation: limit [95%CL])" << endl << endl;
334 dout << "\t";
335 for (int irow=0;irow<jzbcuts.size();irow++) {
336 dout << jzbcuts[irow] << "\t";
337 }
338 dout << endl;
339 for(int irow=0;irow<limits.size();irow++) {
340 for(int ientry=0;ientry<limits[irow].size();ientry++) {
341 if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
342 else dout << " (N/A) \t";
343 }
344 dout << endl;
345 }
346
347 if(!doexpected) {
348 dout << endl << endl << "LIMITS: (Tex)" << endl;
349 tout << "\\begin{table}[hbtp]" << endl;
350 tout << "\\renewcommand{\\arraystretch}{1.3}" << endl;
351 tout << "\\begin{center}" << endl;
352 tout << "\\caption{Observed upper limits on the cross section of different LM benchmark points " << (ConsiderSignalContaminationForLimits?" (accounting for signal contamination)":" (not accounting for signal contamination)") << "}\\label{tab:lmresults}" << endl;
353 tout << "" << endl;
354 tout << "\\begin{tabular}{ | l | ";
355 for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
356 tout << "} " << endl << " \\hline " << endl << "& \t ";
357 for (int irow=0;irow<jzbcuts.size();irow++) {
358 tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
359 }
360 tout << " \\\\ \\hline " << endl;
361 for(int irow=0;irow<limits.size();irow++) {
362 tout << limits[irow][0] << " \t";
363 for(int ientry=0;ientry<jzbcuts.size();ientry++) {
364 if(vlimits[irow][2*ientry]>0) tout << " & " << Round(vlimits[irow][2*ientry],2) << " \t (" << Round(vlimits[irow][2*ientry] / vlimits[irow][2*ientry+1],3)<< "x \\sigma ) \t";
365 else tout << " & ( N / A ) \t";
366 // dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
367 }
368 tout << " \\\\ \\hline " << endl;
369 }
370 tout << "\\end{tabular}" << endl;
371 tout << " \\end{tabular}"<< endl;
372 tout << "\\end{center}"<< endl;
373 tout << "\\end{table} "<< endl;
374
375 }//do observed
376
377 dout << endl << endl << "Final selection efficiencies with total statistical and systematic errors, and corresponding observed and expected upper limits (UL) on ($\\sigma\\times$ BR $\\times$ acceptance) for the LM4 and LM8 scenarios, in the different regions. The last column contains the predicted ($\\sigma \\times $BR$\\times$ acceptance) at NLO obtained from Monte Carlo simulation." << endl;
378 dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
379 for(int icut=0;icut<jzbcuts.size();icut++) {
380 dout << "Region with JZB>" << jzbcuts[icut] << (ConsiderSignalContaminationForLimits?" (accounting for signal contamination)":" (not accounting for signal contamination)") << endl;
381 for(int isample=0;isample<signalsamples.collection.size();isample++) {
382 dout << limits[isample][0] << "\t" << Round(100*uncertainties[isample*jzbcuts.size()+icut][1],3) << "+/-" << Round(100*uncertainties[isample*jzbcuts.size()+icut][2],3) << " (stat) +/- " << Round(100*uncertainties[isample*jzbcuts.size()+icut][3],3) << " (syst) \t" << Round((vlimits[isample][2*icut]),3) << "\t" << Round(vlimits[isample][2*icut+1],3) << endl;
383 }
384 dout << endl;
385 }
386 allresults.Print();
387
388
389 }
390
391
392
393 /********************************************************************** new : Limits using SHAPES ***********************************
394
395
396 SSSSSSSSSSSSSSS hhhhhhh
397 SS:::::::::::::::Sh:::::h
398 S:::::SSSSSS::::::Sh:::::h
399 S:::::S SSSSSSSh:::::h
400 S:::::S h::::h hhhhh aaaaaaaaaaaaa ppppp ppppppppp eeeeeeeeeeee ssssssssss
401 S:::::S h::::hh:::::hhh a::::::::::::a p::::ppp:::::::::p ee::::::::::::ee ss::::::::::s
402 S::::SSSS h::::::::::::::hh aaaaaaaaa:::::ap:::::::::::::::::p e::::::eeeee:::::eess:::::::::::::s
403 SS::::::SSSSS h:::::::hhh::::::h a::::app::::::ppppp::::::pe::::::e e:::::es::::::ssss:::::s
404 SSS::::::::SS h::::::h h::::::h aaaaaaa:::::a p:::::p p:::::pe:::::::eeeee::::::e s:::::s ssssss
405 SSSSSS::::S h:::::h h:::::h aa::::::::::::a p:::::p p:::::pe:::::::::::::::::e s::::::s
406 S:::::S h:::::h h:::::h a::::aaaa::::::a p:::::p p:::::pe::::::eeeeeeeeeee s::::::s
407 S:::::S h:::::h h:::::ha::::a a:::::a p:::::p p::::::pe:::::::e ssssss s:::::s
408 SSSSSSS S:::::S h:::::h h:::::ha::::a a:::::a p:::::ppppp:::::::pe::::::::e s:::::ssss::::::s
409 S::::::SSSSSS:::::S h:::::h h:::::ha:::::aaaa::::::a p::::::::::::::::p e::::::::eeeeeeee s::::::::::::::s
410 S:::::::::::::::SS h:::::h h:::::h a::::::::::aa:::ap::::::::::::::pp ee:::::::::::::e s:::::::::::ss
411 SSSSSSSSSSSSSSS hhhhhhh hhhhhhh aaaaaaaaaa aaaap::::::pppppppp eeeeeeeeeeeeee sssssssssss
412 p:::::p
413 p:::::p
414 p:::::::p
415 p:::::::p
416 p:::::::p
417 ppppppppp
418
419
420 *********************************************************************** new : Limits using SHAPES ***********************************/
421
422
423 void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
424 dout << "Creatig shape templates ... ";
425 if(identifier!="") dout << "for systematic called "<<identifier;
426 dout << endl;
427 int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
428 if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
429
430 TCut limitnJetcut;
431 if(JES==noJES) limitnJetcut=cutnJets;
432 else {
433 if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
434 if(JES==JESup) limitnJetcut=cutnJetsJESup;
435 }
436 TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
437 TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
438 TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
439 TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
440
441 TH1F *SBOSSFP;
442 TH1F *SBOSOFP;
443 TH1F *SBOSSFN;
444 TH1F *SBOSOFN;
445
446 TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
447 TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
448 TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
449 TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
450
451 TH1F *LSBOSSFP;
452 TH1F *LSBOSOFP;
453 TH1F *LSBOSSFN;
454 TH1F *LSBOSOFN;
455
456 flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
457 if(PlottingSetup::RestrictToMassPeak) {
458 SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
459 SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
460 SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
461 SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
462
463 LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
464 LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
465 LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
466 LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
467 }
468
469 string obsname="data_obs";
470 string predname="background";
471 string signalname="signal";
472 if(identifier!="") {
473 obsname=("data_"+identifier);
474 predname=("background_"+identifier);
475 signalname="signal_"+identifier;
476 }
477
478 TH1F *obs = (TH1F*)ZOSSFP->Clone("observation");
479 obs->SetName(obsname.c_str());
480 obs->Write();
481 TH1F *pred = (TH1F*)ZOSSFN->Clone("prediction");
482 flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
483 if(PlottingSetup::RestrictToMassPeak) {
484 pred->Add(ZOSOFP,1.0/3);
485 pred->Add(ZOSOFN,-1.0/3);
486 pred->Add(SBOSSFP,1.0/3);
487 pred->Add(SBOSSFN,-1.0/3);
488 pred->Add(SBOSOFP,1.0/3);
489 pred->Add(SBOSOFN,-1.0/3);
490 } else {
491 pred->Add(ZOSOFP,1.0);
492 pred->Add(ZOSOFN,-1.0);
493 }
494
495 pred->SetName(predname.c_str());
496 pred->Write();
497
498 // TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
499 // TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
500
501 TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
502 TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
503 Lobs->Add(LZOSSFP);
504 Lpred->Add(LZOSSFN);
505 flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
506 if(PlottingSetup::RestrictToMassPeak) {
507 Lpred->Add(LZOSOFP,1.0/3);
508 Lpred->Add(LZOSOFN,-1.0/3);
509 Lpred->Add(LSBOSSFP,1.0/3);
510 Lpred->Add(LSBOSSFN,-1.0/3);
511 Lpred->Add(LSBOSOFP,1.0/3);
512 Lpred->Add(LSBOSOFN,-1.0/3);
513 } else {
514 Lpred->Add(LZOSOFP,1.0);
515 Lpred->Add(LZOSOFN,-1.0);
516 }
517
518 TH1F *signal = (TH1F*)Lobs->Clone();
519 signal->Add(Lpred,-1);
520 signal->SetName(signalname.c_str());
521 signal->Write();
522
523 delete Lobs;
524 delete Lpred;
525
526 delete ZOSSFP;
527 delete ZOSOFP;
528 delete ZOSSFN;
529 delete ZOSOFN;
530
531 if(PlottingSetup::RestrictToMassPeak) {
532 delete SBOSSFP;
533 delete SBOSOFP;
534 delete SBOSSFN;
535 delete SBOSOFN;
536 }
537
538 delete LZOSSFP;
539 delete LZOSOFP;
540 delete LZOSSFN;
541 delete LZOSOFN;
542
543 if(PlottingSetup::RestrictToMassPeak) {
544 delete LSBOSSFP;
545 delete LSBOSOFP;
546 delete LSBOSSFN;
547 delete LSBOSOFN;
548 }
549
550 }
551
552 void prepare_datacard(TFile *f) {
553 TH1F *dataob = (TH1F*)f->Get("data_obs");
554 TH1F *signal = (TH1F*)f->Get("signal");
555 TH1F *background = (TH1F*)f->Get("background");
556
557 ofstream datacard;
558 ensure_directory_exists(get_directory()+"/limits");
559 datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
560 datacard << "Writing this to a file.\n";
561 datacard << "imax 1\n";
562 datacard << "jmax 1\n";
563 datacard << "kmax *\n";
564 datacard << "---------------\n";
565 datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
566 datacard << "---------------\n";
567 datacard << "bin 1\n";
568 datacard << "observation "<<dataob->Integral()<<"\n";
569 datacard << "------------------------------\n";
570 datacard << "bin 1 1\n";
571 datacard << "process signal background\n";
572 datacard << "process 0 1\n";
573 datacard << "rate "<<signal->Integral()<<" "<<background->Integral()<<"\n";
574 datacard << "--------------------------------\n";
575 datacard << "lumi lnN 1.10 1.0\n";
576 datacard << "bgnorm lnN 1.00 1.4 uncertainty on our prediction (40%)\n";
577 datacard << "JES shape 1 1 uncertainty on background shape and normalization\n";
578 datacard << "peak shape 1 1 uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
579 datacard << "# so divide the unit gaussian by 2 before doing the interpolation\n";
580 datacard.close();
581 }
582
583
584 void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
585 ensure_directory_exists(get_directory()+"/limits");
586 TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
587 TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
588 limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
589 limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
590 limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
591 limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
592 limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
593
594 prepare_datacard(limfile);
595 limfile->Close();
596 write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
597
598 }