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Revision: 1.23
Committed: Thu Sep 15 08:58:43 2011 UTC (13 years, 7 months ago) by buchmann
Content type: text/plain
Branch: MAIN
Changes since 1.22: +3 -4 lines
Log Message:
Everything is now ready to switch to roostats (just switch one line in LimitCalculation.C where it says LimitCapsule.exec and replace it with NewLimitCapsule.exec

File Contents

# Content
1 #include <iostream>
2 #include <vector>
3 #include <sys/stat.h>
4 #include <fstream>
5
6 #include <TCut.h>
7 #include <TROOT.h>
8 #include <TCanvas.h>
9 #include <TMath.h>
10 #include <TColor.h>
11 #include <TPaveText.h>
12 #include <TRandom.h>
13 #include <TH1.h>
14 #include <TH2.h>
15 #include <TF1.h>
16 #include <TSQLResult.h>
17 #include <TProfile.h>
18 #include <TSystem.h>
19 #include "LimitDroplet.C"
20
21 //#include "TTbar_stuff.C"
22 using namespace std;
23
24 using namespace PlottingSetup;
25
26
27 void rediscover_the_top(string mcjzb, string datajzb) {
28 dout << "Hi! today we are going to (try to) rediscover the top!" << endl;
29 TCanvas *c3 = new TCanvas("c3","c3");
30 c3->SetLogy(1);
31 vector<float> binning;
32 //binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
33 /*
34 binning.push_back(50);
35 binning.push_back(100);
36 binning.push_back(150);
37 binning.push_back(200);
38 binning.push_back(500);
39
40
41 TH1F *dataprediction = allsamples.Draw("dataprediction", "-"+datajzb, binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
42 TH1F *puresignal = allsamples.Draw("puresignal", datajzb, binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
43 // TH1F *puresignal = allsamples.Draw("puresignal", mcjzb, binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc, luminosity,allsamples.FindSample("TTJets"));
44 TH1F *observed = allsamples.Draw("observed", datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
45 /*
46 ofstream myfile;
47 TH1F *ratio = (TH1F*)observed->Clone();
48 ratio->Divide(dataprediction);
49 ratio->GetYaxis()->SetTitle("Ratio obs/pred");
50 ratio->Draw();
51 c3->SaveAs("testratio.png");
52 myfile.open ("ShapeFit_log.txt");
53 establish_upper_limits(observed,dataprediction,puresignal,"LM4",myfile);
54 myfile.close();
55 */
56
57
58 int nbins=100;
59 float low=0;
60 float hi=500;
61 TCanvas *c4 = new TCanvas("c4","c4",900,900);
62 c4->Divide(2,2);
63 c4->cd(1);
64 c4->cd(1)->SetLogy(1);
65 TH1F *datapredictiont = allsamples.Draw("datapredictiont", "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
66 TH1F *datapredictiono = allsamples.Draw("datapredictiono", "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
67 datapredictiont->Add(datapredictiono,-1);
68 dout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
69 vector<TF1*> functions = do_cb_fit_to_plot(datapredictiont,10);
70 datapredictiont->SetMarkerColor(kRed);
71 datapredictiont->SetLineColor(kRed);
72 datapredictiont->Draw();
73 functions[1]->Draw("same");
74 TText *title1 = write_title("Top Background Prediction (JZB<0, with osof subtr)");
75 title1->Draw();
76
77 c4->cd(2);
78 c4->cd(2)->SetLogy(1);
79 TH1F *observedt = allsamples.Draw("observedt", datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
80 observedt->Draw();
81 datapredictiont->Draw("histo,same");
82 functions[1]->Draw("same");
83 TText *title2 = write_title("Observed and predicted background");
84 title2->Draw();
85
86 c4->cd(3);
87 c4->cd(3)->SetLogy(1);
88 // TH1F *ratio = (TH1F*)observedt->Clone();
89
90 TH1F *analytical_background_prediction= new TH1F("analytical_background_prediction","",nbins,low,hi);
91 for(int i=0;i<=nbins;i++) {
92 analytical_background_prediction->SetBinContent(i+1,functions[1]->Eval(((hi-low)/((float)nbins))*(i+0.5)));
93 analytical_background_prediction->SetBinError(i+1,TMath::Sqrt(functions[1]->Eval(((hi-low)/((float)nbins))*(i+0.5))));
94 }
95 analytical_background_prediction->GetYaxis()->SetTitle("JZB [GeV]");
96 analytical_background_prediction->GetYaxis()->CenterTitle();
97 TH1F *analyticaldrawonly = (TH1F*)analytical_background_prediction->Clone();
98 analytical_background_prediction->SetFillColor(TColor::GetColor("#3399FF"));
99 analytical_background_prediction->SetMarkerSize(0);
100 analytical_background_prediction->Draw("e5");
101 analyticaldrawonly->Draw("histo,same");
102 functions[1]->Draw("same");
103 TText *title3 = write_title("Analytical bg pred histo");
104 title3->Draw();
105
106 c4->cd(4);
107 // c4->cd(4)->SetLogy(1);
108 vector<float> ratio_binning;
109 ratio_binning.push_back(0);
110 ratio_binning.push_back(5);
111 ratio_binning.push_back(10);
112 ratio_binning.push_back(20);
113 ratio_binning.push_back(50);
114 // ratio_binning.push_back(60);
115 /*
116 ratio_binning.push_back(51);
117 ratio_binning.push_back(52);
118 ratio_binning.push_back(53);
119 ratio_binning.push_back(54);
120 ratio_binning.push_back(55);
121 ratio_binning.push_back(56);
122 ratio_binning.push_back(57);
123 ratio_binning.push_back(58);
124 ratio_binning.push_back(59);
125 ratio_binning.push_back(60);
126 // ratio_binning.push_back(70);*/
127 // ratio_binning.push_back(80);
128 // ratio_binning.push_back(90);
129 ratio_binning.push_back(80);
130 // ratio_binning.push_back(110);
131 ratio_binning.push_back(500);
132
133 TH1F *observedtb = allsamples.Draw("observedtb", datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
134 TH1F *datapredictiontb = allsamples.Draw("datapredictiontb", "-"+datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data, luminosity);
135 TH1F *datapredictiontbo = allsamples.Draw("datapredictiontbo", "-"+datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data, luminosity);
136 datapredictiontb->Add(datapredictiontbo,-1);
137 TH1F *analytical_background_predictionb = allsamples.Draw("analytical_background_predictionb",datajzb, ratio_binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets&&"mll<2",data, luminosity);
138 for(int i=0;i<=ratio_binning.size();i++) {
139 analytical_background_predictionb->SetBinContent(i+1,functions[1]->Eval(analytical_background_predictionb->GetBinCenter(i)));
140 analytical_background_predictionb->SetBinError(i+1,TMath::Sqrt(functions[1]->Eval(analytical_background_predictionb->GetBinCenter(i))));
141 }
142
143 TH1F *ratio = (TH1F*) observedtb->Clone();
144 ratio->Divide(datapredictiontb);
145
146 for (int i=0;i<=ratio_binning.size();i++) {
147 dout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
148 }
149
150 // ratio->Divide(datapredictiontb);
151 // ratio->Divide(analytical_background_predictionb);
152 // TGraphAsymmErrors *JZBratio= histRatio(observedtb,analytical_background_predictionb,data,ratio_binning);
153 // ratio->Divide(analytical_background_prediction);
154 // ratio->Divide(datapredictiont);
155 // ratio->GetYaxis()->SetTitle("obs/pred");
156 // JZBratio->Draw("AP");
157 ratio->GetYaxis()->SetRangeUser(0,10);
158 ratio->Draw();
159 //analytical_background_predictionb->Draw();
160 // JZBratio->SetTitle("");
161 TText *title4 = write_title("Ratio of observed to predicted");
162 title4->Draw();
163
164 // CompleteSave(c4,"test/ttbar_discovery_dataprediction___analytical_function");
165 CompleteSave(c4,"test/ttbar_discovery_dataprediction__analytical__new_binning_one_huge_bin_from_80");
166
167
168
169
170
171 }
172
173 vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, string plotfilename, bool doexpected) {
174 float sigma95=-9.9,sigma95A=-9.9;
175 /*
176 USAGE OF ROOSTATS_CL95
177 " Double_t limit = roostats_cl95(ilum, slum, eff, seff, bck, sbck, n, gauss = false, nuisanceModel, method, plotFileName, seed); \n"
178 " LimitResult expected_limit = roostats_clm(ilum, slum, eff, seff, bck, sbck, ntoys, nuisanceModel, method, seed); \n"
179 " Double_t average_limit = roostats_cla(ilum, slum, eff, seff, bck, sbck, nuisanceModel, method, seed); \n"
180 " \n"
181 "
182 " Double_t obs_limit = limit.GetObservedLimit(); \n"
183 " Double_t exp_limit = limit.GetExpectedLimit(); \n"
184 " Double_t exp_up = limit.GetOneSigmaHighRange(); \n"
185 " Double_t exp_down = limit.GetOneSigmaLowRange(); \n"
186 " Double_t exp_2up = limit.GetTwoSigmaHighRange(); \n"
187 " Double_t exp_2down = limit.GetTwoSigmaLowRange(); \n"
188 */
189 if(mceff<=0) {
190 write_warning(__FUNCTION__,"Cannot compute upper limit in this configuration as the efficiency is negative:");
191 dout << "mc efficiency=" << mceff << " +/- " << mcefferr;
192 vector<float> sigmas;
193 sigmas.push_back(-1);
194 sigmas.push_back(-1);
195 return sigmas;
196 } else {
197 int nlimittoysused=1;
198
199 ///------------------------------------------ < NEW > ----------------------------------------------------------
200
201 int secondssince1970=time(NULL);
202 stringstream repname;
203 repname << PlottingSetup::cbafbasedir << "/exchange/report_" << secondssince1970 << "_"<<plotfilename<< "__"<< ".txt";
204
205 /* - report filename [1]
206 - luminosity [2]
207 - lumi uncert [3]
208 - MC efficiency [4]
209 - MC efficiency error [5]
210 - Npred [6]
211 - Nprederr [7]
212 - Nobs [8]
213 - JZB cut [9]
214 - plot name [10]*/
215
216 dout << "Calling limit capsule instead of calling : CL95(" << luminosity << "," << lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
217
218 write_warning(__FUNCTION__,"To update to roostats, replace LimitCapsule.exec with NewLimitCapsule.exec below (line"+string(any2string(__LINE__))+")");
219 stringstream command; // if you want to use roostats instead of cmscl95, please replace "LimitCapsule.exec" below with "NewLimitCapsule.exec"
220 command << PlottingSetup::cbafbasedir << "/DistributedModelCalculations/Limits/LimitCapsule.exec " << repname.str() << " " << luminosity << " " << luminosity*lumiuncert << " " << mceff << " " << mcefferr << " " << Npred[ibin] << " " << Nprederr[ibin] << " " << Nobs[ibin] << " " << -1 << " " << PlottingSetup::basedirectory << "/" << plotfilename << " " << doexpected;
221 dout << command.str() << endl;
222
223 int retval = 256;
224 int attempts=0;
225 while(!(retval==0||attempts>=5)) {//try up to 5 times
226 attempts++;
227 dout << "Starting limit calculation (LimitCapsule) now : Attempt " << attempts << endl;
228 retval=gSystem->Exec(command.str().c_str());
229 }
230
231 LimitDroplet limres;
232 limres.readDroplet(repname.str());
233 dout << limres << endl;
234 remove(repname.str().c_str());
235 sigma95=limres.observed;
236
237
238 ///------------------------------------------ < /NEW > ----------------------------------------------------------
239 //if(doexpected) nlimittoysused=nlimittoys;
240 // nlimittoysused=nlimittoys;
241 // dout << "Now calling : CL95(" << luminosity << "," << lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
242 // sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, nuisancemodel);
243 // sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, nuisancemodel);
244
245 /* dout << "Now calling : roostats_cl95(" << luminosity << "," << lumiuncert*luminosity << ","<<mceff <<","<<mcefferr<<","<<Npred[ibin]<<","<<Nprederr[ibin] << ",n=" << nlimittoysused << ",gauss=" << false << ",nuisanceModel="<<nuisancemodel<<",method="<<limitmethod<<",plotfilename="<<plotfilename<<",seed=0) " << endl;
246 /* dout << "Now calling : roostats_limit(" << luminosity << "," << lumiuncert*luminosity << ","<<mceff <<","<<mcefferr<<","<<Npred[ibin]<<","<<Nprederr[ibin] << ",n=" << nlimittoysused << ",gauss=" << false << ", nuisanceModel="<<nuisancemodel<<",method="<<limitmethod<<",plotfilename="<<plotfilename<<",seed=1) " << endl;
247 LimitResult limit = roostats_limit(luminosity,lumiuncert*luminosity,mceff,mcefferr,Npred[ibin],Nprederr[ibin],nlimittoysused,false,nuisancemodel,limitmethod,plotfilename,0);
248 dout << "Now interpreting and saving results ... " << endl;
249 vector<float> sigmas;
250 sigmas.push_back(limit.GetExpectedLimit());//expected
251 sigmas.push_back(limit.GetObservedLimit());//observed
252 //up to here for backward compatibility
253 sigmas.push_back(limit.GetOneSigmaHighRange());//expected, up
254 sigmas.push_back(limit.GetTwoSigmaHighRange());//expected, 2 up
255 sigmas.push_back(limit.GetOneSigmaLowRange());//expected, down
256 sigmas.push_back(limit.GetTwoSigmaLowRange());//expected, 2 down
257 */
258 // float limit = roostats_cl95(luminosity,lumiuncert*luminosity,mceff,mcefferr,Npred[ibin],Nprederr[ibin],nlimittoysused,false,nuisancemodel,limitmethod,plotfilename,0);
259 if(doexpected) {
260 write_warning(__FUNCTION__,"EXPECTED LIMITS HAVE BEEN SWITCHED OFF TEMPORARILY");
261 // dout << "Now calling : CLA(" << luminosity << "," << lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << nuisancemodel<< ") " << endl;
262 // sigma95A = CLA(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], nuisancemodel);
263 }
264 // vector<float> sigmas;
265 // sigmas.push_back(limit);
266 vector<float> sigmas;
267 sigmas.push_back(sigma95);
268 sigmas.push_back(sigma95A);
269 return sigmas;
270
271
272 }
273 write_warning(__FUNCTION__,"STILL MISSING SIGMAS, LIMITS, EVERYTHING ...");
274 }
275
276 void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doexpected) {
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 // fill_result_histos(observed,observederr, null,null,null,null,null,null,null,mcjzb,JZBcutat,14000,(int)5,result,(signalsamples.FindSample(signalsamples.collection[isample].filename)),signalsamples);
297 // observed-=result;//this is the actual excess we see!
298 // float expected=observed/luminosity;
299 string plotfilename=(string)(TString(signalsamples.collection[isample].samplename)+TString("___JZB_geq_")+TString(any2string(JZBcutat))+TString(".png"));
300 dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
301 vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,plotfilename,doexpected);
302
303 if(doexpected) {
304 // rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
305 rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
306 vrows.push_back(sigmas[0]);
307 vrows.push_back(sigmas[1]);
308 // vrows.push_back(expected);
309 vrows.push_back(signalsamples.collection[isample].xs);
310 }
311 else {
312 // rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
313 rows.push_back(any2string(sigmas[0]));
314 vrows.push_back(sigmas[0]);
315 vrows.push_back(signalsamples.collection[isample].xs);
316 // vrows.push_back(expected);
317 }
318 }//end of bin loop
319 limits.push_back(rows);
320 vlimits.push_back(vrows);
321 }//end of sample loop
322 dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
323 dout << endl << endl << "PAS table 3: (notation: limit [95%CL])" << endl << endl;
324 dout << "\t";
325 for (int irow=0;irow<jzbcuts.size();irow++) {
326 dout << jzbcuts[irow] << "\t";
327 }
328 dout << endl;
329 for(int irow=0;irow<limits.size();irow++) {
330 for(int ientry=0;ientry<limits[irow].size();ientry++) {
331 if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
332 else dout << " (N/A) \t";
333 }
334 dout << endl;
335 }
336
337 if(!doexpected) {
338 dout << endl << endl << "LIMITS: (Tex)" << endl;
339 tout << "\\begin{table}[hbtp]" << endl;
340 tout << "\\renewcommand{\\arraystretch}{1.3}" << endl;
341 tout << "\\begin{center}" << endl;
342 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;
343 tout << "" << endl;
344 tout << "\\begin{tabular}{ | l | ";
345 for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
346 tout << "} " << endl << " \\hline " << endl << "& \t ";
347 for (int irow=0;irow<jzbcuts.size();irow++) {
348 tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
349 }
350 tout << " \\\\ \\hline " << endl;
351 for(int irow=0;irow<limits.size();irow++) {
352 tout << limits[irow][0] << " \t";
353 for(int ientry=0;ientry<jzbcuts.size();ientry++) {
354 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";
355 else tout << " & ( N / A ) \t";
356 // dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
357 }
358 tout << " \\\\ \\hline " << endl;
359 }
360 tout << "\\end{tabular}" << endl;
361 tout << " \\end{tabular}"<< endl;
362 tout << "\\end{center}"<< endl;
363 tout << "\\end{table} "<< endl;
364
365 }//do observed
366
367 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;
368 dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
369 for(int icut=0;icut<jzbcuts.size();icut++) {
370 dout << "Region with JZB>" << jzbcuts[icut] << (ConsiderSignalContaminationForLimits?" (accounting for signal contamination)":" (not accounting for signal contamination)") << endl;
371 for(int isample=0;isample<signalsamples.collection.size();isample++) {
372 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;
373 }
374 dout << endl;
375 }
376 }
377
378
379
380 /********************************************************************** new : Limits using SHAPES ***********************************
381
382
383 SSSSSSSSSSSSSSS hhhhhhh
384 SS:::::::::::::::Sh:::::h
385 S:::::SSSSSS::::::Sh:::::h
386 S:::::S SSSSSSSh:::::h
387 S:::::S h::::h hhhhh aaaaaaaaaaaaa ppppp ppppppppp eeeeeeeeeeee ssssssssss
388 S:::::S h::::hh:::::hhh a::::::::::::a p::::ppp:::::::::p ee::::::::::::ee ss::::::::::s
389 S::::SSSS h::::::::::::::hh aaaaaaaaa:::::ap:::::::::::::::::p e::::::eeeee:::::eess:::::::::::::s
390 SS::::::SSSSS h:::::::hhh::::::h a::::app::::::ppppp::::::pe::::::e e:::::es::::::ssss:::::s
391 SSS::::::::SS h::::::h h::::::h aaaaaaa:::::a p:::::p p:::::pe:::::::eeeee::::::e s:::::s ssssss
392 SSSSSS::::S h:::::h h:::::h aa::::::::::::a p:::::p p:::::pe:::::::::::::::::e s::::::s
393 S:::::S h:::::h h:::::h a::::aaaa::::::a p:::::p p:::::pe::::::eeeeeeeeeee s::::::s
394 S:::::S h:::::h h:::::ha::::a a:::::a p:::::p p::::::pe:::::::e ssssss s:::::s
395 SSSSSSS S:::::S h:::::h h:::::ha::::a a:::::a p:::::ppppp:::::::pe::::::::e s:::::ssss::::::s
396 S::::::SSSSSS:::::S h:::::h h:::::ha:::::aaaa::::::a p::::::::::::::::p e::::::::eeeeeeee s::::::::::::::s
397 S:::::::::::::::SS h:::::h h:::::h a::::::::::aa:::ap::::::::::::::pp ee:::::::::::::e s:::::::::::ss
398 SSSSSSSSSSSSSSS hhhhhhh hhhhhhh aaaaaaaaaa aaaap::::::pppppppp eeeeeeeeeeeeee sssssssssss
399 p:::::p
400 p:::::p
401 p:::::::p
402 p:::::::p
403 p:::::::p
404 ppppppppp
405
406
407 *********************************************************************** new : Limits using SHAPES ***********************************/
408
409
410 void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
411 dout << "Creatig shape templates ... ";
412 if(identifier!="") dout << "for systematic called "<<identifier;
413 dout << endl;
414 int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
415 if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
416
417 TCut limitnJetcut;
418 if(JES==noJES) limitnJetcut=cutnJets;
419 else {
420 if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
421 if(JES==JESup) limitnJetcut=cutnJetsJESup;
422 }
423 TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
424 TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
425 TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
426 TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
427
428 TH1F *SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
429 TH1F *SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
430 TH1F *SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
431 TH1F *SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
432
433 TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
434 TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
435 TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
436 TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
437
438 TH1F *LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
439 TH1F *LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
440 TH1F *LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
441 TH1F *LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
442
443 string obsname="data_obs";
444 string predname="background";
445 string signalname="signal";
446 if(identifier!="") {
447 obsname=("data_"+identifier);
448 predname=("background_"+identifier);
449 signalname="signal_"+identifier;
450 }
451
452 TH1F *obs = (TH1F*)ZOSSFP->Clone();
453 obs->SetName(obsname.c_str());
454 obs->Write();
455 TH1F *pred = (TH1F*)ZOSSFN->Clone();
456 pred->Add(ZOSOFP,1.0/3);
457 pred->Add(ZOSOFN,-1.0/3);
458 pred->Add(SBOSSFP,1.0/3);
459 pred->Add(SBOSSFN,-1.0/3);
460 pred->Add(SBOSOFP,1.0/3);
461 pred->Add(SBOSOFN,-1.0/3);
462 pred->SetName(predname.c_str());
463 pred->Write();
464
465 // TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
466 // TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
467
468 TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
469 TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
470 Lobs->Add(LZOSSFP);
471 Lpred->Add(LZOSSFN);
472 Lpred->Add(LZOSOFP,1.0/3);
473 Lpred->Add(LZOSOFN,-1.0/3);
474 Lpred->Add(LSBOSSFP,1.0/3);
475 Lpred->Add(LSBOSSFN,-1.0/3);
476 Lpred->Add(LSBOSOFP,1.0/3);
477 Lpred->Add(LSBOSOFN,-1.0/3);
478 TH1F *signal = (TH1F*)Lobs->Clone();
479 signal->Add(Lpred,-1);
480 signal->SetName(signalname.c_str());
481 signal->Write();
482
483 delete Lobs;
484 delete Lpred;
485
486 delete ZOSSFP;
487 delete ZOSOFP;
488 delete ZOSSFN;
489 delete ZOSOFN;
490
491 delete SBOSSFP;
492 delete SBOSOFP;
493 delete SBOSSFN;
494 delete SBOSOFN;
495
496 delete LZOSSFP;
497 delete LZOSOFP;
498 delete LZOSSFN;
499 delete LZOSOFN;
500
501 delete LSBOSSFP;
502 delete LSBOSOFP;
503 delete LSBOSSFN;
504 delete LSBOSOFN;
505
506 }
507
508 void prepare_datacard(TFile *f) {
509 TH1F *dataob = (TH1F*)f->Get("data_obs");
510 TH1F *signal = (TH1F*)f->Get("signal");
511 TH1F *background = (TH1F*)f->Get("background");
512
513 ofstream datacard;
514 ensure_directory_exists(get_directory()+"/limits");
515 datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
516 datacard << "Writing this to a file.\n";
517 datacard << "imax 1\n";
518 datacard << "jmax 1\n";
519 datacard << "kmax *\n";
520 datacard << "---------------\n";
521 datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
522 datacard << "---------------\n";
523 datacard << "bin 1\n";
524 datacard << "observation "<<dataob->Integral()<<"\n";
525 datacard << "------------------------------\n";
526 datacard << "bin 1 1\n";
527 datacard << "process signal background\n";
528 datacard << "process 0 1\n";
529 datacard << "rate "<<signal->Integral()<<" "<<background->Integral()<<"\n";
530 datacard << "--------------------------------\n";
531 datacard << "lumi lnN 1.10 1.0\n";
532 datacard << "bgnorm lnN 1.00 1.4 uncertainty on our prediction (40%)\n";
533 datacard << "JES shape 1 1 uncertainty on background shape and normalization\n";
534 datacard << "peak shape 1 1 uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
535 datacard << "# so divide the unit gaussian by 2 before doing the interpolation\n";
536 datacard.close();
537 }
538
539
540 void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
541 ensure_directory_exists(get_directory()+"/limits");
542 TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
543 TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
544 limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
545 limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
546 limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
547 limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
548 limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
549
550 prepare_datacard(limfile);
551 limfile->Close();
552 write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
553
554 }