ViewVC Help

View File | Revision Log | Show Annotations | Root Listing

root/cvsroot/UserCode/cbrown/AnalysisFramework/Plotting/Modules/LimitCalculation.C

Comparing UserCode/cbrown/AnalysisFramework/Plotting/Modules/LimitCalculation.C (file contents):
Revision 1.1 by buchmann, Tue Jul 19 08:15:45 2011 UTC vs.
Revision 1.15 by buchmann, Thu Sep 1 11:01:42 2011 UTC

#	Line 1 | Line 1
1		#include <iostream>
2		#include <vector>
3		#include <sys/stat.h>
4	+	#include <fstream>
5
6		#include <TCut.h>
7		#include <TROOT.h>
#	Line 22 | Line 23 | using namespace PlottingSetup;
23
24
25		void rediscover_the_top(string mcjzb, string datajzb) {
26	<	cout << "Hi! today we are going to (try to) rediscover the top!" << endl;
26	>	dout << "Hi! today we are going to (try to) rediscover the top!" << endl;
27		TCanvas *c3 = new TCanvas("c3","c3");
28		c3->SetLogy(1);
29		vector<float> binning;
#	Line 62 | Line 63 | void rediscover_the_top(string mcjzb, st
63		TH1F *datapredictiont = allsamples.Draw("datapredictiont",    "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,  luminosity);
64		TH1F *datapredictiono = allsamples.Draw("datapredictiono",    "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,  luminosity);
65		datapredictiont->Add(datapredictiono,-1);
66	<	cout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
66	>	dout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
67		vector<TF1*> functions = do_cb_fit_to_plot(datapredictiont,10);
68		datapredictiont->SetMarkerColor(kRed);
69		datapredictiont->SetLineColor(kRed);
#	Line 141 | Line 142 | ratio_binning.push_back(80);
142		ratio->Divide(datapredictiontb);
143
144		for (int i=0;i<=ratio_binning.size();i++) {
145	<	cout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
145	>	dout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
146		}
147
148		//  ratio->Divide(datapredictiontb);
#	Line 167 | Line 168 | ratio_binning.push_back(80);
168
169		}
170
171	<	void calculate_upper_limits(string mcjzb, string datajzb) {
172	<	write_warning("calculate_upper_limits","Upper limit calculation temporarily deactivated");
173	<	//  write_warning("calculate_upper_limits","Calculation of SUSY upper limits has been temporarily suspended in favor of top discovery");
174	<	//  rediscover_the_top(mcjzb,datajzb);
175	<	/*
176	<	TCanvas *c3 = new TCanvas("c3","c3");
177	<	c3->SetLogy(1);
178	<	vector<float> binning;
179	<	//binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
180	<	binning.push_back(50);
181	<	binning.push_back(100);
182	<	binning.push_back(150);
183	<	binning.push_back(200);
184	<	binning.push_back(500);
185	<	TH1F *datapredictiona = allsamples.Draw("datapredictiona",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity);
186	<	TH1F *datapredictionb = allsamples.Draw("datapredictionb",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
187	<	TH1F *datapredictionc = allsamples.Draw("datapredictionc",    datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
188	<	TH1F *dataprediction = (TH1F*)datapredictiona->Clone();
189	<	dataprediction->Add(datapredictionb,-1);
190	<	dataprediction->Add(datapredictionc);
191	<	TH1F *puresignal     = allsamples.Draw("puresignal",        mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
192	<	TH1F *signalpred     = allsamples.Draw("signalpred",    "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
193	<	TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
194	<	TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
195	<	TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
196	<	signalpred->Add(signalpredlo,-1);
197	<	signalpred->Add(signalpredro);
198	<	puresignal->Add(signalpred,-1);//subtracting signal contamination
199	<	ofstream myfile;
200	<	myfile.open ("ShapeFit_log.txt");
201	<	establish_upper_limits(puredata,dataprediction,puresignal,"LM4",myfile);
202	<	myfile.close();
203	<	*/
171	>	vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, string plotfilename, bool doobserved) {
172	>	float sigma95=-9.9,sigma95A=-9.9;
173	>	int nuisancemodel=0;
174	>	/*
175	>	USAGE OF ROOSTATS_CL95
176	>	" Double_t             limit = roostats_cl95(ilum, slum, eff, seff, bck, sbck, n, gauss = false, nuisanceModel, method, plotFileName, seed); \n"
177	>	" LimitResult expected_limit = roostats_clm(ilum, slum, eff, seff, bck, sbck, ntoys, nuisanceModel, method, seed); \n"
178	>	" Double_t     average_limit = roostats_cla(ilum, slum, eff, seff, bck, sbck, nuisanceModel, method, seed); \n"
179	>	"                                                                     \n"
180	>	"
181	>	" Double_t obs_limit = limit.GetObservedLimit();                      \n"
182	>	" Double_t exp_limit = limit.GetExpectedLimit();                      \n"
183	>	" Double_t exp_up    = limit.GetOneSigmaHighRange();                  \n"
184	>	" Double_t exp_down  = limit.GetOneSigmaLowRange();                   \n"
185	>	" Double_t exp_2up   = limit.GetTwoSigmaHighRange();                  \n"
186	>	" Double_t exp_2down = limit.GetTwoSigmaLowRange();                   \n"
187	>	*/
188	>	if(mceff<=0) {
189	>	write_warning(__FUNCTION__,"Cannot compute upper limit in this configuration as the efficiency is negative:");
190	>	dout << "mc efficiency=" << mceff << " +/- " << mcefferr;
191	>	vector<float> sigmas;
192	>	sigmas.push_back(-1);
193	>	sigmas.push_back(-1);
194	>	return sigmas;
195	>	} else {
196	>	int nlimittoysused=1;
197	>	if(doobserved) nlimittoysused=nlimittoys;
198	>	/*  dout << "Now calling : CL95(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
199	>	sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, nuisancemodel);
200	>	*/
201	>	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;
202	>	LimitResult limit = roostats_limit(luminosity,lumiuncert*luminosity,mceff,mcefferr,Npred[ibin],Nprederr[ibin],nlimittoysused,false,nuisancemodel,limitmethod,plotfilename,1);
203	>
204	>	vector<float> sigmas;
205	>	sigmas.push_back(limit.GetExpectedLimit());//expected
206	>	sigmas.push_back(limit.GetObservedLimit());//observed
207	>	//up to here for backward compatibility
208	>	sigmas.push_back(limit.GetOneSigmaHighRange());//expected, up
209	>	sigmas.push_back(limit.GetTwoSigmaHighRange());//expected, 2 up
210	>	sigmas.push_back(limit.GetOneSigmaLowRange());//expected, down
211	>	sigmas.push_back(limit.GetTwoSigmaLowRange());//expected, 2 down
212	>	//  if(doobserved) {
213	>	//    dout << "Now calling : CLA(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << nuisancemodel<< ") " << endl;
214	>	//    sigma95A = CLA(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], nuisancemodel);
215	>	//  }
216	>
217	>	/*  vector<float> sigmas;
218	>	sigmas.push_back(sigma95);
219	>	sigmas.push_back(sigma95A);*/
220	>	return sigmas;
221	>
222	>
223	>	}
224	>	write_warning(__FUNCTION__,"STILL MISSING SIGMAS, LIMITS, EVERYTHING ...");
225		}
226
227	<	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts) {
228	<	cout << "Doing counting experiment ... " << endl;
227	>	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doobserved) {
228	>	dout << "Doing counting experiment ... " << endl;
229	>	vector<vector<string> > limits;
230	>	vector<vector<float> > vlimits;
231	>
232
233		for(int isample=0;isample<signalsamples.collection.size();isample++) {
234	<	cout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
234	>	vector<string> rows;
235	>	vector<float> vrows;
236	>	dout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
237	>	rows.push_back(signalsamples.collection[isample].samplename);
238		for(int ibin=0;ibin<jzbcuts.size();ibin++) {
239	<	cout << "   Considering bin " << jzbcuts[ibin] << endl;
240	<	for(int isyst=0;isyst<uncertainties[isample*jzbcuts.size()+ibin].size();isyst++) {
241	<	if(isyst==0) {
242	<	if(uncertainties[isample*jzbcuts.size()+ibin][isyst]!=jzbcuts[ibin]) cout << "WATCH OUT THERE SEEMS TO BE A PROBLEM - THE TEST BIN DOESN'T CORRESPOND TO YOUR BIN!" << endl;
243	<	continue;
244	<	}
245	<	cout << "     Considering syst " << isyst << " : " << uncertainties[isample*jzbcuts.size()+ibin][isyst] << endl;
246	<	}//end of syst loop
247	<	}//end of bin loop
248	<	}//end of sample loop
249	<	}
250	<
251	<	void susy_scan_axis_labeling(TH2F *histo) {
252	<	histo->GetXaxis()->SetTitle("#Chi_{2}^{0}-LSP");
253	<	histo->GetXaxis()->CenterTitle();
254	<	histo->GetYaxis()->SetTitle("m_{#tilde{q}}");
255	<	histo->GetYaxis()->CenterTitle();
256	<	}
257	<
258	<	void scan_susy_space(string mcjzb, string datajzb) {
259	<	TCanvas *c3 = new TCanvas("c3","c3");
260	<	vector<float> binning;
233	<	binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
234	<	/*
235	<	binning.push_back(50);
236	<	binning.push_back(75);
237	<	binning.push_back(100);
238	<	binning.push_back(150);
239	<	binning.push_back(200);
240	<	binning.push_back(500);
241	<	*/
242	<	float arrbinning[binning.size()];
243	<	for(int i=0;i<binning.size();i++) arrbinning[i]=binning[i];
244	<	TH1F *puredata   = allsamples.Draw("puredata",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
245	<	puredata->SetMarkerSize(DataMarkerSize);
246	<	TH1F *allbgs   = allsamples.Draw("allbgs",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
247	<	TH1F *allbgsb   = allsamples.Draw("allbgsb",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
248	<	TH1F *allbgsc   = allsamples.Draw("allbgsc",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
249	<	allbgs->Add(allbgsb,-1);
250	<	allbgs->Add(allbgsc);
251	<	int ndata=puredata->Integral();
252	<	ofstream myfile;
253	<	myfile.open ("susyscan_log.txt");
254	<	TFile *susyscanfile = new TFile("/scratch/fronga/SMS/T5z_SqSqToQZQZ_38xFall10.root");
255	<	TTree *suevents = (TTree*)susyscanfile->Get("events");
256	<	TH2F *exclusionmap = new TH2F("exclusionmap","",20,0,500,20,0,1000);
257	<	TH2F *exclusionmap1s = new TH2F("exclusionmap1s","",20,0,500,20,0,1000);
258	<	TH2F *exclusionmap2s = new TH2F("exclusionmap2s","",20,0,500,20,0,1000);
259	<	TH2F *exclusionmap3s = new TH2F("exclusionmap3s","",20,0,500,20,0,1000);
260	<
261	<	susy_scan_axis_labeling(exclusionmap);
262	<	susy_scan_axis_labeling(exclusionmap1s);
263	<	susy_scan_axis_labeling(exclusionmap2s);
264	<	susy_scan_axis_labeling(exclusionmap3s);
265	<
266	<	Int_t MyPalette[100];
267	<	Double_t r[]    = {0., 0.0, 1.0, 1.0, 1.0};
268	<	Double_t g[]    = {0., 0.0, 0.0, 1.0, 1.0};
269	<	Double_t b[]    = {0., 1.0, 0.0, 0.0, 1.0};
270	<	Double_t stop[] = {0., .25, .50, .75, 1.0};
271	<	Int_t FI = TColor::CreateGradientColorTable(5, stop, r, g, b, 100);
272	<	for (int i=0;i<100;i++) MyPalette[i] = FI+i;
273	<
274	<	gStyle->SetPalette(100, MyPalette);
275	<
276	<	for(int m23=50;m23<500;m23+=25) {
277	<	for (int m0=(2*(m23-50)+150);m0<=1000;m0+=50)
278	<	{
279	<	c3->cd();
280	<	stringstream drawcondition;
281	<	drawcondition << "pfJetGoodNum>=3&&(TMath::Abs(masses[0]-"<<m0<<")<10&&TMath::Abs(masses[2]-masses[3]-"<<m23<<")<10)&&mll>5&&id1==id2";
282	<	TH1F *puresignal = new TH1F("puresignal","puresignal",binning.size()-1,arrbinning);
283	<	TH1F *puresignall= new TH1F("puresignall","puresignal",binning.size()-1,arrbinning);
284	<	stringstream drawvar,drawvar2;
285	<	drawvar<<mcjzb<<">>puresignal";
286	<	drawvar2<<"-"<<mcjzb<<">>puresignall";
287	<	suevents->Draw(drawvar.str().c_str(),drawcondition.str().c_str());
288	<	suevents->Draw(drawvar2.str().c_str(),drawcondition.str().c_str());
289	<	if(puresignal->Integral()<60) {
290	<	delete puresignal;
291	<	continue;
239	>	dout << "_________________________________________________________________________________" << endl;
240	>	float JZBcutat=uncertainties[isample*jzbcuts.size()+ibin][0];
241	>	float mceff=uncertainties[isample*jzbcuts.size()+ibin][1];
242	>	float staterr=uncertainties[isample*jzbcuts.size()+ibin][2];
243	>	float systerr=uncertainties[isample*jzbcuts.size()+ibin][3];
244	>	float toterr =uncertainties[isample*jzbcuts.size()+ibin][4];
245	>	float observed,observederr,null,result;
246	>
247	>	//      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);
248	>	//      observed-=result;//this is the actual excess we see!
249	>	//      float expected=observed/luminosity;
250	>	string plotfilename=(string)(TString(signalsamples.collection[isample].samplename)+TString("___JZB_geq_")+TString(any2string(JZBcutat)));
251	>	dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
252	>	vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,plotfilename,doobserved);
253	>
254	>	if(doobserved) {
255	>	//      rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
256	>	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
257	>	vrows.push_back(sigmas[0]);
258	>	vrows.push_back(sigmas[1]);
259	>	//      vrows.push_back(expected);
260	>	vrows.push_back(signalsamples.collection[isample].xs);
261		}
262	<	puresignal->Add(puresignall,-1);//we need to correct for the signal contamination - we effectively only see (JZB>0)-(JZB<0) !!
263	<	puresignal->Scale(ndata/(20*puresignal->Integral()));//normalizing it to 5% of the data
264	<	stringstream saveas;
265	<	saveas<<"Model_Scan/m0_"<<m0<<"__m23_"<<m23;
266	<	cout << "PLEASE KEEP IN MIND THAT SIGNAL CONTAMINATION IS NOT REALLY TAKEN CARE OF YET DUE TO LOW STATISTICS! SHOULD BE SOMETHING LIKE THIS : "<< endl;
267	<	//        TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
299	<	//        TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
300	<	//        TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
301	<	//        signalpred->Add(signalpredlo,-1);
302	<	//        signalpred->Add(signalpredro);
303	<	//        puresignal->Add(signalpred,-1);//subtracting signal contamination
304	<	//---------------------
305	<	//      cout << "(m0,m23)=("<<m0<<","<<m23<<") contains " << puresignal->Integral() << endl;
306	<	//    TH1F *puresignal = allsamples.Draw("puresignal",mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
307	<	vector<float> results=establish_upper_limits(puredata,allbgs,puresignal,saveas.str(),myfile);
308	<	if(results.size()==0) {
309	<	delete puresignal;
310	<	continue;
262	>	else {
263	>	//      rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
264	>	rows.push_back(any2string(sigmas[0]));
265	>	vrows.push_back(sigmas[0]);
266	>	vrows.push_back(signalsamples.collection[isample].xs);
267	>	//      vrows.push_back(expected);
268		}
269	<	exclusionmap->Fill(m23,m0,results[0]);
270	<	exclusionmap1s->Fill(m23,m0,results[1]);
271	<	exclusionmap2s->Fill(m23,m0,results[2]);
272	<	exclusionmap3s->Fill(m23,m0,results[3]);
273	<	delete puresignal;
274	<	cout << "(m0,m23)=("<<m0<<","<<m23<<") : 3 sigma at " << results[3] << endl;
269	>	}//end of bin loop
270	>	limits.push_back(rows);
271	>	vlimits.push_back(vrows);
272	>	}//end of sample loop
273	>	dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
274	>	dout << endl << endl << "PAS table 3:   (notation: limit [95%CL])" << endl << endl;
275	>	dout << "\t";
276	>	for (int irow=0;irow<jzbcuts.size();irow++) {
277	>	dout << jzbcuts[irow] << "\t";
278	>	}
279	>	dout << endl;
280	>	for(int irow=0;irow<limits.size();irow++) {
281	>	for(int ientry=0;ientry<limits[irow].size();ientry++) {
282	>	if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
283	>	else dout << " (N/A) \t";
284		}
285	<	}//end of model scan for loop
285	>	dout << endl;
286	>	}
287
288	<	cout << "Exclusion Map contains" << exclusionmap->Integral() << " (integral) and entries: " << exclusionmap->GetEntries() << endl;
289	<	c3->cd();
290	<	exclusionmap->Draw("CONTZ");
291	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_Mean_values");
292	<	exclusionmap->Draw("COLZ");
293	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_Mean_values");
294	<
295	<	exclusionmap1s->Draw("CONTZ");
296	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_1sigma_values");
297	<	exclusionmap1s->Draw("COLZ");
298	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_1sigma_values");
299	<
300	<	exclusionmap2s->Draw("CONTZ");
301	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_2sigma_values");
302	<	exclusionmap2s->Draw("COLZ");
303	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_2sigma_values");
304	<
305	<	exclusionmap3s->Draw("CONTZ");
306	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_3sigma_values");
307	<	exclusionmap3s->Draw("COLZ");
308	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_3sigma_values");
309	<
310	<	TFile *exclusion_limits = new TFile("exclusion_limits.root","RECREATE");
311	<	exclusionmap->Write();
312	<	exclusionmap1s->Write();
313	<	exclusionmap2s->Write();
314	<	exclusionmap3s->Write();
315	<	exclusion_limits->Close();
316	<	susyscanfile->Close();
288	>	if(!doobserved) {
289	>	dout << endl << endl << "LIMITS: (Tex)" << endl;
290	>	tout << "\\begin{table}[hbtp]" << endl;
291	>	tout << "\\renewcommand{\arraystretch}{1.3}" << endl;
292	>	tout << "\\begin{center}" << endl;
293	>	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;
294	>	tout << "" << endl;
295	>	tout << "\\begin{tabular}{ | l | ";
296	>	for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
297	>	tout << "} " << endl << " \\hline " << endl << "& \t ";
298	>	for (int irow=0;irow<jzbcuts.size();irow++) {
299	>	tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
300	>	}
301	>	tout << " \\\\ \\hline " << endl;
302	>	for(int irow=0;irow<limits.size();irow++) {
303	>	tout << limits[irow][0] << " \t";
304	>	for(int ientry=0;ientry<jzbcuts.size();ientry++) {
305	>	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";
306	>	else tout << " & ( N / A ) \t";
307	>	//      dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
308	>	}
309	>	tout << " \\\\ \\hline " << endl;
310	>	}
311	>	tout << "\\end{tabular}" << endl;
312	>	tout << "      \\end{tabular}"<< endl;
313	>	tout << "\\end{center}"<< endl;
314	>	tout << "\\end{table} "<< endl;
315	>
316	>	}//do observed
317	>
318	>	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;
319	>	dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
320	>	for(int icut=0;icut<jzbcuts.size();icut++) {
321	>	dout << "Region with JZB>" << jzbcuts[icut] << (ConsiderSignalContaminationForLimits?"  (accounting for signal contamination)":"  (not accounting for signal contamination)") << endl;
322	>	for(int isample=0;isample<signalsamples.collection.size();isample++) {
323	>	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;
324	>	}
325	>	dout << endl;
326	>	}
327
328	<	myfile.close();
328	>	write_warning(__FUNCTION__,"Still need to update the script");
329		}
330
331
332	+
333	+	/********************************************************************** new : Limits using SHAPES ***********************************
334	+
335	+
336	+	SSSSSSSSSSSSSSS hhhhhhh
337	+	SS:::::::::::::::Sh:::::h
338	+	S:::::SSSSSS::::::Sh:::::h
339	+	S:::::S     SSSSSSSh:::::h
340	+	S:::::S             h::::h hhhhh         aaaaaaaaaaaaa  ppppp   ppppppppp       eeeeeeeeeeee        ssssssssss
341	+	S:::::S             h::::hh:::::hhh      a::::::::::::a p::::ppp:::::::::p    ee::::::::::::ee    ss::::::::::s
342	+	S::::SSSS          h::::::::::::::hh    aaaaaaaaa:::::ap:::::::::::::::::p  e::::::eeeee:::::eess:::::::::::::s
343	+	SS::::::SSSSS     h:::::::hhh::::::h            a::::app::::::ppppp::::::pe::::::e     e:::::es::::::ssss:::::s
344	+	SSS::::::::SS   h::::::h   h::::::h    aaaaaaa:::::a p:::::p     p:::::pe:::::::eeeee::::::e s:::::s  ssssss
345	+	SSSSSS::::S  h:::::h     h:::::h  aa::::::::::::a p:::::p     p:::::pe:::::::::::::::::e    s::::::s
346	+	S:::::S h:::::h     h:::::h a::::aaaa::::::a p:::::p     p:::::pe::::::eeeeeeeeeee        s::::::s
347	+	S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::p    p::::::pe:::::::e           ssssss   s:::::s
348	+	SSSSSSS     S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::ppppp:::::::pe::::::::e          s:::::ssss::::::s
349	+	S::::::SSSSSS:::::S h:::::h     h:::::ha:::::aaaa::::::a p::::::::::::::::p  e::::::::eeeeeeee  s::::::::::::::s
350	+	S:::::::::::::::SS  h:::::h     h:::::h a::::::::::aa:::ap::::::::::::::pp    ee:::::::::::::e   s:::::::::::ss
351	+	SSSSSSSSSSSSSSS    hhhhhhh     hhhhhhh  aaaaaaaaaa  aaaap::::::pppppppp        eeeeeeeeeeeeee    sssssssssss
352	+	p:::::p
353	+	p:::::p
354	+	p:::::::p
355	+	p:::::::p
356	+	p:::::::p
357	+	ppppppppp
358	+
359	+
360	+	*********************************************************************** new : Limits using SHAPES ***********************************/
361	+
362	+
363	+	void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
364	+	dout << "Creatig shape templates ... ";
365	+	if(identifier!="") dout << "for systematic called "<<identifier;
366	+	dout << endl;
367	+	int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
368	+	if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
369	+
370	+	TCut limitnJetcut;
371	+	if(JES==noJES) limitnJetcut=cutnJets;
372	+	else {
373	+	if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
374	+	if(JES==JESup) limitnJetcut=cutnJetsJESup;
375	+	}
376	+	TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
377	+	TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
378	+	TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
379	+	TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
380	+
381	+	TH1F *SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
382	+	TH1F *SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
383	+	TH1F *SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
384	+	TH1F *SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
385	+
386	+	TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
387	+	TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
388	+	TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
389	+	TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
390	+
391	+	TH1F *LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
392	+	TH1F *LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
393	+	TH1F *LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
394	+	TH1F *LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
395	+
396	+	string obsname="data_obs";
397	+	string predname="background";
398	+	string signalname="signal";
399	+	if(identifier!="") {
400	+	obsname=("data_"+identifier);
401	+	predname=("background_"+identifier);
402	+	signalname="signal_"+identifier;
403	+	}
404	+
405	+	TH1F *obs = (TH1F*)ZOSSFP->Clone();
406	+	obs->SetName(obsname.c_str());
407	+	obs->Write();
408	+	TH1F *pred = (TH1F*)ZOSSFN->Clone();
409	+	pred->Add(ZOSOFP,1.0/3);
410	+	pred->Add(ZOSOFN,-1.0/3);
411	+	pred->Add(SBOSSFP,1.0/3);
412	+	pred->Add(SBOSSFN,-1.0/3);
413	+	pred->Add(SBOSOFP,1.0/3);
414	+	pred->Add(SBOSOFN,-1.0/3);
415	+	pred->SetName(predname.c_str());
416	+	pred->Write();
417	+
418	+	//  TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
419	+	//  TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
420	+
421	+	TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
422	+	TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
423	+	Lobs->Add(LZOSSFP);
424	+	Lpred->Add(LZOSSFN);
425	+	Lpred->Add(LZOSOFP,1.0/3);
426	+	Lpred->Add(LZOSOFN,-1.0/3);
427	+	Lpred->Add(LSBOSSFP,1.0/3);
428	+	Lpred->Add(LSBOSSFN,-1.0/3);
429	+	Lpred->Add(LSBOSOFP,1.0/3);
430	+	Lpred->Add(LSBOSOFN,-1.0/3);
431	+	TH1F *signal = (TH1F*)Lobs->Clone();
432	+	signal->Add(Lpred,-1);
433	+	signal->SetName(signalname.c_str());
434	+	signal->Write();
435	+
436	+	delete Lobs;
437	+	delete Lpred;
438	+
439	+	delete ZOSSFP;
440	+	delete ZOSOFP;
441	+	delete ZOSSFN;
442	+	delete ZOSOFN;
443	+
444	+	delete SBOSSFP;
445	+	delete SBOSOFP;
446	+	delete SBOSSFN;
447	+	delete SBOSOFN;
448	+
449	+	delete LZOSSFP;
450	+	delete LZOSOFP;
451	+	delete LZOSSFN;
452	+	delete LZOSOFN;
453	+
454	+	delete LSBOSSFP;
455	+	delete LSBOSOFP;
456	+	delete LSBOSSFN;
457	+	delete LSBOSOFN;
458	+
459	+	}
460
461	+	void prepare_datacard(TFile *f) {
462	+	TH1F *dataob = (TH1F*)f->Get("data_obs");
463	+	TH1F *signal = (TH1F*)f->Get("signal");
464	+	TH1F *background = (TH1F*)f->Get("background");
465
466	+	ofstream datacard;
467	+	ensure_directory_exists(get_directory()+"/limits");
468	+	datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
469	+	datacard << "Writing this to a file.\n";
470	+	datacard << "imax 1\n";
471	+	datacard << "jmax 1\n";
472	+	datacard << "kmax *\n";
473	+	datacard << "---------------\n";
474	+	datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
475	+	datacard << "---------------\n";
476	+	datacard << "bin 1\n";
477	+	datacard << "observation "<<dataob->Integral()<<"\n";
478	+	datacard << "------------------------------\n";
479	+	datacard << "bin             1          1\n";
480	+	datacard << "process         signal     background\n";
481	+	datacard << "process         0          1\n";
482	+	datacard << "rate            "<<signal->Integral()<<"         "<<background->Integral()<<"\n";
483	+	datacard << "--------------------------------\n";
484	+	datacard << "lumi     lnN    1.10       1.0\n";
485	+	datacard << "bgnorm   lnN    1.00       1.4  uncertainty on our prediction (40%)\n";
486	+	datacard << "JES    shape    1          1    uncertainty on background shape and normalization\n";
487	+	datacard << "peak   shape    1          1    uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
488	+	datacard << "#                                so divide the unit gaussian by 2 before doing the interpolation\n";
489	+	datacard.close();
490	+	}
491	+
492	+
493	+	void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
494	+	ensure_directory_exists(get_directory()+"/limits");
495	+	TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
496	+	TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
497	+	limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
498	+	limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
499	+	limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
500	+	limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
501	+	limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
502	+
503	+	prepare_datacard(limfile);
504	+	limfile->Close();
505	+	write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
506	+
507	+	}

Diff Legend

–	Removed lines
+	Added lines
<	Changed lines
>	Changed lines