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Comparing UserCode/cbrown/AnalysisFramework/Plotting/Modules/LimitCalculation.C (file contents):
Revision 1.3 by buchmann, Wed Jul 20 08:52:17 2011 UTC vs.
Revision 1.12 by buchmann, Fri Aug 26 10:37:21 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 167 | Line 168 | ratio_binning.push_back(80);
168
169		}
170
170	–	void calculate_upper_limits(string mcjzb, string datajzb) {
171	–	write_warning("calculate_upper_limits","Upper limit calculation temporarily deactivated");
172	–	//  write_warning("calculate_upper_limits","Calculation of SUSY upper limits has been temporarily suspended in favor of top discovery");
173	–	//  rediscover_the_top(mcjzb,datajzb);
174	–	/*
175	–	TCanvas *c3 = new TCanvas("c3","c3");
176	–	c3->SetLogy(1);
177	–	vector<float> binning;
178	–	//binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
179	–	binning.push_back(50);
180	–	binning.push_back(100);
181	–	binning.push_back(150);
182	–	binning.push_back(200);
183	–	binning.push_back(500);
184	–	TH1F *datapredictiona = allsamples.Draw("datapredictiona",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity);
185	–	TH1F *datapredictionb = allsamples.Draw("datapredictionb",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
186	–	TH1F *datapredictionc = allsamples.Draw("datapredictionc",    datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
187	–	TH1F *dataprediction = (TH1F*)datapredictiona->Clone();
188	–	dataprediction->Add(datapredictionb,-1);
189	–	dataprediction->Add(datapredictionc);
190	–	TH1F *puresignal     = allsamples.Draw("puresignal",        mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
191	–	TH1F *signalpred     = allsamples.Draw("signalpred",    "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
192	–	TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
193	–	TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
194	–	TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
195	–	signalpred->Add(signalpredlo,-1);
196	–	signalpred->Add(signalpredro);
197	–	puresignal->Add(signalpred,-1);//subtracting signal contamination
198	–	ofstream myfile;
199	–	myfile.open ("ShapeFit_log.txt");
200	–	establish_upper_limits(puredata,dataprediction,puresignal,"LM4",myfile);
201	–	myfile.close();
202	–	*/
203	–	}
204	–
171		vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, bool doobserved=false) {
172	<	float sigma95=0.0,sigma95A=0.0;
173	<	dout << "Now calling : CL95(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << 1<< ") " << endl;
174	<	sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, 1);
172	>	float sigma95=-9.9,sigma95A=-9.9;
173	>	int nuisancemodel=1;
174	>	if(mceff<=0) {
175	>	write_warning(__FUNCTION__,"Cannot compute upper limit in this configuration as the efficiency is negative:");
176	>	dout << "mc efficiency=" << mceff << " +/- " << mcefferr;
177	>	vector<float> sigmas;
178	>	sigmas.push_back(-1);
179	>	sigmas.push_back(-1);
180	>	return sigmas;
181	>	} else {
182	>	dout << "Now calling : CL95(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
183	>	sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, nuisancemodel);
184		if(doobserved) {
185	<	dout << "Now calling : CL95A(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << 1<< ") " << endl;
186	<	sigma95A = CLA(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], 1);
185	>	dout << "Now calling : CLA(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << nuisancemodel<< ") " << endl;
186	>	sigma95A = CLA(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], nuisancemodel);
187		}
188		vector<float> sigmas;
189		sigmas.push_back(sigma95);
190		sigmas.push_back(sigma95A);
191		return sigmas;
192	+	}
193		}
194
195		void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doobserved) {
#	Line 234 | Line 210 | void compute_upper_limits_from_counting_
210		float staterr=uncertainties[isample*jzbcuts.size()+ibin][2];
211		float systerr=uncertainties[isample*jzbcuts.size()+ibin][3];
212		float toterr =uncertainties[isample*jzbcuts.size()+ibin][4];
213	<	float observed,null,result;
214	<	fill_result_histos(observed, null,null,null,null,null,null,null,mcjzb,JZBcutat,(int)5,result,(signalsamples.FindSample(signalsamples.collection[isample].filename)),signalsamples);
215	<	observed-=result;//this is the actual excess we see!
216	<	float expected=observed/luminosity;
213	>	float observed,observederr,null,result;
214	>
215	>	//      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);
216	>	//      observed-=result;//this is the actual excess we see!
217	>	//      float expected=observed/luminosity;
218
219		dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
220		vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,doobserved);
221
222		if(doobserved) {
223	<	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
223	>	//      rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
224	>	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
225		vrows.push_back(sigmas[0]);
226		vrows.push_back(sigmas[1]);
227	<	vrows.push_back(expected);
227	>	//      vrows.push_back(expected);
228	>	vrows.push_back(signalsamples.collection[isample].xs);
229		}
230		else {
231	<	rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
231	>	//      rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
232	>	rows.push_back(any2string(sigmas[0]));
233		vrows.push_back(sigmas[0]);
234	<	vrows.push_back(expected);
234	>	vrows.push_back(signalsamples.collection[isample].xs);
235	>	//      vrows.push_back(expected);
236		}
237		}//end of bin loop
238		limits.push_back(rows);
239		vlimits.push_back(vrows);
240		}//end of sample loop
241	<	dout << endl << endl << "PAS table 3: " << endl << endl;
241	>	dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
242	>	dout << endl << endl << "PAS table 3:   (notation: limit [95%CL])" << endl << endl;
243		dout << "\t";
244		for (int irow=0;irow<jzbcuts.size();irow++) {
245		dout << jzbcuts[irow] << "\t";
#	Line 265 | Line 247 | void compute_upper_limits_from_counting_
247		dout << endl;
248		for(int irow=0;irow<limits.size();irow++) {
249		for(int ientry=0;ientry<limits[irow].size();ientry++) {
250	<	dout << limits[irow][ientry] << "\t";
250	>	if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
251	>	else dout << " (N/A) \t";
252		}
253		dout << endl;
254		}
255
256		if(!doobserved) {
257	<	dout << endl << endl << "LIMITS: " << endl;
258	<	dout << "\t";
257	>	dout << endl << endl << "LIMITS: (Tex)" << endl;
258	>	tout << "\\begin{tabular}{ | l | ";
259	>	for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
260	>	tout << "} " << endl << " \\hline " << endl << "& \t ";
261		for (int irow=0;irow<jzbcuts.size();irow++) {
262	<	dout << jzbcuts[irow] << "\t";
262	>	tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
263		}
264	<	dout << endl;
264	>	tout << " \\\\ \\hline " << endl;
265		for(int irow=0;irow<limits.size();irow++) {
266	<	dout << limits[irow][0] << "\t";
266	>	tout << limits[irow][0] << " \t";
267		for(int ientry=0;ientry<jzbcuts.size();ientry++) {
268	<	dout << Round(vlimits[irow][2*ientry] / vlimits[irow][2*ientry+1],3)<< "\t";
268	>	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";
269	>	else tout << " & ( N / A ) \t";
270	>	//      dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
271		}
272	<	dout << endl;
272	>	tout << " \\\\ \\hline " << endl;
273		}
274	+	tout << "\\end{tabular}" << endl;
275		}//do observed
276
277		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;
278	<	dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t Prediction [pb]" << endl;
278	>	dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
279		for(int icut=0;icut<jzbcuts.size();icut++) {
280		dout << "Region with JZB>" << jzbcuts[icut] << endl;
281		for(int isample=0;isample<signalsamples.collection.size();isample++) {
282	<	dout << limits[icut][0] << "\t" << Round(100*uncertainties[isample*jzbcuts.size()+icut][1],1) << "+/-" << Round(100*uncertainties[isample*jzbcuts.size()+icut][2],1) << " (stat) +/- " << Round(100*uncertainties[isample*jzbcuts.size()+icut][3],1) << " (syst) \t" << Round((vlimits[isample][2*icut]),3) << "\t" << Round(vlimits[isample][2*icut+1],3) << endl;
282	>	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;
283		}
284		dout << endl;
285		}
286	+
287	+	write_warning(__FUNCTION__,"Still need to update the script");
288		}
289
300	–	void susy_scan_axis_labeling(TH2F *histo) {
301	–	histo->GetXaxis()->SetTitle("#Chi_{2}^{0}-LSP");
302	–	histo->GetXaxis()->CenterTitle();
303	–	histo->GetYaxis()->SetTitle("m_{#tilde{q}}");
304	–	histo->GetYaxis()->CenterTitle();
305	–	}
290
291	<	void scan_susy_space(string mcjzb, string datajzb) {
292	<	TCanvas *c3 = new TCanvas("c3","c3");
293	<	vector<float> binning;
294	<	binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
295	<	float arrbinning[binning.size()];
296	<	for(int i=0;i<binning.size();i++) arrbinning[i]=binning[i];
297	<	TH1F *puredata   = allsamples.Draw("puredata",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
298	<	puredata->SetMarkerSize(DataMarkerSize);
299	<	TH1F *allbgs   = allsamples.Draw("allbgs",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
300	<	TH1F *allbgsb   = allsamples.Draw("allbgsb",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
301	<	TH1F *allbgsc   = allsamples.Draw("allbgsc",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
302	<	allbgs->Add(allbgsb,-1);
303	<	allbgs->Add(allbgsc);
304	<	int ndata=puredata->Integral();
305	<	ofstream myfile;
306	<	myfile.open ("susyscan_log.txt");
307	<	TFile *susyscanfile = new TFile("/scratch/fronga/SMS/T5z_SqSqToQZQZ_38xFall10.root");
308	<	TTree *suevents = (TTree*)susyscanfile->Get("events");
309	<	TH2F *exclusionmap = new TH2F("exclusionmap","",20,0,500,20,0,1000);
310	<	TH2F *exclusionmap1s = new TH2F("exclusionmap1s","",20,0,500,20,0,1000);
311	<	TH2F *exclusionmap2s = new TH2F("exclusionmap2s","",20,0,500,20,0,1000);
312	<	TH2F *exclusionmap3s = new TH2F("exclusionmap3s","",20,0,500,20,0,1000);
313	<
314	<	susy_scan_axis_labeling(exclusionmap);
315	<	susy_scan_axis_labeling(exclusionmap1s);
316	<	susy_scan_axis_labeling(exclusionmap2s);
317	<	susy_scan_axis_labeling(exclusionmap3s);
318	<
319	<	Int_t MyPalette[100];
320	<	Double_t r[]    = {0., 0.0, 1.0, 1.0, 1.0};
321	<	Double_t g[]    = {0., 0.0, 0.0, 1.0, 1.0};
322	<	Double_t b[]    = {0., 1.0, 0.0, 0.0, 1.0};
323	<	Double_t stop[] = {0., .25, .50, .75, 1.0};
324	<	Int_t FI = TColor::CreateGradientColorTable(5, stop, r, g, b, 100);
325	<	for (int i=0;i<100;i++) MyPalette[i] = FI+i;
326	<
327	<	gStyle->SetPalette(100, MyPalette);
344	<
345	<	for(int m23=50;m23<500;m23+=25) {
346	<	for (int m0=(2*(m23-50)+150);m0<=1000;m0+=50)
347	<	{
348	<	c3->cd();
349	<	stringstream drawcondition;
350	<	drawcondition << "pfJetGoodNum>=3&&(TMath::Abs(masses[0]-"<<m0<<")<10&&TMath::Abs(masses[2]-masses[3]-"<<m23<<")<10)&&mll>5&&id1==id2";
351	<	TH1F *puresignal = new TH1F("puresignal","puresignal",binning.size()-1,arrbinning);
352	<	TH1F *puresignall= new TH1F("puresignall","puresignal",binning.size()-1,arrbinning);
353	<	stringstream drawvar,drawvar2;
354	<	drawvar<<mcjzb<<">>puresignal";
355	<	drawvar2<<"-"<<mcjzb<<">>puresignall";
356	<	suevents->Draw(drawvar.str().c_str(),drawcondition.str().c_str());
357	<	suevents->Draw(drawvar2.str().c_str(),drawcondition.str().c_str());
358	<	if(puresignal->Integral()<60) {
359	<	delete puresignal;
360	<	continue;
361	<	}
362	<	puresignal->Add(puresignall,-1);//we need to correct for the signal contamination - we effectively only see (JZB>0)-(JZB<0) !!
363	<	puresignal->Scale(ndata/(20*puresignal->Integral()));//normalizing it to 5% of the data
364	<	stringstream saveas;
365	<	saveas<<"Model_Scan/m0_"<<m0<<"__m23_"<<m23;
366	<	dout << "PLEASE KEEP IN MIND THAT SIGNAL CONTAMINATION IS NOT REALLY TAKEN CARE OF YET DUE TO LOW STATISTICS! SHOULD BE SOMETHING LIKE THIS : "<< endl;
367	<	//        TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
368	<	//        TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
369	<	//        TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
370	<	//        signalpred->Add(signalpredlo,-1);
371	<	//        signalpred->Add(signalpredro);
372	<	//        puresignal->Add(signalpred,-1);//subtracting signal contamination
373	<	//---------------------
374	<	//      dout << "(m0,m23)=("<<m0<<","<<m23<<") contains " << puresignal->Integral() << endl;
375	<	//    TH1F *puresignal = allsamples.Draw("puresignal",mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
376	<	vector<float> results=establish_upper_limits(puredata,allbgs,puresignal,saveas.str(),myfile);
377	<	if(results.size()==0) {
378	<	delete puresignal;
379	<	continue;
380	<	}
381	<	exclusionmap->Fill(m23,m0,results[0]);
382	<	exclusionmap1s->Fill(m23,m0,results[1]);
383	<	exclusionmap2s->Fill(m23,m0,results[2]);
384	<	exclusionmap3s->Fill(m23,m0,results[3]);
385	<	delete puresignal;
386	<	dout << "(m0,m23)=("<<m0<<","<<m23<<") : 3 sigma at " << results[3] << endl;
387	<	}
388	<	}//end of model scan for loop
291	>
292	>	/********************************************************************** new : Limits using SHAPES ***********************************
293	>
294	>
295	>	SSSSSSSSSSSSSSS hhhhhhh
296	>	SS:::::::::::::::Sh:::::h
297	>	S:::::SSSSSS::::::Sh:::::h
298	>	S:::::S     SSSSSSSh:::::h
299	>	S:::::S             h::::h hhhhh         aaaaaaaaaaaaa  ppppp   ppppppppp       eeeeeeeeeeee        ssssssssss
300	>	S:::::S             h::::hh:::::hhh      a::::::::::::a p::::ppp:::::::::p    ee::::::::::::ee    ss::::::::::s
301	>	S::::SSSS          h::::::::::::::hh    aaaaaaaaa:::::ap:::::::::::::::::p  e::::::eeeee:::::eess:::::::::::::s
302	>	SS::::::SSSSS     h:::::::hhh::::::h            a::::app::::::ppppp::::::pe::::::e     e:::::es::::::ssss:::::s
303	>	SSS::::::::SS   h::::::h   h::::::h    aaaaaaa:::::a p:::::p     p:::::pe:::::::eeeee::::::e s:::::s  ssssss
304	>	SSSSSS::::S  h:::::h     h:::::h  aa::::::::::::a p:::::p     p:::::pe:::::::::::::::::e    s::::::s
305	>	S:::::S h:::::h     h:::::h a::::aaaa::::::a p:::::p     p:::::pe::::::eeeeeeeeeee        s::::::s
306	>	S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::p    p::::::pe:::::::e           ssssss   s:::::s
307	>	SSSSSSS     S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::ppppp:::::::pe::::::::e          s:::::ssss::::::s
308	>	S::::::SSSSSS:::::S h:::::h     h:::::ha:::::aaaa::::::a p::::::::::::::::p  e::::::::eeeeeeee  s::::::::::::::s
309	>	S:::::::::::::::SS  h:::::h     h:::::h a::::::::::aa:::ap::::::::::::::pp    ee:::::::::::::e   s:::::::::::ss
310	>	SSSSSSSSSSSSSSS    hhhhhhh     hhhhhhh  aaaaaaaaaa  aaaap::::::pppppppp        eeeeeeeeeeeeee    sssssssssss
311	>	p:::::p
312	>	p:::::p
313	>	p:::::::p
314	>	p:::::::p
315	>	p:::::::p
316	>	ppppppppp
317	>
318	>
319	>	*********************************************************************** new : Limits using SHAPES ***********************************/
320	>
321	>
322	>	void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
323	>	dout << "Creatig shape templates ... ";
324	>	if(identifier!="") dout << "for systematic called "<<identifier;
325	>	dout << endl;
326	>	int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
327	>	if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
328
329	<	dout << "Exclusion Map contains" << exclusionmap->Integral() << " (integral) and entries: " << exclusionmap->GetEntries() << endl;
330	<	c3->cd();
331	<	exclusionmap->Draw("CONTZ");
332	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_Mean_values");
333	<	exclusionmap->Draw("COLZ");
334	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_Mean_values");
335	<
336	<	exclusionmap1s->Draw("CONTZ");
337	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_1sigma_values");
338	<	exclusionmap1s->Draw("COLZ");
339	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_1sigma_values");
340	<
341	<	exclusionmap2s->Draw("CONTZ");
342	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_2sigma_values");
343	<	exclusionmap2s->Draw("COLZ");
344	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_2sigma_values");
345	<
346	<	exclusionmap3s->Draw("CONTZ");
347	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_3sigma_values");
348	<	exclusionmap3s->Draw("COLZ");
349	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_3sigma_values");
350	<
351	<	TFile *exclusion_limits = new TFile("exclusion_limits.root","RECREATE");
352	<	exclusionmap->Write();
353	<	exclusionmap1s->Write();
354	<	exclusionmap2s->Write();
355	<	exclusionmap3s->Write();
356	<	exclusion_limits->Close();
357	<	susyscanfile->Close();
329	>	TCut limitnJetcut;
330	>	if(JES==noJES) limitnJetcut=cutnJets;
331	>	else {
332	>	if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
333	>	if(JES==JESup) limitnJetcut=cutnJetsJESup;
334	>	}
335	>	TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
336	>	TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
337	>	TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
338	>	TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
339	>
340	>	TH1F *SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
341	>	TH1F *SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
342	>	TH1F *SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
343	>	TH1F *SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
344	>
345	>	TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
346	>	TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
347	>	TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
348	>	TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
349	>
350	>	TH1F *LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
351	>	TH1F *LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
352	>	TH1F *LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
353	>	TH1F *LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
354	>
355	>	string obsname="data_obs";
356	>	string predname="background";
357	>	string signalname="signal";
358	>	if(identifier!="") {
359	>	obsname=("data_"+identifier);
360	>	predname=("background_"+identifier);
361	>	signalname="signal_"+identifier;
362	>	}
363
364	<	myfile.close();
364	>	TH1F *obs = (TH1F*)ZOSSFP->Clone();
365	>	obs->SetName(obsname.c_str());
366	>	obs->Write();
367	>	TH1F *pred = (TH1F*)ZOSSFN->Clone();
368	>	pred->Add(ZOSOFP,1.0/3);
369	>	pred->Add(ZOSOFN,-1.0/3);
370	>	pred->Add(SBOSSFP,1.0/3);
371	>	pred->Add(SBOSSFN,-1.0/3);
372	>	pred->Add(SBOSOFP,1.0/3);
373	>	pred->Add(SBOSOFN,-1.0/3);
374	>	pred->SetName(predname.c_str());
375	>	pred->Write();
376	>
377	>	//  TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
378	>	//  TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
379	>
380	>	TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
381	>	TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
382	>	Lobs->Add(LZOSSFP);
383	>	Lpred->Add(LZOSSFN);
384	>	Lpred->Add(LZOSOFP,1.0/3);
385	>	Lpred->Add(LZOSOFN,-1.0/3);
386	>	Lpred->Add(LSBOSSFP,1.0/3);
387	>	Lpred->Add(LSBOSSFN,-1.0/3);
388	>	Lpred->Add(LSBOSOFP,1.0/3);
389	>	Lpred->Add(LSBOSOFN,-1.0/3);
390	>	TH1F *signal = (TH1F*)Lobs->Clone();
391	>	signal->Add(Lpred,-1);
392	>	signal->SetName(signalname.c_str());
393	>	signal->Write();
394	>
395	>	delete Lobs;
396	>	delete Lpred;
397	>
398	>	delete ZOSSFP;
399	>	delete ZOSOFP;
400	>	delete ZOSSFN;
401	>	delete ZOSOFN;
402	>
403	>	delete SBOSSFP;
404	>	delete SBOSOFP;
405	>	delete SBOSSFN;
406	>	delete SBOSOFN;
407	>
408	>	delete LZOSSFP;
409	>	delete LZOSOFP;
410	>	delete LZOSSFN;
411	>	delete LZOSOFN;
412	>
413	>	delete LSBOSSFP;
414	>	delete LSBOSOFP;
415	>	delete LSBOSSFN;
416	>	delete LSBOSOFN;
417	>
418		}
419
420	+	void prepare_datacard(TFile *f) {
421	+	TH1F *dataob = (TH1F*)f->Get("data_obs");
422	+	TH1F *signal = (TH1F*)f->Get("signal");
423	+	TH1F *background = (TH1F*)f->Get("background");
424	+
425	+	ofstream datacard;
426	+	ensure_directory_exists(get_directory()+"/limits");
427	+	datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
428	+	datacard << "Writing this to a file.\n";
429	+	datacard << "imax 1\n";
430	+	datacard << "jmax 1\n";
431	+	datacard << "kmax *\n";
432	+	datacard << "---------------\n";
433	+	datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
434	+	datacard << "---------------\n";
435	+	datacard << "bin 1\n";
436	+	datacard << "observation "<<dataob->Integral()<<"\n";
437	+	datacard << "------------------------------\n";
438	+	datacard << "bin             1          1\n";
439	+	datacard << "process         signal     background\n";
440	+	datacard << "process         0          1\n";
441	+	datacard << "rate            "<<signal->Integral()<<"         "<<background->Integral()<<"\n";
442	+	datacard << "--------------------------------\n";
443	+	datacard << "lumi     lnN    1.10       1.0\n";
444	+	datacard << "bgnorm   lnN    1.00       1.4  uncertainty on our prediction (40%)\n";
445	+	datacard << "JES    shape    1          1    uncertainty on background shape and normalization\n";
446	+	datacard << "peak   shape    1          1    uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
447	+	datacard << "#                                so divide the unit gaussian by 2 before doing the interpolation\n";
448	+	datacard.close();
449	+	}
450
451
452	<
452	>	void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
453	>	ensure_directory_exists(get_directory()+"/limits");
454	>	TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
455	>	TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
456	>	limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
457	>	limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
458	>	limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
459	>	limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
460	>	limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
461	>
462	>	prepare_datacard(limfile);
463	>	limfile->Close();
464	>	write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
465	>
466	>	}

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