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Comparing UserCode/cbrown/AnalysisFramework/Plotting/Modules/LimitCalculation.C (file contents):
Revision 1.2 by buchmann, Tue Jul 19 15:04:16 2011 UTC vs.
Revision 1.25 by buchmann, Mon Sep 26 15:48:20 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 14 | Line 15
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;
#	Line 22 | Line 25 | using namespace PlottingSetup;
25
26
27		void rediscover_the_top(string mcjzb, string datajzb) {
28	<	cout << "Hi! today we are going to (try to) rediscover the top!" << endl;
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;
#	Line 62 | Line 65 | void rediscover_the_top(string mcjzb, st
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	<	cout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
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);
#	Line 141 | Line 144 | ratio_binning.push_back(80);
144		ratio->Divide(datapredictiontb);
145
146		for (int i=0;i<=ratio_binning.size();i++) {
147	<	cout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
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);
#	Line 167 | Line 170 | ratio_binning.push_back(80);
170
171		}
172
173	<	void calculate_upper_limits(string mcjzb, string datajzb) {
174	<	write_warning("calculate_upper_limits","Upper limit calculation temporarily deactivated");
175	<	//  write_warning("calculate_upper_limits","Calculation of SUSY upper limits has been temporarily suspended in favor of top discovery");
176	<	//  rediscover_the_top(mcjzb,datajzb);
177	<	/*
178	<	TCanvas *c3 = new TCanvas("c3","c3");
179	<	c3->SetLogy(1);
180	<	vector<float> binning;
181	<	//binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
182	<	binning.push_back(50);
183	<	binning.push_back(100);
184	<	binning.push_back(150);
185	<	binning.push_back(200);
186	<	binning.push_back(500);
187	<	TH1F *datapredictiona = allsamples.Draw("datapredictiona",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity);
188	<	TH1F *datapredictionb = allsamples.Draw("datapredictionb",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
189	<	TH1F *datapredictionc = allsamples.Draw("datapredictionc",    datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
190	<	TH1F *dataprediction = (TH1F*)datapredictiona->Clone();
191	<	dataprediction->Add(datapredictionb,-1);
192	<	dataprediction->Add(datapredictionc);
193	<	TH1F *puresignal     = allsamples.Draw("puresignal",        mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
194	<	TH1F *signalpred     = allsamples.Draw("signalpred",    "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
195	<	TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
196	<	TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
197	<	TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
198	<	signalpred->Add(signalpredlo,-1);
199	<	signalpred->Add(signalpredro);
200	<	puresignal->Add(signalpred,-1);//subtracting signal contamination
201	<	ofstream myfile;
202	<	myfile.open ("ShapeFit_log.txt");
203	<	establish_upper_limits(puredata,dataprediction,puresignal,"LM4",myfile);
204	<	myfile.close();
205	<	*/
206	<	}
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	>	stringstream command;
219	>	command << PlottingSetup::cbafbasedir << "/DistributedModelCalculations/Limits/NewLimitCapsule.exec " << repname.str() << " " << luminosity << " " << luminosity*lumiuncert << " " << mceff << " " << mcefferr << " " << Npred[ibin] << " " << Nprederr[ibin] << " " << Nobs[ibin] << " " << -1 << " " << PlottingSetup::basedirectory << "/" << plotfilename << " " << doexpected;
220	>	dout << command.str() << endl;
221	>
222	>	int retval = 256;
223	>	int attempts=0;
224	>	while(!(retval==0||attempts>=5)) {//try up to 5 times
225	>	attempts++;
226	>	dout << "Starting limit calculation (LimitCapsule) now : Attempt " << attempts << endl;
227	>	retval=gSystem->Exec(command.str().c_str());
228	>	}
229	>
230	>	LimitDroplet limres;
231	>	limres.readDroplet(repname.str());
232	>	dout << limres << endl;
233	>	remove(repname.str().c_str());
234	>	sigma95=limres.observed;
235
236	<	vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, bool doobserved=false) {
237	<	float sigma95=0.0,sigma95A=0.0;
207	<	cout << "Now calling : CL95(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << 1<< ") " << endl;
208	<	sigma95 = CL95(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], Nobs[ibin], false, 1);
209	<	if(doobserved) {
210	<	cout << "Now calling : CL95A(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << 1<< ") " << endl;
211	<	sigma95A = CLA(luminosity, lumiuncert*luminosity, mceff, mcefferr, Npred[ibin], Nprederr[ibin], 1);
212	<	}
236	>
237	>	///------------------------------------------ < /NEW > ----------------------------------------------------------
238		vector<float> sigmas;
239		sigmas.push_back(sigma95);
240	<	sigmas.push_back(sigma95A);
240	>	if(doexpected) {
241	>	sigmas.push_back(limres.expected);
242	>	sigmas.push_back(limres.upper68);
243	>	sigmas.push_back(limres.lower68);
244	>	sigmas.push_back(limres.upper95);
245	>	sigmas.push_back(limres.lower95);
246	>	}
247	>
248		return sigmas;
249	+
250	+
251	+	}//end of mc efficiency is ok
252		}
253
254	<	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doobserved) {
255	<	cout << "Doing counting experiment ... " << endl;
254	>	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doexpected) {
255	>	dout << "Doing counting experiment ... " << endl;
256		vector<vector<string> > limits;
257		vector<vector<float> > vlimits;
258
#	Line 225 | Line 260 | void compute_upper_limits_from_counting_
260		for(int isample=0;isample<signalsamples.collection.size();isample++) {
261		vector<string> rows;
262		vector<float> vrows;
263	<	cout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
263	>	dout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
264		rows.push_back(signalsamples.collection[isample].samplename);
265		for(int ibin=0;ibin<jzbcuts.size();ibin++) {
266	<	cout << "_________________________________________________________________________________" << endl;
266	>	dout << "_________________________________________________________________________________" << endl;
267		float JZBcutat=uncertainties[isample*jzbcuts.size()+ibin][0];
268		float mceff=uncertainties[isample*jzbcuts.size()+ibin][1];
269		float staterr=uncertainties[isample*jzbcuts.size()+ibin][2];
270		float systerr=uncertainties[isample*jzbcuts.size()+ibin][3];
271		float toterr =uncertainties[isample*jzbcuts.size()+ibin][4];
272	<	float observed,null,result;
238	<	fill_result_histos(observed, null,null,null,null,null,null,null,mcjzb,JZBcutat,(int)5,result,(signalsamples.FindSample(signalsamples.collection[isample].filename)),signalsamples);
239	<	observed-=result;//this is the actual excess we see!
240	<	float expected=observed/luminosity;
272	>	float observed,observederr,null,result;
273
274	<	cout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
275	<	vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,doobserved);
274	>	//      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);
275	>	//      observed-=result;//this is the actual excess we see!
276	>	//      float expected=observed/luminosity;
277	>	string plotfilename=(string)(TString(signalsamples.collection[isample].samplename)+TString("___JZB_geq_")+TString(any2string(JZBcutat))+TString(".png"));
278	>	dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
279	>	vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,plotfilename,doexpected);
280
281	<	if(doobserved) {
282	<	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
281	>	if(doexpected) {
282	>	//      rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
283	>	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
284		vrows.push_back(sigmas[0]);
285		vrows.push_back(sigmas[1]);
286	<	vrows.push_back(expected);
286	>	//      vrows.push_back(expected);
287	>	vrows.push_back(signalsamples.collection[isample].xs);
288		}
289		else {
290	<	rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
290	>	//      rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
291	>	rows.push_back(any2string(sigmas[0]));
292		vrows.push_back(sigmas[0]);
293	<	vrows.push_back(expected);
293	>	vrows.push_back(signalsamples.collection[isample].xs);
294	>	//      vrows.push_back(expected);
295		}
296		}//end of bin loop
297		limits.push_back(rows);
298		vlimits.push_back(vrows);
299		}//end of sample loop
300	<	cout << endl << endl << "PAS table 3: " << endl << endl;
301	<	cout << "\t";
300	>	dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
301	>	dout << endl << endl << "PAS table 3:   (notation: limit [95%CL])" << endl << endl;
302	>	dout << "\t";
303		for (int irow=0;irow<jzbcuts.size();irow++) {
304	<	cout << jzbcuts[irow] << "\t";
304	>	dout << jzbcuts[irow] << "\t";
305		}
306	<	cout << endl;
306	>	dout << endl;
307		for(int irow=0;irow<limits.size();irow++) {
308		for(int ientry=0;ientry<limits[irow].size();ientry++) {
309	<	cout << limits[irow][ientry] << "\t";
309	>	if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
310	>	else dout << " (N/A) \t";
311		}
312	<	cout << endl;
312	>	dout << endl;
313		}
314
315	<	if(!doobserved) {
316	<	cout << endl << endl << "LIMITS: " << endl;
317	<	cout << "\t";
315	>	if(!doexpected) {
316	>	dout << endl << endl << "LIMITS: (Tex)" << endl;
317	>	tout << "\\begin{table}[hbtp]" << endl;
318	>	tout << "\\renewcommand{\\arraystretch}{1.3}" << endl;
319	>	tout << "\\begin{center}" << endl;
320	>	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;
321	>	tout << "" << endl;
322	>	tout << "\\begin{tabular}{ | l | ";
323	>	for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
324	>	tout << "} " << endl << " \\hline " << endl << "& \t ";
325		for (int irow=0;irow<jzbcuts.size();irow++) {
326	<	cout << jzbcuts[irow] << "\t";
326	>	tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
327		}
328	<	cout << endl;
328	>	tout << " \\\\ \\hline " << endl;
329		for(int irow=0;irow<limits.size();irow++) {
330	<	cout << limits[irow][0] << "\t";
330	>	tout << limits[irow][0] << " \t";
331		for(int ientry=0;ientry<jzbcuts.size();ientry++) {
332	<	cout << Round(vlimits[irow][2*ientry] / vlimits[irow][2*ientry+1],3)<< "\t";
332	>	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";
333	>	else tout << " & ( N / A ) \t";
334	>	//      dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
335		}
336	<	cout << endl;
336	>	tout << " \\\\ \\hline " << endl;
337		}
338	+	tout << "\\end{tabular}" << endl;
339	+	tout << "      \\end{tabular}"<< endl;
340	+	tout << "\\end{center}"<< endl;
341	+	tout << "\\end{table} "<< endl;
342	+
343		}//do observed
344	+
345	+	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;
346	+	dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
347	+	for(int icut=0;icut<jzbcuts.size();icut++) {
348	+	dout << "Region with JZB>" << jzbcuts[icut] << (ConsiderSignalContaminationForLimits?"  (accounting for signal contamination)":"  (not accounting for signal contamination)") << endl;
349	+	for(int isample=0;isample<signalsamples.collection.size();isample++) {
350	+	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;
351	+	}
352	+	dout << endl;
353	+	}
354		}
355
290	–	void susy_scan_axis_labeling(TH2F *histo) {
291	–	histo->GetXaxis()->SetTitle("#Chi_{2}^{0}-LSP");
292	–	histo->GetXaxis()->CenterTitle();
293	–	histo->GetYaxis()->SetTitle("m_{#tilde{q}}");
294	–	histo->GetYaxis()->CenterTitle();
295	–	}
356
357	<	void scan_susy_space(string mcjzb, string datajzb) {
358	<	TCanvas *c3 = new TCanvas("c3","c3");
359	<	vector<float> binning;
360	<	binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
361	<	float arrbinning[binning.size()];
362	<	for(int i=0;i<binning.size();i++) arrbinning[i]=binning[i];
363	<	TH1F *puredata   = allsamples.Draw("puredata",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
364	<	puredata->SetMarkerSize(DataMarkerSize);
365	<	TH1F *allbgs   = allsamples.Draw("allbgs",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
366	<	TH1F *allbgsb   = allsamples.Draw("allbgsb",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
367	<	TH1F *allbgsc   = allsamples.Draw("allbgsc",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
368	<	allbgs->Add(allbgsb,-1);
369	<	allbgs->Add(allbgsc);
370	<	int ndata=puredata->Integral();
371	<	ofstream myfile;
372	<	myfile.open ("susyscan_log.txt");
373	<	TFile *susyscanfile = new TFile("/scratch/fronga/SMS/T5z_SqSqToQZQZ_38xFall10.root");
374	<	TTree *suevents = (TTree*)susyscanfile->Get("events");
375	<	TH2F *exclusionmap = new TH2F("exclusionmap","",20,0,500,20,0,1000);
376	<	TH2F *exclusionmap1s = new TH2F("exclusionmap1s","",20,0,500,20,0,1000);
377	<	TH2F *exclusionmap2s = new TH2F("exclusionmap2s","",20,0,500,20,0,1000);
378	<	TH2F *exclusionmap3s = new TH2F("exclusionmap3s","",20,0,500,20,0,1000);
379	<
380	<	susy_scan_axis_labeling(exclusionmap);
381	<	susy_scan_axis_labeling(exclusionmap1s);
382	<	susy_scan_axis_labeling(exclusionmap2s);
383	<	susy_scan_axis_labeling(exclusionmap3s);
384	<
385	<	Int_t MyPalette[100];
386	<	Double_t r[]    = {0., 0.0, 1.0, 1.0, 1.0};
387	<	Double_t g[]    = {0., 0.0, 0.0, 1.0, 1.0};
388	<	Double_t b[]    = {0., 1.0, 0.0, 0.0, 1.0};
389	<	Double_t stop[] = {0., .25, .50, .75, 1.0};
390	<	Int_t FI = TColor::CreateGradientColorTable(5, stop, r, g, b, 100);
391	<	for (int i=0;i<100;i++) MyPalette[i] = FI+i;
392	<
393	<	gStyle->SetPalette(100, MyPalette);
394	<
395	<	for(int m23=50;m23<500;m23+=25) {
396	<	for (int m0=(2*(m23-50)+150);m0<=1000;m0+=50)
397	<	{
398	<	c3->cd();
399	<	stringstream drawcondition;
400	<	drawcondition << "pfJetGoodNum>=3&&(TMath::Abs(masses[0]-"<<m0<<")<10&&TMath::Abs(masses[2]-masses[3]-"<<m23<<")<10)&&mll>5&&id1==id2";
401	<	TH1F *puresignal = new TH1F("puresignal","puresignal",binning.size()-1,arrbinning);
402	<	TH1F *puresignall= new TH1F("puresignall","puresignal",binning.size()-1,arrbinning);
403	<	stringstream drawvar,drawvar2;
404	<	drawvar<<mcjzb<<">>puresignal";
405	<	drawvar2<<"-"<<mcjzb<<">>puresignall";
406	<	suevents->Draw(drawvar.str().c_str(),drawcondition.str().c_str());
407	<	suevents->Draw(drawvar2.str().c_str(),drawcondition.str().c_str());
408	<	if(puresignal->Integral()<60) {
409	<	delete puresignal;
410	<	continue;
411	<	}
412	<	puresignal->Add(puresignall,-1);//we need to correct for the signal contamination - we effectively only see (JZB>0)-(JZB<0) !!
413	<	puresignal->Scale(ndata/(20*puresignal->Integral()));//normalizing it to 5% of the data
414	<	stringstream saveas;
415	<	saveas<<"Model_Scan/m0_"<<m0<<"__m23_"<<m23;
416	<	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;
417	<	//        TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
418	<	//        TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
419	<	//        TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
420	<	//        signalpred->Add(signalpredlo,-1);
421	<	//        signalpred->Add(signalpredro);
422	<	//        puresignal->Add(signalpred,-1);//subtracting signal contamination
423	<	//---------------------
424	<	//      cout << "(m0,m23)=("<<m0<<","<<m23<<") contains " << puresignal->Integral() << endl;
425	<	//    TH1F *puresignal = allsamples.Draw("puresignal",mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
426	<	vector<float> results=establish_upper_limits(puredata,allbgs,puresignal,saveas.str(),myfile);
427	<	if(results.size()==0) {
428	<	delete puresignal;
369	<	continue;
370	<	}
371	<	exclusionmap->Fill(m23,m0,results[0]);
372	<	exclusionmap1s->Fill(m23,m0,results[1]);
373	<	exclusionmap2s->Fill(m23,m0,results[2]);
374	<	exclusionmap3s->Fill(m23,m0,results[3]);
375	<	delete puresignal;
376	<	cout << "(m0,m23)=("<<m0<<","<<m23<<") : 3 sigma at " << results[3] << endl;
377	<	}
378	<	}//end of model scan for loop
379	<
380	<	cout << "Exclusion Map contains" << exclusionmap->Integral() << " (integral) and entries: " << exclusionmap->GetEntries() << endl;
381	<	c3->cd();
382	<	exclusionmap->Draw("CONTZ");
383	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_Mean_values");
384	<	exclusionmap->Draw("COLZ");
385	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_Mean_values");
386	<
387	<	exclusionmap1s->Draw("CONTZ");
388	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_1sigma_values");
389	<	exclusionmap1s->Draw("COLZ");
390	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_1sigma_values");
391	<
392	<	exclusionmap2s->Draw("CONTZ");
393	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_2sigma_values");
394	<	exclusionmap2s->Draw("COLZ");
395	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_2sigma_values");
396	<
397	<	exclusionmap3s->Draw("CONTZ");
398	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_3sigma_values");
399	<	exclusionmap3s->Draw("COLZ");
400	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_3sigma_values");
401	<
402	<	TFile *exclusion_limits = new TFile("exclusion_limits.root","RECREATE");
403	<	exclusionmap->Write();
404	<	exclusionmap1s->Write();
405	<	exclusionmap2s->Write();
406	<	exclusionmap3s->Write();
407	<	exclusion_limits->Close();
408	<	susyscanfile->Close();
357	>
358	>	/********************************************************************** new : Limits using SHAPES ***********************************
359	>
360	>
361	>	SSSSSSSSSSSSSSS hhhhhhh
362	>	SS:::::::::::::::Sh:::::h
363	>	S:::::SSSSSS::::::Sh:::::h
364	>	S:::::S     SSSSSSSh:::::h
365	>	S:::::S             h::::h hhhhh         aaaaaaaaaaaaa  ppppp   ppppppppp       eeeeeeeeeeee        ssssssssss
366	>	S:::::S             h::::hh:::::hhh      a::::::::::::a p::::ppp:::::::::p    ee::::::::::::ee    ss::::::::::s
367	>	S::::SSSS          h::::::::::::::hh    aaaaaaaaa:::::ap:::::::::::::::::p  e::::::eeeee:::::eess:::::::::::::s
368	>	SS::::::SSSSS     h:::::::hhh::::::h            a::::app::::::ppppp::::::pe::::::e     e:::::es::::::ssss:::::s
369	>	SSS::::::::SS   h::::::h   h::::::h    aaaaaaa:::::a p:::::p     p:::::pe:::::::eeeee::::::e s:::::s  ssssss
370	>	SSSSSS::::S  h:::::h     h:::::h  aa::::::::::::a p:::::p     p:::::pe:::::::::::::::::e    s::::::s
371	>	S:::::S h:::::h     h:::::h a::::aaaa::::::a p:::::p     p:::::pe::::::eeeeeeeeeee        s::::::s
372	>	S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::p    p::::::pe:::::::e           ssssss   s:::::s
373	>	SSSSSSS     S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::ppppp:::::::pe::::::::e          s:::::ssss::::::s
374	>	S::::::SSSSSS:::::S h:::::h     h:::::ha:::::aaaa::::::a p::::::::::::::::p  e::::::::eeeeeeee  s::::::::::::::s
375	>	S:::::::::::::::SS  h:::::h     h:::::h a::::::::::aa:::ap::::::::::::::pp    ee:::::::::::::e   s:::::::::::ss
376	>	SSSSSSSSSSSSSSS    hhhhhhh     hhhhhhh  aaaaaaaaaa  aaaap::::::pppppppp        eeeeeeeeeeeeee    sssssssssss
377	>	p:::::p
378	>	p:::::p
379	>	p:::::::p
380	>	p:::::::p
381	>	p:::::::p
382	>	ppppppppp
383	>
384	>
385	>	*********************************************************************** new : Limits using SHAPES ***********************************/
386	>
387	>
388	>	void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
389	>	dout << "Creatig shape templates ... ";
390	>	if(identifier!="") dout << "for systematic called "<<identifier;
391	>	dout << endl;
392	>	int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
393	>	if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
394	>
395	>	TCut limitnJetcut;
396	>	if(JES==noJES) limitnJetcut=cutnJets;
397	>	else {
398	>	if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
399	>	if(JES==JESup) limitnJetcut=cutnJetsJESup;
400	>	}
401	>	TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
402	>	TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
403	>	TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
404	>	TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
405	>
406	>	TH1F *SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
407	>	TH1F *SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
408	>	TH1F *SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
409	>	TH1F *SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
410	>
411	>	TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
412	>	TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
413	>	TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
414	>	TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
415	>
416	>	TH1F *LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
417	>	TH1F *LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
418	>	TH1F *LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
419	>	TH1F *LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
420	>
421	>	string obsname="data_obs";
422	>	string predname="background";
423	>	string signalname="signal";
424	>	if(identifier!="") {
425	>	obsname=("data_"+identifier);
426	>	predname=("background_"+identifier);
427	>	signalname="signal_"+identifier;
428	>	}
429
430	<	myfile.close();
430	>	TH1F *obs = (TH1F*)ZOSSFP->Clone();
431	>	obs->SetName(obsname.c_str());
432	>	obs->Write();
433	>	TH1F *pred = (TH1F*)ZOSSFN->Clone();
434	>	pred->Add(ZOSOFP,1.0/3);
435	>	pred->Add(ZOSOFN,-1.0/3);
436	>	pred->Add(SBOSSFP,1.0/3);
437	>	pred->Add(SBOSSFN,-1.0/3);
438	>	pred->Add(SBOSOFP,1.0/3);
439	>	pred->Add(SBOSOFN,-1.0/3);
440	>	pred->SetName(predname.c_str());
441	>	pred->Write();
442	>
443	>	//  TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
444	>	//  TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
445	>
446	>	TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
447	>	TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
448	>	Lobs->Add(LZOSSFP);
449	>	Lpred->Add(LZOSSFN);
450	>	Lpred->Add(LZOSOFP,1.0/3);
451	>	Lpred->Add(LZOSOFN,-1.0/3);
452	>	Lpred->Add(LSBOSSFP,1.0/3);
453	>	Lpred->Add(LSBOSSFN,-1.0/3);
454	>	Lpred->Add(LSBOSOFP,1.0/3);
455	>	Lpred->Add(LSBOSOFN,-1.0/3);
456	>	TH1F *signal = (TH1F*)Lobs->Clone();
457	>	signal->Add(Lpred,-1);
458	>	signal->SetName(signalname.c_str());
459	>	signal->Write();
460	>
461	>	delete Lobs;
462	>	delete Lpred;
463	>
464	>	delete ZOSSFP;
465	>	delete ZOSOFP;
466	>	delete ZOSSFN;
467	>	delete ZOSOFN;
468	>
469	>	delete SBOSSFP;
470	>	delete SBOSOFP;
471	>	delete SBOSSFN;
472	>	delete SBOSOFN;
473	>
474	>	delete LZOSSFP;
475	>	delete LZOSOFP;
476	>	delete LZOSSFN;
477	>	delete LZOSOFN;
478	>
479	>	delete LSBOSSFP;
480	>	delete LSBOSOFP;
481	>	delete LSBOSSFN;
482	>	delete LSBOSOFN;
483	>
484		}
485
486	+	void prepare_datacard(TFile *f) {
487	+	TH1F *dataob = (TH1F*)f->Get("data_obs");
488	+	TH1F *signal = (TH1F*)f->Get("signal");
489	+	TH1F *background = (TH1F*)f->Get("background");
490	+
491	+	ofstream datacard;
492	+	ensure_directory_exists(get_directory()+"/limits");
493	+	datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
494	+	datacard << "Writing this to a file.\n";
495	+	datacard << "imax 1\n";
496	+	datacard << "jmax 1\n";
497	+	datacard << "kmax *\n";
498	+	datacard << "---------------\n";
499	+	datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
500	+	datacard << "---------------\n";
501	+	datacard << "bin 1\n";
502	+	datacard << "observation "<<dataob->Integral()<<"\n";
503	+	datacard << "------------------------------\n";
504	+	datacard << "bin             1          1\n";
505	+	datacard << "process         signal     background\n";
506	+	datacard << "process         0          1\n";
507	+	datacard << "rate            "<<signal->Integral()<<"         "<<background->Integral()<<"\n";
508	+	datacard << "--------------------------------\n";
509	+	datacard << "lumi     lnN    1.10       1.0\n";
510	+	datacard << "bgnorm   lnN    1.00       1.4  uncertainty on our prediction (40%)\n";
511	+	datacard << "JES    shape    1          1    uncertainty on background shape and normalization\n";
512	+	datacard << "peak   shape    1          1    uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
513	+	datacard << "#                                so divide the unit gaussian by 2 before doing the interpolation\n";
514	+	datacard.close();
515	+	}
516
517
518	<
518	>	void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
519	>	ensure_directory_exists(get_directory()+"/limits");
520	>	TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
521	>	TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
522	>	limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
523	>	limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
524	>	limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
525	>	limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
526	>	limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
527	>
528	>	prepare_datacard(limfile);
529	>	limfile->Close();
530	>	write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
531	>
532	>	}

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