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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 1.27 by buchmann, Mon Oct 24 15:26:14 2011 UTC

#	Line 1 | Line 1
1	+	/****
2	+
3	+	Off peak status (RestrictToMassPeak) :
4	+
5	+	x  Necessary adaptations identified
6	+	x  Started working on necessary adaptations
7	+	x  Necessary adaptations implemented
8	+	x  Necessary adaptations tested
9	+
10	+	DONE!
11	+
12	+
13	+	****/
14		#include <iostream>
15		#include <vector>
16		#include <sys/stat.h>
17	+	#include <fstream>
18
19		#include <TCut.h>
20		#include <TROOT.h>
#	Line 14 | Line 28
28		#include <TF1.h>
29		#include <TSQLResult.h>
30		#include <TProfile.h>
31	+	#include <TSystem.h>
32	+	#include "LimitDroplet.C"
33
34		//#include "TTbar_stuff.C"
35		using namespace std;
#	Line 22 | Line 38 | using namespace PlottingSetup;
38
39
40		void rediscover_the_top(string mcjzb, string datajzb) {
41	<	cout << "Hi! today we are going to (try to) rediscover the top!" << endl;
41	>	dout << "Hi! today we are going to (try to) rediscover the top!" << endl;
42		TCanvas *c3 = new TCanvas("c3","c3");
43		c3->SetLogy(1);
44		vector<float> binning;
#	Line 62 | Line 78 | void rediscover_the_top(string mcjzb, st
78		TH1F *datapredictiont = allsamples.Draw("datapredictiont",    "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,  luminosity);
79		TH1F *datapredictiono = allsamples.Draw("datapredictiono",    "-"+datajzb, nbins,low,hi, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,  luminosity);
80		datapredictiont->Add(datapredictiono,-1);
81	<	cout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
81	>	dout << "Second way of doing this !!!! Analytical shape to the left :-D" << endl;
82		vector<TF1*> functions = do_cb_fit_to_plot(datapredictiont,10);
83		datapredictiont->SetMarkerColor(kRed);
84		datapredictiont->SetLineColor(kRed);
#	Line 141 | Line 157 | ratio_binning.push_back(80);
157		ratio->Divide(datapredictiontb);
158
159		for (int i=0;i<=ratio_binning.size();i++) {
160	<	cout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
160	>	dout << observedtb->GetBinLowEdge(i+1) << ";"<<observedtb->GetBinContent(i+1) << ";" << datapredictiontb->GetBinContent(i+1) << " --> " << ratio->GetBinContent(i+1) << "+/-" << ratio->GetBinError(i+1) << endl;
161		}
162
163		//  ratio->Divide(datapredictiontb);
#	Line 167 | Line 183 | ratio_binning.push_back(80);
183
184		}
185
186	<	void calculate_upper_limits(string mcjzb, string datajzb) {
187	<	write_warning("calculate_upper_limits","Upper limit calculation temporarily deactivated");
188	<	//  write_warning("calculate_upper_limits","Calculation of SUSY upper limits has been temporarily suspended in favor of top discovery");
189	<	//  rediscover_the_top(mcjzb,datajzb);
190	<	/*
191	<	TCanvas *c3 = new TCanvas("c3","c3");
192	<	c3->SetLogy(1);
193	<	vector<float> binning;
194	<	//binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
195	<	binning.push_back(50);
196	<	binning.push_back(100);
197	<	binning.push_back(150);
198	<	binning.push_back(200);
199	<	binning.push_back(500);
200	<	TH1F *datapredictiona = allsamples.Draw("datapredictiona",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity);
201	<	TH1F *datapredictionb = allsamples.Draw("datapredictionb",    "-"+datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
202	<	TH1F *datapredictionc = allsamples.Draw("datapredictionc",    datajzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity);
203	<	TH1F *dataprediction = (TH1F*)datapredictiona->Clone();
204	<	dataprediction->Add(datapredictionb,-1);
205	<	dataprediction->Add(datapredictionc);
206	<	TH1F *puresignal     = allsamples.Draw("puresignal",        mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
207	<	TH1F *signalpred     = allsamples.Draw("signalpred",    "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
208	<	TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
209	<	TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
210	<	TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
211	<	signalpred->Add(signalpredlo,-1);
212	<	signalpred->Add(signalpredro);
213	<	puresignal->Add(signalpred,-1);//subtracting signal contamination
214	<	ofstream myfile;
215	<	myfile.open ("ShapeFit_log.txt");
216	<	establish_upper_limits(puredata,dataprediction,puresignal,"LM4",myfile);
217	<	myfile.close();
218	<	*/
186	>	vector<float> compute_one_upper_limit(float mceff,float mcefferr, int ibin, string mcjzb, string plotfilename, bool doexpected) {
187	>	float sigma95=-9.9,sigma95A=-9.9;
188	>	/*
189	>	USAGE OF ROOSTATS_CL95
190	>	" Double_t             limit = roostats_cl95(ilum, slum, eff, seff, bck, sbck, n, gauss = false, nuisanceModel, method, plotFileName, seed); \n"
191	>	" LimitResult expected_limit = roostats_clm(ilum, slum, eff, seff, bck, sbck, ntoys, nuisanceModel, method, seed); \n"
192	>	" Double_t     average_limit = roostats_cla(ilum, slum, eff, seff, bck, sbck, nuisanceModel, method, seed); \n"
193	>	"                                                                     \n"
194	>	"
195	>	" Double_t obs_limit = limit.GetObservedLimit();                      \n"
196	>	" Double_t exp_limit = limit.GetExpectedLimit();                      \n"
197	>	" Double_t exp_up    = limit.GetOneSigmaHighRange();                  \n"
198	>	" Double_t exp_down  = limit.GetOneSigmaLowRange();                   \n"
199	>	" Double_t exp_2up   = limit.GetTwoSigmaHighRange();                  \n"
200	>	" Double_t exp_2down = limit.GetTwoSigmaLowRange();                   \n"
201	>	*/
202	>	if(mceff<=0) {
203	>	write_warning(__FUNCTION__,"Cannot compute upper limit in this configuration as the efficiency is negative:");
204	>	dout << "mc efficiency=" << mceff << " +/- " << mcefferr;
205	>	vector<float> sigmas;
206	>	sigmas.push_back(-1);
207	>	sigmas.push_back(-1);
208	>	return sigmas;
209	>	} else {
210	>	int nlimittoysused=1;
211	>
212	>	///------------------------------------------ < NEW > ----------------------------------------------------------
213	>
214	>	int secondssince1970=time(NULL);
215	>	stringstream repname;
216	>	repname << PlottingSetup::cbafbasedir << "/exchange/report_" << secondssince1970 << "_"<<plotfilename<< "__"<< ".txt";
217	>
218	>	/* - report filename [1]
219	>	- luminosity [2]
220	>	- lumi uncert [3]
221	>	- MC efficiency [4]
222	>	- MC efficiency error [5]
223	>	- Npred [6]
224	>	- Nprederr [7]
225	>	- Nobs [8]
226	>	- JZB cut [9]
227	>	- plot name  [10]*/
228	>
229	>	dout << "Calling limit capsule instead of calling : CL95(" << luminosity << "," <<  lumiuncert*luminosity << "," << mceff << "," << mcefferr << "," << Npred[ibin] << "," << Nprederr[ibin] << "," << Nobs[ibin] << "," << false << "," << nuisancemodel<< ") " << endl;
230	>
231	>	stringstream command;
232	>	command << PlottingSetup::cbafbasedir << "/DistributedModelCalculations/Limits/TimedLimitCapsule.exec " << repname.str() << " " << luminosity << " " << luminosity*lumiuncert << " " << mceff << " " << mcefferr << " " << Npred[ibin] << " " << Nprederr[ibin] << " " << Nobs[ibin] << " " << -1 << " " << PlottingSetup::basedirectory << "/" << plotfilename << " " << doexpected;
233	>	dout << command.str() << endl;
234	>
235	>	int retval = 256;
236	>	int attempts=0;
237	>	while(!(retval==0||attempts>=3)) {//try up to 3 times
238	>	attempts++;
239	>	dout << "Starting limit calculation (LimitCapsule) now : Attempt " << attempts << endl;
240	>	retval=gSystem->Exec(command.str().c_str());
241	>	}
242	>
243	>	LimitDroplet limres;
244	>	limres.readDroplet(repname.str());
245	>	dout << limres << endl;
246	>	remove(repname.str().c_str());
247	>	sigma95=limres.observed;
248	>
249	>
250	>	///------------------------------------------ < /NEW > ----------------------------------------------------------
251	>	vector<float> sigmas;
252	>	sigmas.push_back(sigma95);
253	>	if(doexpected) {
254	>	sigmas.push_back(limres.expected);
255	>	sigmas.push_back(limres.upper68);
256	>	sigmas.push_back(limres.lower68);
257	>	sigmas.push_back(limres.upper95);
258	>	sigmas.push_back(limres.lower95);
259	>	}
260	>
261	>	return sigmas;
262	>
263	>
264	>	}//end of mc efficiency is ok
265		}
266
267	<	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts) {
268	<	cout << "Doing counting experiment ... " << endl;
267	>	void compute_upper_limits_from_counting_experiment(vector<vector<float> > uncertainties,vector<float> jzbcuts, string mcjzb, bool doexpected) {
268	>	dout << "Doing counting experiment ... " << endl;
269	>	vector<vector<string> > limits;
270	>	vector<vector<float> > vlimits;
271	>
272
273		for(int isample=0;isample<signalsamples.collection.size();isample++) {
274	<	cout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
274	>	vector<string> rows;
275	>	vector<float> vrows;
276	>	dout << "Considering sample " << signalsamples.collection[isample].samplename << endl;
277	>	rows.push_back(signalsamples.collection[isample].samplename);
278		for(int ibin=0;ibin<jzbcuts.size();ibin++) {
279	<	cout << "   Considering bin " << jzbcuts[ibin] << endl;
280	<	for(int isyst=0;isyst<uncertainties[isample*jzbcuts.size()+ibin].size();isyst++) {
281	<	if(isyst==0) {
282	<	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;
283	<	continue;
284	<	}
285	<	cout << "     Considering syst " << isyst << " : " << uncertainties[isample*jzbcuts.size()+ibin][isyst] << endl;
286	<	}//end of syst loop
279	>	dout << "_________________________________________________________________________________" << endl;
280	>	float JZBcutat=uncertainties[isample*jzbcuts.size()+ibin][0];
281	>	float mceff=uncertainties[isample*jzbcuts.size()+ibin][1];
282	>	float staterr=uncertainties[isample*jzbcuts.size()+ibin][2];
283	>	float systerr=uncertainties[isample*jzbcuts.size()+ibin][3];
284	>	float toterr =uncertainties[isample*jzbcuts.size()+ibin][4];
285	>	float observed,observederr,null,result;
286	>
287	>	//      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);
288	>	//      observed-=result;//this is the actual excess we see!
289	>	//      float expected=observed/luminosity;
290	>	string plotfilename=(string)(TString(signalsamples.collection[isample].samplename)+TString("___JZB_geq_")+TString(any2string(JZBcutat))+TString(".png"));
291	>	dout << "Sample: " << signalsamples.collection[isample].samplename << ", JZB>"<<JZBcutat<< " : " << mceff << " +/- " << staterr << " (stat) +/- " << systerr << " (syst) --> toterr = " << toterr << endl;
292	>	vector<float> sigmas = compute_one_upper_limit(mceff,toterr,ibin,mcjzb,plotfilename,doexpected);
293	>
294	>	if(doexpected) {
295	>	//      rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(expected)+")");
296	>	rows.push_back(any2string(sigmas[0])+";"+any2string(sigmas[1])+";"+"("+any2string(signalsamples.collection[isample].xs)+")");
297	>	vrows.push_back(sigmas[0]);
298	>	vrows.push_back(sigmas[1]);
299	>	//      vrows.push_back(expected);
300	>	vrows.push_back(signalsamples.collection[isample].xs);
301	>	}
302	>	else {
303	>	//      rows.push_back(any2string(sigmas[0])+"("+any2string(expected)+")");
304	>	rows.push_back(any2string(sigmas[0]));
305	>	vrows.push_back(sigmas[0]);
306	>	vrows.push_back(signalsamples.collection[isample].xs);
307	>	//      vrows.push_back(expected);
308	>	}
309		}//end of bin loop
310	+	limits.push_back(rows);
311	+	vlimits.push_back(vrows);
312		}//end of sample loop
313	+	dout << endl << endl << endl << "_________________________________________________________________________________________________" << endl << endl;
314	+	dout << endl << endl << "PAS table 3:   (notation: limit [95%CL])" << endl << endl;
315	+	dout << "\t";
316	+	for (int irow=0;irow<jzbcuts.size();irow++) {
317	+	dout << jzbcuts[irow] << "\t";
318	+	}
319	+	dout << endl;
320	+	for(int irow=0;irow<limits.size();irow++) {
321	+	for(int ientry=0;ientry<limits[irow].size();ientry++) {
322	+	if (limits[irow][ientry]>0) dout << limits[irow][ientry] << "\t";
323	+	else dout << " (N/A) \t";
324	+	}
325	+	dout << endl;
326	+	}
327	+
328	+	if(!doexpected) {
329	+	dout << endl << endl << "LIMITS: (Tex)" << endl;
330	+	tout << "\\begin{table}[hbtp]" << endl;
331	+	tout << "\\renewcommand{\\arraystretch}{1.3}" << endl;
332	+	tout << "\\begin{center}" << endl;
333	+	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;
334	+	tout << "" << endl;
335	+	tout << "\\begin{tabular}{ | l | ";
336	+	for (int irow=0;irow<jzbcuts.size();irow++) tout << " l |";
337	+	tout << "} " << endl << " \\hline " << endl << "& \t ";
338	+	for (int irow=0;irow<jzbcuts.size();irow++) {
339	+	tout << "JZB $>$ " << jzbcuts[irow] << " GeV & \t ";
340	+	}
341	+	tout << " \\\\ \\hline " << endl;
342	+	for(int irow=0;irow<limits.size();irow++) {
343	+	tout << limits[irow][0] << " \t";
344	+	for(int ientry=0;ientry<jzbcuts.size();ientry++) {
345	+	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";
346	+	else tout << " & ( N / A ) \t";
347	+	//      dout << Round(vlimits[irow][2*ientry],3) << " / " << Round(vlimits[irow][2*ientry+1],3)<< "\t";
348	+	}
349	+	tout << " \\\\ \\hline " << endl;
350	+	}
351	+	tout << "\\end{tabular}" << endl;
352	+	tout << "      \\end{tabular}"<< endl;
353	+	tout << "\\end{center}"<< endl;
354	+	tout << "\\end{table} "<< endl;
355	+
356	+	}//do observed
357	+
358	+	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;
359	+	dout << "Scenario \t Efficiency [%] \t Upper limits [pb] \t \\sigma [pb]" << endl;
360	+	for(int icut=0;icut<jzbcuts.size();icut++) {
361	+	dout << "Region with JZB>" << jzbcuts[icut] << (ConsiderSignalContaminationForLimits?"  (accounting for signal contamination)":"  (not accounting for signal contamination)") << endl;
362	+	for(int isample=0;isample<signalsamples.collection.size();isample++) {
363	+	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;
364	+	}
365	+	dout << endl;
366	+	}
367		}
368
223	–	void susy_scan_axis_labeling(TH2F *histo) {
224	–	histo->GetXaxis()->SetTitle("#Chi_{2}^{0}-LSP");
225	–	histo->GetXaxis()->CenterTitle();
226	–	histo->GetYaxis()->SetTitle("m_{#tilde{q}}");
227	–	histo->GetYaxis()->CenterTitle();
228	–	}
369
370	<	void scan_susy_space(string mcjzb, string datajzb) {
371	<	TCanvas *c3 = new TCanvas("c3","c3");
372	<	vector<float> binning;
373	<	binning=allsamples.get_optimal_binsize(mcjzb,cutmass&&cutOSSF&&cutnJets,20,50,800);
374	<	/*
375	<	binning.push_back(50);
376	<	binning.push_back(75);
377	<	binning.push_back(100);
378	<	binning.push_back(150);
379	<	binning.push_back(200);
380	<	binning.push_back(500);
381	<	*/
382	<	float arrbinning[binning.size()];
383	<	for(int i=0;i<binning.size();i++) arrbinning[i]=binning[i];
384	<	TH1F *puredata   = allsamples.Draw("puredata",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
385	<	puredata->SetMarkerSize(DataMarkerSize);
386	<	TH1F *allbgs   = allsamples.Draw("allbgs",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
387	<	TH1F *allbgsb   = allsamples.Draw("allbgsb",  "-"+datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
388	<	TH1F *allbgsc   = allsamples.Draw("allbgsc",  datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,data,luminosity);
389	<	allbgs->Add(allbgsb,-1);
390	<	allbgs->Add(allbgsc);
391	<	int ndata=puredata->Integral();
392	<	ofstream myfile;
393	<	myfile.open ("susyscan_log.txt");
394	<	TFile *susyscanfile = new TFile("/scratch/fronga/SMS/T5z_SqSqToQZQZ_38xFall10.root");
395	<	TTree *suevents = (TTree*)susyscanfile->Get("events");
396	<	TH2F *exclusionmap = new TH2F("exclusionmap","",20,0,500,20,0,1000);
397	<	TH2F *exclusionmap1s = new TH2F("exclusionmap1s","",20,0,500,20,0,1000);
398	<	TH2F *exclusionmap2s = new TH2F("exclusionmap2s","",20,0,500,20,0,1000);
399	<	TH2F *exclusionmap3s = new TH2F("exclusionmap3s","",20,0,500,20,0,1000);
400	<
401	<	susy_scan_axis_labeling(exclusionmap);
402	<	susy_scan_axis_labeling(exclusionmap1s);
403	<	susy_scan_axis_labeling(exclusionmap2s);
404	<	susy_scan_axis_labeling(exclusionmap3s);
405	<
406	<	Int_t MyPalette[100];
407	<	Double_t r[]    = {0., 0.0, 1.0, 1.0, 1.0};
408	<	Double_t g[]    = {0., 0.0, 0.0, 1.0, 1.0};
409	<	Double_t b[]    = {0., 1.0, 0.0, 0.0, 1.0};
410	<	Double_t stop[] = {0., .25, .50, .75, 1.0};
411	<	Int_t FI = TColor::CreateGradientColorTable(5, stop, r, g, b, 100);
412	<	for (int i=0;i<100;i++) MyPalette[i] = FI+i;
413	<
414	<	gStyle->SetPalette(100, MyPalette);
415	<
416	<	for(int m23=50;m23<500;m23+=25) {
417	<	for (int m0=(2*(m23-50)+150);m0<=1000;m0+=50)
418	<	{
419	<	c3->cd();
420	<	stringstream drawcondition;
421	<	drawcondition << "pfJetGoodNum>=3&&(TMath::Abs(masses[0]-"<<m0<<")<10&&TMath::Abs(masses[2]-masses[3]-"<<m23<<")<10)&&mll>5&&id1==id2";
422	<	TH1F *puresignal = new TH1F("puresignal","puresignal",binning.size()-1,arrbinning);
423	<	TH1F *puresignall= new TH1F("puresignall","puresignal",binning.size()-1,arrbinning);
424	<	stringstream drawvar,drawvar2;
425	<	drawvar<<mcjzb<<">>puresignal";
426	<	drawvar2<<"-"<<mcjzb<<">>puresignall";
427	<	suevents->Draw(drawvar.str().c_str(),drawcondition.str().c_str());
428	<	suevents->Draw(drawvar2.str().c_str(),drawcondition.str().c_str());
429	<	if(puresignal->Integral()<60) {
430	<	delete puresignal;
431	<	continue;
432	<	}
433	<	puresignal->Add(puresignall,-1);//we need to correct for the signal contamination - we effectively only see (JZB>0)-(JZB<0) !!
434	<	puresignal->Scale(ndata/(20*puresignal->Integral()));//normalizing it to 5% of the data
435	<	stringstream saveas;
436	<	saveas<<"Model_Scan/m0_"<<m0<<"__m23_"<<m23;
437	<	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;
438	<	//        TH1F *signalpredlo   = allsamples.Draw("signalpredlo",  "-"+mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
439	<	//        TH1F *signalpredro   = allsamples.Draw("signalpredro",      mcjzb,  binning, "JZB [GeV]", "events", cutmass&&cutOSOF&&cutnJets,mc,  luminosity,allsamples.FindSample("LM4"));
440	<	//        TH1F *puredata       = allsamples.Draw("puredata",          datajzb,binning, "JZB [GeV]", "events", cutmass&&cutOSSF&&cutnJets,data,luminosity);
441	<	//        signalpred->Add(signalpredlo,-1);
442	<	//        signalpred->Add(signalpredro);
443	<	//        puresignal->Add(signalpred,-1);//subtracting signal contamination
444	<	//---------------------
445	<	//      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;
311	<	}
312	<	exclusionmap->Fill(m23,m0,results[0]);
313	<	exclusionmap1s->Fill(m23,m0,results[1]);
314	<	exclusionmap2s->Fill(m23,m0,results[2]);
315	<	exclusionmap3s->Fill(m23,m0,results[3]);
316	<	delete puresignal;
317	<	cout << "(m0,m23)=("<<m0<<","<<m23<<") : 3 sigma at " << results[3] << endl;
318	<	}
319	<	}//end of model scan for loop
370	>
371	>	/********************************************************************** new : Limits using SHAPES ***********************************
372	>
373	>
374	>	SSSSSSSSSSSSSSS hhhhhhh
375	>	SS:::::::::::::::Sh:::::h
376	>	S:::::SSSSSS::::::Sh:::::h
377	>	S:::::S     SSSSSSSh:::::h
378	>	S:::::S             h::::h hhhhh         aaaaaaaaaaaaa  ppppp   ppppppppp       eeeeeeeeeeee        ssssssssss
379	>	S:::::S             h::::hh:::::hhh      a::::::::::::a p::::ppp:::::::::p    ee::::::::::::ee    ss::::::::::s
380	>	S::::SSSS          h::::::::::::::hh    aaaaaaaaa:::::ap:::::::::::::::::p  e::::::eeeee:::::eess:::::::::::::s
381	>	SS::::::SSSSS     h:::::::hhh::::::h            a::::app::::::ppppp::::::pe::::::e     e:::::es::::::ssss:::::s
382	>	SSS::::::::SS   h::::::h   h::::::h    aaaaaaa:::::a p:::::p     p:::::pe:::::::eeeee::::::e s:::::s  ssssss
383	>	SSSSSS::::S  h:::::h     h:::::h  aa::::::::::::a p:::::p     p:::::pe:::::::::::::::::e    s::::::s
384	>	S:::::S h:::::h     h:::::h a::::aaaa::::::a p:::::p     p:::::pe::::::eeeeeeeeeee        s::::::s
385	>	S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::p    p::::::pe:::::::e           ssssss   s:::::s
386	>	SSSSSSS     S:::::S h:::::h     h:::::ha::::a    a:::::a p:::::ppppp:::::::pe::::::::e          s:::::ssss::::::s
387	>	S::::::SSSSSS:::::S h:::::h     h:::::ha:::::aaaa::::::a p::::::::::::::::p  e::::::::eeeeeeee  s::::::::::::::s
388	>	S:::::::::::::::SS  h:::::h     h:::::h a::::::::::aa:::ap::::::::::::::pp    ee:::::::::::::e   s:::::::::::ss
389	>	SSSSSSSSSSSSSSS    hhhhhhh     hhhhhhh  aaaaaaaaaa  aaaap::::::pppppppp        eeeeeeeeeeeeee    sssssssssss
390	>	p:::::p
391	>	p:::::p
392	>	p:::::::p
393	>	p:::::::p
394	>	p:::::::p
395	>	ppppppppp
396	>
397	>
398	>	*********************************************************************** new : Limits using SHAPES ***********************************/
399	>
400	>
401	>	void limit_shapes_for_systematic_effect(TFile *limfile, string identifier, string mcjzb, string datajzb, int JES,vector<float> binning, TCanvas *limcan) {
402	>	dout << "Creatig shape templates ... ";
403	>	if(identifier!="") dout << "for systematic called "<<identifier;
404	>	dout << endl;
405	>	int dataormc=mcwithsignal;//this is only for tests - for real life you want dataormc=data !!!
406	>	if(dataormc!=data) write_warning(__FUNCTION__,"WATCH OUT! Not using data for limits!!!! this is ok for tests, but not ok for anything official!");
407	>
408	>	TCut limitnJetcut;
409	>	if(JES==noJES) limitnJetcut=cutnJets;
410	>	else {
411	>	if(JES==JESdown) limitnJetcut=cutnJetsJESdown;
412	>	if(JES==JESup) limitnJetcut=cutnJetsJESup;
413	>	}
414	>	TH1F *ZOSSFP = allsamples.Draw("ZOSSFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
415	>	TH1F *ZOSOFP = allsamples.Draw("ZOSOFP",datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
416	>	TH1F *ZOSSFN = allsamples.Draw("ZOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,dataormc,luminosity);
417	>	TH1F *ZOSOFN = allsamples.Draw("ZOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,dataormc,luminosity);
418	>
419	>	TH1F *SBOSSFP;
420	>	TH1F *SBOSOFP;
421	>	TH1F *SBOSSFN;
422	>	TH1F *SBOSOFN;
423	>
424	>	TH1F *LZOSSFP = allsamples.Draw("LZOSSFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
425	>	TH1F *LZOSOFP = allsamples.Draw("LZOSOFP",mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
426	>	TH1F *LZOSSFN = allsamples.Draw("LZOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSSF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
427	>	TH1F *LZOSOFN = allsamples.Draw("LZOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutmass&&cutOSOF&&limitnJetcut&&basiccut,mc,luminosity,allsamples.FindSample("LM4"));
428	>
429	>	TH1F *LSBOSSFP;
430	>	TH1F *LSBOSOFP;
431	>	TH1F *LSBOSSFN;
432	>	TH1F *LSBOSOFN;
433	>
434	>	flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
435	>	if(PlottingSetup::RestrictToMassPeak) {
436	>	SBOSSFP = allsamples.Draw("SBOSSFP",datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
437	>	SBOSOFP = allsamples.Draw("SBOSOFP",datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
438	>	SBOSSFN = allsamples.Draw("SBOSSFN","-"+datajzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
439	>	SBOSOFN = allsamples.Draw("SBOSOFN","-"+datajzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,dataormc,luminosity);
440	>
441	>	LSBOSSFP = allsamples.Draw("LSBOSSFP",mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
442	>	LSBOSOFP = allsamples.Draw("LSBOSOFP",mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
443	>	LSBOSSFN = allsamples.Draw("LSBOSSFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSSF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
444	>	LSBOSOFN = allsamples.Draw("LSBOSOFN","-"+mcjzb,binning, "JZB4limits", "events",cutOSOF&&limitnJetcut&&basiccut&&sidebandcut,mc,luminosity,allsamples.FindSample("LM4"));
445	>	}
446
447	<	cout << "Exclusion Map contains" << exclusionmap->Integral() << " (integral) and entries: " << exclusionmap->GetEntries() << endl;
448	<	c3->cd();
449	<	exclusionmap->Draw("CONTZ");
450	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_Mean_values");
451	<	exclusionmap->Draw("COLZ");
452	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_Mean_values");
453	<
454	<	exclusionmap1s->Draw("CONTZ");
329	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_1sigma_values");
330	<	exclusionmap1s->Draw("COLZ");
331	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_1sigma_values");
332	<
333	<	exclusionmap2s->Draw("CONTZ");
334	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_2sigma_values");
335	<	exclusionmap2s->Draw("COLZ");
336	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_2sigma_values");
337	<
338	<	exclusionmap3s->Draw("CONTZ");
339	<	CompleteSave(c3,"Model_Scan/CONT/Model_Scan_3sigma_values");
340	<	exclusionmap3s->Draw("COLZ");
341	<	CompleteSave(c3,"Model_Scan/COL/Model_Scan_3sigma_values");
342	<
343	<	TFile *exclusion_limits = new TFile("exclusion_limits.root","RECREATE");
344	<	exclusionmap->Write();
345	<	exclusionmap1s->Write();
346	<	exclusionmap2s->Write();
347	<	exclusionmap3s->Write();
348	<	exclusion_limits->Close();
349	<	susyscanfile->Close();
447	>	string obsname="data_obs";
448	>	string predname="background";
449	>	string signalname="signal";
450	>	if(identifier!="") {
451	>	obsname=("data_"+identifier);
452	>	predname=("background_"+identifier);
453	>	signalname="signal_"+identifier;
454	>	}
455
456	<	myfile.close();
457	<	}
456	>	TH1F *obs = (TH1F*)ZOSSFP->Clone("observation");
457	>	obs->SetName(obsname.c_str());
458	>	obs->Write();
459	>	TH1F *pred = (TH1F*)ZOSSFN->Clone("prediction");
460	>	flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
461	>	if(PlottingSetup::RestrictToMassPeak) {
462	>	pred->Add(ZOSOFP,1.0/3);
463	>	pred->Add(ZOSOFN,-1.0/3);
464	>	pred->Add(SBOSSFP,1.0/3);
465	>	pred->Add(SBOSSFN,-1.0/3);
466	>	pred->Add(SBOSOFP,1.0/3);
467	>	pred->Add(SBOSOFN,-1.0/3);
468	>	} else {
469	>	pred->Add(ZOSOFP,1.0);
470	>	pred->Add(ZOSOFN,-1.0);
471	>	}
472	>
473	>	pred->SetName(predname.c_str());
474	>	pred->Write();
475	>
476	>	//  TH1F *Lobs = (TH1F*)LZOSSFP->Clone();
477	>	//  TH1F *Lpred = (TH1F*)LZOSSFN->Clone();
478	>
479	>	TH1F *Lobs = new TH1F("Lobs","Lobs",binning.size()-1,&binning[0]);
480	>	TH1F *Lpred = new TH1F("Lpred","Lpred",binning.size()-1,&binning[0]);
481	>	Lobs->Add(LZOSSFP);
482	>	Lpred->Add(LZOSSFN);
483	>	flag_this_change(__FUNCTION__,__LINE__,false);//PlottingSetup::RestrictToMassPeak
484	>	if(PlottingSetup::RestrictToMassPeak) {
485	>	Lpred->Add(LZOSOFP,1.0/3);
486	>	Lpred->Add(LZOSOFN,-1.0/3);
487	>	Lpred->Add(LSBOSSFP,1.0/3);
488	>	Lpred->Add(LSBOSSFN,-1.0/3);
489	>	Lpred->Add(LSBOSOFP,1.0/3);
490	>	Lpred->Add(LSBOSOFN,-1.0/3);
491	>	} else {
492	>	Lpred->Add(LZOSOFP,1.0);
493	>	Lpred->Add(LZOSOFN,-1.0);
494	>	}
495
496	+	TH1F *signal = (TH1F*)Lobs->Clone();
497	+	signal->Add(Lpred,-1);
498	+	signal->SetName(signalname.c_str());
499	+	signal->Write();
500	+
501	+	delete Lobs;
502	+	delete Lpred;
503	+
504	+	delete ZOSSFP;
505	+	delete ZOSOFP;
506	+	delete ZOSSFN;
507	+	delete ZOSOFN;
508	+
509	+	if(PlottingSetup::RestrictToMassPeak) {
510	+	delete SBOSSFP;
511	+	delete SBOSOFP;
512	+	delete SBOSSFN;
513	+	delete SBOSOFN;
514	+	}
515	+
516	+	delete LZOSSFP;
517	+	delete LZOSOFP;
518	+	delete LZOSSFN;
519	+	delete LZOSOFN;
520	+
521	+	if(PlottingSetup::RestrictToMassPeak) {
522	+	delete LSBOSSFP;
523	+	delete LSBOSOFP;
524	+	delete LSBOSSFN;
525	+	delete LSBOSOFN;
526	+	}
527
528	+	}
529
530	+	void prepare_datacard(TFile *f) {
531	+	TH1F *dataob = (TH1F*)f->Get("data_obs");
532	+	TH1F *signal = (TH1F*)f->Get("signal");
533	+	TH1F *background = (TH1F*)f->Get("background");
534
535	+	ofstream datacard;
536	+	ensure_directory_exists(get_directory()+"/limits");
537	+	datacard.open ((get_directory()+"/limits/susydatacard.txt").c_str());
538	+	datacard << "Writing this to a file.\n";
539	+	datacard << "imax 1\n";
540	+	datacard << "jmax 1\n";
541	+	datacard << "kmax *\n";
542	+	datacard << "---------------\n";
543	+	datacard << "shapes * * limitfile.root $PROCESS $PROCESS_$SYSTEMATIC\n";
544	+	datacard << "---------------\n";
545	+	datacard << "bin 1\n";
546	+	datacard << "observation "<<dataob->Integral()<<"\n";
547	+	datacard << "------------------------------\n";
548	+	datacard << "bin             1          1\n";
549	+	datacard << "process         signal     background\n";
550	+	datacard << "process         0          1\n";
551	+	datacard << "rate            "<<signal->Integral()<<"         "<<background->Integral()<<"\n";
552	+	datacard << "--------------------------------\n";
553	+	datacard << "lumi     lnN    1.10       1.0\n";
554	+	datacard << "bgnorm   lnN    1.00       1.4  uncertainty on our prediction (40%)\n";
555	+	datacard << "JES    shape    1          1    uncertainty on background shape and normalization\n";
556	+	datacard << "peak   shape    1          1    uncertainty on signal resolution. Assume the histogram is a 2 sigma shift, \n";
557	+	datacard << "#                                so divide the unit gaussian by 2 before doing the interpolation\n";
558	+	datacard.close();
559	+	}
560	+
561	+
562	+	void prepare_limits(string mcjzb, string datajzb, float jzbpeakerrordata, float jzbpeakerrormc, vector<float> jzbbins) {
563	+	ensure_directory_exists(get_directory()+"/limits");
564	+	TFile *limfile = new TFile((get_directory()+"/limits/limitfile.root").c_str(),"RECREATE");
565	+	TCanvas *limcan = new TCanvas("limcan","Canvas for calculating limits");
566	+	limit_shapes_for_systematic_effect(limfile,"",mcjzb,datajzb,noJES,jzbbins,limcan);
567	+	limit_shapes_for_systematic_effect(limfile,"peakUp",newjzbexpression(mcjzb,jzbpeakerrormc),newjzbexpression(datajzb,jzbpeakerrordata),noJES,jzbbins,limcan);
568	+	limit_shapes_for_systematic_effect(limfile,"peakDown",newjzbexpression(mcjzb,-jzbpeakerrormc),newjzbexpression(datajzb,-jzbpeakerrordata),noJES,jzbbins,limcan);
569	+	limit_shapes_for_systematic_effect(limfile,"JESUp",mcjzb,datajzb,JESup,jzbbins,limcan);
570	+	limit_shapes_for_systematic_effect(limfile,"JESDown",mcjzb,datajzb,JESdown,jzbbins,limcan);
571	+
572	+	prepare_datacard(limfile);
573	+	limfile->Close();
574	+	write_info("prepare_limits","limitfile.root and datacard.txt have been generated. You can now use them to calculate limits!");
575	+
576	+	}

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