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Comparing UserCode/cbrown/Development/Plotting/Modules/EdgeLimit.C (file contents):
Revision 1.3 by buchmann, Mon Jun 18 07:51:38 2012 UTC vs.
Revision 1.19 by buchmann, Fri Jun 14 05:36:10 2013 UTC

#	Line 1 | Line 1
1		#include <iostream>
2
3	+	#include <TVirtualIndex.h>
4	+
5		#include <RooRealVar.h>
6		#include <RooArgSet.h>
7		#include <RooDataSet.h>
8	<	#include <RooRealVar.h>
9	<	#include <RooArgSet.h>
10	<	#include <RooDataSet.h>
8	>	#include <RooMCStudy.h>
9	>	#include <RooCategory.h>
10	>
11	>	#include <RooPlot.h>
12	>	#include <RooSimultaneous.h>
13	>	#include <RooAddPdf.h>
14	>	#include <RooFitResult.h>
15	>	#include <RooVoigtian.h>
16	>	#include <RooMsgService.h>
17	>
18		#include <RooStats/ModelConfig.h>
19		#include "RooStats/ProfileLikelihoodCalculator.h"
20		#include "RooStats/LikelihoodInterval.h"
#	Line 15 | Line 24
24		#include "RooStats/HybridCalculatorOriginal.h"
25		#include "RooStats/HypoTestInverterOriginal.h"
26
27	+	//#include "ParametrizedEdge.C"
28	+	#include "EdgeModules/RooSUSYTPdf.cxx"
29	+	#include "EdgeModules/RooSUSYBkgPdf.cxx"
30	+
31
32		using namespace std;
33		using namespace PlottingSetup;
#	Line 40 | Line 53 | namespace EdgeFitter {
53
54		void DoEdgeFit(string mcjzb, string datajzb, float DataPeakError, float MCPeakError, float jzb_cut, int icut, int is_data, TCut cut, TTree*);
55		void DoEdgeFit(string mcjzb, string datajzb, float DataPeakError, float MCPeakError, vector<float> jzb_cut, int is_data, TCut cut, TTree*);
56	+	void getMedianLimit(RooWorkspace *ws,vector<RooDataSet> theToys,float &median,float &sigmaDown, float &sigmaUp, float &twoSigmaDown, float &twoSigmaUp);
57		void InitializeVariables(float _mllmin, float _mllmax, float _jzbmax, TCut _cut);
58		void PrepareDatasets(int);
59	<	void DoFit();
59	>	void DrawDatasetContent(int);
60	>	void DoFit(int is_data, float jzb_cut);
61		string RandomStorageFile();
62		Yield Get_Z_estimate(float,int);
63		Yield Get_T_estimate(float,int);
64	<	float SetEdgeLimit(int , RooWorkspace *ws);
64	>	float calcExclusion(RooWorkspace *ws, RooDataSet data, bool calcExclusion);
65	>	vector<RooDataSet> generateToys(RooWorkspace *ws, int nToys);
66	>	void prepareLimits(RooWorkspace *ws, bool ComputeBands);
67	>	TGraph* prepareLM(float mass, float nEv);
68
69		float jzbmax;
70		float mllmin;
#	Line 54 | Line 72 | namespace EdgeFitter {
72		TCut cut;
73
74		RooDataSet* AllData;
75	<	RooDataSet* eeSample;
76	<	RooDataSet* mmSample;
77	<	RooDataSet* emSample;
75	>	RooDataSet* SFSample;
76	>	RooDataSet* OFSample;
77	>
78	>	bool MarcoDebug=true;
79	>
80	>	float FixedMEdge=-1;
81	>	float FixedMEdgeChi2=-1;
82	>
83	>	bool RejectPointIfNoConvergence=false;
84	>
85	>	string Mode="UndefinedMode";
86	>
87	>	}
88	>
89	>	TLatex* WriteAppleStudel() {
90	>	string sel="Apple Strudel Preliminary";
91	>	TLatex *sele = new TLatex(0.97,0.135,sel.c_str());
92	>	sele->SetNDC(true);
93	>	sele->SetTextColor(TColor::GetColor("#848484"));
94	>	sele->SetTextFont(42);
95	>	sele->SetTextAlign(32);
96	>	sele->SetTextSize(0.03);
97	>	sele->SetTextAngle(270);
98	>	return sele;
99	>	}
100	>
101	>	TGraph* EdgeFitter::prepareLM(float mass, float nEv) {
102	>	float massLM[1];
103	>	massLM[0]=mass;
104	>	float accEffLM[1];
105	>	accEffLM[0]=nEv/PlottingSetup::luminosity;
106	>	TGraph *lm = new TGraph(1, massLM, accEffLM);
107	>	lm->GetXaxis()->SetNoExponent(true);
108	>	lm->GetXaxis()->SetTitle("m_{cut} [GeV]");
109	>	lm->GetYaxis()->SetTitle("#sigma #times A [pb] 95% CL UL");
110	>	lm->GetXaxis()->SetLimits(0.,300.);
111	>	lm->GetYaxis()->SetRangeUser(0.,0.08);
112	>	lm->SetMarkerStyle(34);
113	>	lm->SetMarkerColor(kRed);
114	>	return lm;
115	>	}
116	>
117	>	vector<RooDataSet> EdgeFitter::generateToys(RooWorkspace *ws, int nToys) {
118	>	ws->ls();
119	>	ws->var("nSig")->setVal(0.);
120	>	ws->var("nSig")->setConstant(true);
121	>	RooFitResult* fit = ws->pdf("combModel")->fitTo(*ws->data("data_obs"),RooFit::Save());
122	>	vector<RooDataSet> theToys;
123	>
124	>	RooMCStudy mcEE(*ws->pdf("combModel"),RooArgSet(*ws->var("inv")),RooFit::Slice(*ws->cat("cat"),"EE"));
125	>	mcEE.generate(nToys,44,true);
126	>	RooMCStudy mcMM(*ws->pdf("combModel"),RooArgSet(*ws->var("inv")),RooFit::Slice(*ws->cat("cat"),"MM"));
127	>	mcMM.generate(nToys,44,true);
128	>	RooMCStudy mcOSOF(*ws->pdf("combModel"),RooArgSet(*ws->var("inv")),RooFit::Slice(*ws->cat("cat"),"OSOF"));
129	>	mcOSOF.generate(nToys,44,true);
130
131	<	bool MarcoDebug;
131	>	RooRealVar mll("m_{ll}","m_{ll}",mllmin,mllmax,"GeV/c^{2}");
132	>	RooRealVar id1("id1","id1",0,1,"GeV/c^{2}");
133	>	RooRealVar id2("id2","id2",0,1,"GeV/c^{2}");
134	>	RooRealVar jzb("jzb","jzb",-jzbmax,jzbmax,"GeV/c");
135	>	RooRealVar weight("weight","weight",0,1000,"");
136	>	RooArgSet observables(mll,jzb,id1,id2,weight);
137	>
138	>	for(int i=0;i<nToys;i++) {
139	>	RooDataSet* toyEE    = (RooDataSet*)mcEE.genData(i);
140	>	RooDataSet* toyMM    = (RooDataSet*)mcMM.genData(i);
141	>	RooDataSet* toyOSOF  = (RooDataSet*)mcOSOF.genData(i);
142	>	stringstream toyname;
143	>	toyname << "theToy_" << i;
144	>	write_warning(__FUNCTION__,"Problem while adding toys");
145	>	RooDataSet toyData = RooDataSet(toyname.str().c_str(),toyname.str().c_str(),observables,RooFit::Index(const_cast<RooCategory&>(*ws->cat("cat"))),RooFit::Import("OSOF",*toyOSOF),RooFit::Import("EE",*toyEE),RooFit::Import("MM",*toyMM));
146	>	theToys.push_back(toyData);
147	>	}
148	>	ws->var("nSig")->setVal(17.0);
149	>	ws->var("nSig")->setConstant(false);
150	>	return theToys;
151		}
152
153	<	float EdgeFitter::SetEdgeLimit(int is_data, RooWorkspace *ws) {
153	>	void EdgeFitter::getMedianLimit(RooWorkspace *ws,vector<RooDataSet> theToys,float &median,float &sigmaDown, float &sigmaUp, float &twoSigmaDown, float &twoSigmaUp) {
154	>	TH1F *gauLimit = new TH1F("gausLimit","gausLimit",60,0.,80./PlottingSetup::luminosity);
155	>	vector<float> theLimits;
156	>	for(int itoy=0;itoy<(int)theToys.size();itoy++) {
157	>	float theLimit = calcExclusion(ws,theToys[itoy],false);
158	>	if(theLimit > 0 ) gauLimit->Fill(theLimit);
159	>	}
160	>	const Int_t nQ = 4;
161	>	Double_t yQ[nQ] = {0.,0.,0.,0.};
162	>	Double_t xQ[nQ] = {0.022750132,0.1586552539,0.84134474609999998,0.977249868};
163	>	gauLimit->GetQuantiles(nQ,yQ,xQ);
164	>	median = gauLimit->GetMean();
165	>	//  median = median1(gauLimit);
166	>	twoSigmaDown = abs(yQ[0]-median);
167	>	sigmaDown = abs(yQ[1]-median);
168	>	sigmaUp = abs(yQ[2]-median);
169	>	twoSigmaUp = abs(yQ[3]-median);
170	>	dout << median * PlottingSetup::luminosity << " " << sigmaUp * PlottingSetup::luminosity << endl;
171	>	}
172	>
173	>	void EdgeFitter::prepareLimits(RooWorkspace *ws, bool ComputeBands) {
174	>	if(ComputeBands) {
175	>	vector<RooDataSet> theToys = EdgeFitter::generateToys(ws,50);
176	>	vector<float> medVals;
177	>	vector<float> medLimits;
178	>	vector<float> sigmaLimitsDown;
179	>	vector<float> sigmaLimitsUp;
180	>	vector<float> twoSigmaLimitsDown;
181	>	vector<float> twoSigmaLimitsUp;
182	>	for(int i=20;i<=320;i+=40) {
183	>	ws->var("nSig")->setVal(10.0);
184	>	medVals.push_back((float)i);
185	>	ws->var("m0")->setVal((float)i);
186	>	ws->var("m0")->setConstant(true);
187	>	float Smedian,SsigmaDown,SsigmaUp,StwoSigmaDown,StwoSigmaUp;
188	>	EdgeFitter::getMedianLimit(ws,theToys,Smedian,SsigmaDown,SsigmaUp,StwoSigmaDown,StwoSigmaUp);
189	>	medLimits.push_back(Smedian);
190	>	sigmaLimitsDown.push_back(SsigmaDown);
191	>	sigmaLimitsUp.push_back(SsigmaUp);
192	>	twoSigmaLimitsDown.push_back(StwoSigmaDown);
193	>	twoSigmaLimitsUp.push_back(StwoSigmaUp);
194	>	}
195	>	write_warning(__FUNCTION__,"Still need to store limits");
196	>	} else {
197	>	vector<float> theVals;
198	>	vector<float> theLimits;
199	>	for(int i=20;i<300;i+=5) {
200	>	ws->var("nSig")->setVal(0.0);
201	>	theVals.push_back((float)i);
202	>	ws->var("m0")->setVal((float)i);
203	>	ws->var("m0")->setConstant(true);
204	>	//      theLimits.push_back(calcExclusion(ws,(RooDataSet)*ws->data("data_obs"),true));
205	>	write_error(__FUNCTION__,"Error while casting roo data set");
206	>	}
207	>
208	>	for(int i=0;i<(int)theLimits.size();i++) {
209	>	if((theLimits[i]<2.0/PlottingSetup::luminosity)||(theLimits[i]>40.0/PlottingSetup::luminosity)) {
210	>	dout << i << " : " << theVals[i] << endl;
211	>	theLimits[i] = (theLimits[i+2]+theLimits[i-2])/2.0;
212	>	write_warning(__FUNCTION__,"Need to store limits");
213	>	}
214	>	write_warning(__FUNCTION__,"Need to store limits");
215	>	}
216	>	}
217	>	}
218	>
219	>
220	>	float EdgeFitter::calcExclusion(RooWorkspace *ws, RooDataSet data, bool LoadDataObs) {
221	>	int numberOfToys=50;
222		RooRealVar mu("mu","nSig",0,10000,"");
223		RooArgSet poi = RooArgSet(mu);
224		RooArgSet *nullParams = (RooArgSet*)poi.snapshot();
#	Line 70 | Line 227 | float EdgeFitter::SetEdgeLimit(int is_da
227		model->SetWorkspace(*ws);
228		model->SetPdf("combModel");
229		model->SetParametersOfInterest(poi);
230	<	RooAbsData* data = ws->data("data_obs");
230	>	//  if(LoadDataObs) data = (RooDataSet)*ws->data("data_obs");
231
232	<	RooStats::ProfileLikelihoodCalculator plc(*data, *model);
232	>	RooStats::ProfileLikelihoodCalculator plc(data, *model);
233		plc.SetNullParameters(*nullParams);
234		plc.SetTestSize(0.05);
235	+
236		RooStats::LikelihoodInterval* interval = plc.GetInterval();
237		RooStats::HypoTestResult *htr = plc.GetHypoTest();
238		double theLimit = interval->UpperLimit( mu );
239	<	cout << "Significance " << htr->Significance() << endl;
239	>	//  double significance = htr->Significance();
240
241		ws->defineSet("obs","nB");
242		ws->defineSet("poi","nSig");
#	Line 102 | Line 260 | RooAbsData* data = ws->data("data_obs");
260		slrts.SetAltParameters(*sb_model.GetSnapshot());
261		RooStats::ProfileLikelihoodTestStat profll = RooStats::ProfileLikelihoodTestStat(*b_model.GetPdf());
262
263	<	RooStats::HybridCalculatorOriginal hc = RooStats::HybridCalculatorOriginal(*data, sb_model, b_model,0,0);
263	>	RooStats::HybridCalculatorOriginal hc = RooStats::HybridCalculatorOriginal(data, sb_model, b_model,0,0);
264		hc.SetTestStatistic(2);
265	<	hc.SetNumberOfToys(50);
108	<
265	>	hc.SetNumberOfToys(numberOfToys);
266
267		RooStats::HypoTestInverterOriginal hcInv =  RooStats::HypoTestInverterOriginal(hc,*ws->var("nSig"));
268		hcInv.SetTestSize(0.05);
#	Line 114 | Line 271 | RooAbsData* data = ws->data("data_obs");
271		RooStats::HypoTestInverterResult* hcInt = hcInv.GetInterval();
272		float ulError = hcInt->UpperLimitEstimatedError();
273		theLimit = hcInt->UpperLimit();
274	<	cout << "Found upper limit : " << theLimit << "+/-" << ulError << endl;
274	>	dout << "Found upper limit : " << theLimit << "+/-" << ulError << endl;
275
276		return theLimit/PlottingSetup::luminosity;
277
278		}
279
280		TTree* SkimTree(int isample) {
281	<	TTree* newTree = allsamples.collection[isample].events->CloneTree(0);
281	>	string TreeName = allsamples.collection[isample].filename;
282	>	TTree* newTree = new TTree("NanoTree",TreeName.c_str());
283	>
284	>	float mll,edgeWeight;
285	>	int id1,id2;
286	>
287	>	newTree->Branch("edgeWeight",&edgeWeight,"edgeWeight/F");
288	>	newTree->Branch("mll",&mll,"mll/F");
289	>	newTree->Branch("id1",&id1,"id1/I");
290	>	newTree->Branch("id2",&id2,"id2/I");
291	>
292		float xsweight=1.0;
293		if(allsamples.collection[isample].is_data==false) xsweight=luminosity*allsamples.collection[isample].weight;
294		if(EdgeFitter::MarcoDebug) {
295	<	cout << "   Original tree contains " << allsamples.collection[isample].events->GetEntries() << endl;
296	<	cout << "   Going to reduce it with cut " << EdgeFitter::cut << endl;
295	>	dout << "   Original tree contains " << allsamples.collection[isample].events->GetEntries() << endl;
296	>	dout << "   Going to reduce it with cut " << EdgeFitter::cut << endl;
297		}
298	+
299	+	float tmll;
300	+	int tid1,tid2;
301	+	allsamples.collection[isample].events->SetBranchAddress("mll",&tmll);
302	+	allsamples.collection[isample].events->SetBranchAddress("id1",&tid1);
303	+	allsamples.collection[isample].events->SetBranchAddress("id2",&tid2);
304	+
305		TTreeFormula *select = new TTreeFormula("select", EdgeFitter::cut, allsamples.collection[isample].events);
306	+	TTreeFormula *Weight = new TTreeFormula("Weight", cutWeight, allsamples.collection[isample].events);
307	+
308		float wgt=1.0;
133	–	allsamples.collection[isample].events->SetBranchAddress(cutWeight,&wgt);
309		for (Int_t entry = 0 ; entry < allsamples.collection[isample].events->GetEntries() ; entry++) {
310		allsamples.collection[isample].events->LoadTree(entry);
311		if (select->EvalInstance()) {
312		allsamples.collection[isample].events->GetEntry(entry);
313	<	wgt=wgt*xsweight;
313	>	mll=tmll;
314	>	id1=tid1;
315	>	id2=tid2;
316	>	wgt=Weight->EvalInstance();
317	>	edgeWeight=wgt*xsweight;
318		newTree->Fill();
319		}
320		}
321
322	<	if(EdgeFitter::MarcoDebug) cout << "     Reduced tree contains " << newTree->GetEntries() << " entries " << endl;
322	>	if(EdgeFitter::MarcoDebug) dout << "     Reduced tree contains " << newTree->GetEntries() << " entries " << endl;
323		return newTree;
324		}
325
#	Line 150 | Line 329 | void EdgeFitter::InitializeVariables(flo
329		jzbmax=_jzbmax;
330		cut=_cut;
331		}
332	<
332	>
333	>	TTree* MergeTrees(vector<TTree*> trees) {
334	>	TTree * newtree = (TTree*)trees[0]->CloneTree(0);
335	>	trees[0]->GetListOfClones()->Remove(newtree);
336	>	trees[0]->ResetBranchAddresses();
337	>	newtree->ResetBranchAddresses();
338	>
339	>	for(int itree=0;itree<trees.size();itree++) {
340	>	newtree->CopyAddresses(trees[itree]);
341	>	Long64_t nentries = trees[itree]->GetEntries();
342	>	for (Long64_t iEntry=0;iEntry<nentries;iEntry++) {
343	>	trees[itree]->GetEntry(iEntry);
344	>	newtree->Fill();
345	>	}
346	>	trees[itree]->ResetBranchAddresses(); // Disconnect from new tree
347	>	if (newtree->GetTreeIndex()) {
348	>	newtree->GetTreeIndex()->Append(trees[itree]->GetTreeIndex(),kTRUE);
349	>	}
350	>	if (newtree && newtree->GetTreeIndex()) {
351	>	newtree->GetTreeIndex()->Append(0,kFALSE); // Force the sorting
352	>	}
353	>	}
354	>	return newtree;
355	>	}
356	>
357	>
358	>
359		void EdgeFitter::PrepareDatasets(int is_data) {
360	<	TTree *completetree;
361	<	bool hashit=0;
362	<	for(int isample=0;isample<allsamples.collection.size();isample++) {
360	>	write_warning(__FUNCTION__,"Need to make this function ready for scans as well (use signal from scan samples)");
361	>	TFile *tempout = new TFile("tempout.root","RECREATE");
362	>	vector<TTree*> SkimmedTrees;
363	>	TTree *SkimmedTree[(int)allsamples.collection.size()];
364	>	for(int isample=0;isample<(int)allsamples.collection.size();isample++) {
365		if(!allsamples.collection[isample].is_active) continue;
366		if(is_data==1&&allsamples.collection[isample].is_data==false) continue;//kick all samples that aren't data if we're looking for data.
367		if(is_data==1&&allsamples.collection[isample].is_data==false) continue;//kick all samples that aren't data if we're looking for data.
368		if(is_data!=1&&allsamples.collection[isample].is_data==true) continue;//kick all data samples when looking for MC
369		if(is_data!=2&&allsamples.collection[isample].is_signal==true) continue;//remove signal sample if we don't want it.
370	<	if(EdgeFitter::MarcoDebug) cout << "Considering : " << allsamples.collection[isample].samplename << endl;
371	<	if(!hashit) {
372	<	hashit=true;
373	<	completetree = SkimTree(isample)->CloneTree();
374	<	} else {
168	<	completetree->CopyEntries(SkimTree(isample));
169	<	}
170	<	if(EdgeFitter::MarcoDebug) cout << "Complete tree now contains " << completetree->GetEntries() << " entries " << endl;
370	>	if(EdgeFitter::MarcoDebug) dout << "Considering : " << allsamples.collection[isample].samplename << endl;
371	>	SkimmedTree[isample] = SkimTree(isample);
372	>	tempout->cd();
373	>	SkimmedTree[isample]->Write();
374	>	SkimmedTrees.push_back(SkimmedTree[isample]);
375		}
376
377	<	RooRealVar mll("mll","mll",mllmin,mllmax,"GeV/c^{2}");
377	>	TTree *completetree  = MergeTrees(SkimmedTrees);
378	>
379	>	if(EdgeFitter::MarcoDebug) dout << "Complete tree now contains " << completetree->GetEntries() << " entries " << endl;
380	>
381	>	RooRealVar mll("mll","m_{ll}",mllmin,mllmax,"GeV/c^{2}");
382		RooRealVar id1("id1","id1",0,1,"GeV/c^{2}");
383		RooRealVar id2("id2","id2",0,1,"GeV/c^{2}");
384	<	RooRealVar jzb("jzb","jzb",-jzbmax,jzbmax,"GeV/c");
385	<	RooRealVar weight("weight","weight",0,1000,"");
178	<	RooArgSet observables(mll,jzb,id1,id2,weight);
384	>	RooRealVar edgeWeight("edgeWeight","edgeWeight",0,1000,"");
385	>	RooArgSet observables(mll,id1,id2,edgeWeight);
386
387		string title="CMS Data";
388		if(is_data!=1) title="CMS SIMULATION";
389	<	RooDataSet LAllData("LAllData",title.c_str(),completetree,observables,"","weight");
389	>	RooDataSet LAllData("LAllData",title.c_str(),completetree,observables,"","edgeWeight");
390	>	tempout->cd();
391		completetree->Write();
392	<	//  delete completetree;
392	>	tempout->Close();
393	>
394
395	<	EdgeFitter::eeSample = (RooDataSet*)LAllData.reduce("id1==id2&&id1==0");
396	<	EdgeFitter::mmSample = (RooDataSet*)LAllData.reduce("id1==id2&&id1==1");
188	<	EdgeFitter::emSample = (RooDataSet*)LAllData.reduce("id1!=id2");
395	>	EdgeFitter::SFSample = (RooDataSet*)LAllData.reduce("id1==id2");
396	>	EdgeFitter::OFSample = (RooDataSet*)LAllData.reduce("id1!=id2");
397		EdgeFitter::AllData  = (RooDataSet*)LAllData.reduce("id1!=id2||id1==id2");
398
399	<	eeSample->SetName("eeSample");
400	<	mmSample->SetName("mmSample");
193	<	emSample->SetName("emSample");
399	>	SFSample->SetName("SFSample");
400	>	OFSample->SetName("OFSample");
401		AllData->SetName("AllData");
402
403		if(EdgeFitter::MarcoDebug) {
404	<	cout << "Number of events in data sample = " << AllData->numEntries() << endl;
405	<	cout << "Number of events in ee sample = " << eeSample->numEntries() << endl;
406	<	cout << "Number of events in mm sample = " << mmSample->numEntries() << endl;
200	<	cout << "Number of events in em sample = " << emSample->numEntries() << endl;
404	>	dout << "Number of events in data sample = " << AllData->sumEntries() << endl;
405	>	dout << "Number of events in eemm sample = " << SFSample->sumEntries() << endl;
406	>	dout << "Number of events in em sample = " << OFSample->sumEntries() << endl;
407		}
408	+
409	+	}
410	+
411	+	void EdgeFitter::DrawDatasetContent(int is_data) {
412	+	RooRealVar mll("mll","m_{ll}",mllmin,mllmax,"GeV/c^{2}");
413	+	RooPlot* frame1 = mll.frame(RooFit::Bins(int((mllmax-mllmin)/5.0)),RooFit::Title("SF sample")) ;
414	+	frame1->GetXaxis()->CenterTitle(1);
415	+	frame1->GetYaxis()->CenterTitle(1);
416	+	SFSample->plotOn(frame1,RooFit::Name("SFdata")) ;
417	+
418	+	RooPlot* frame2 = mll.frame(RooFit::Bins(int((mllmax-mllmin)/5.0)),RooFit::Title("OF sample")) ;
419	+	frame2->GetXaxis()->CenterTitle(1);
420	+	frame2->GetYaxis()->CenterTitle(1);
421	+	OFSample->plotOn(frame2,RooFit::Name("OFdata")) ;
422	+
423	+	TCanvas* cSFdata = new TCanvas("cSFdata","cSFdata") ;
424	+	cSFdata->cd() ;
425	+	gPad->SetLeftMargin(0.15);
426	+	frame1->GetYaxis()->SetTitleOffset(1.4);
427	+	frame1->Draw();
428	+	if(is_data==data) DrawPrelim();
429	+	else DrawPrelim(PlottingSetup::luminosity,true);
430	+	CompleteSave(cSFdata,"Edge/SF_NoFit");
431	+
432	+	TCanvas* cOFdata = new TCanvas("cOFdata","cOFdata") ;
433	+	cOFdata->cd() ;
434	+	gPad->SetLeftMargin(0.15);
435	+	frame2->SetMaximum(frame1->GetMaximum());
436	+	frame2->GetYaxis()->SetTitleOffset(1.4);
437	+	frame2->Draw();
438	+	if(is_data==data) DrawPrelim();
439	+	else DrawPrelim(PlottingSetup::luminosity,true);
440	+	CompleteSave(cOFdata,"Edge/OF_NoFit");
441	+	}
442	+
443	+	string WriteWithError(float central, float error, int digits) {
444	+	float ref=central;
445	+	if(ref<0) ref=-central;
446	+	int HighestSigDigit = 0;
447	+	if(ref>1) HighestSigDigit = int(log(ref)/log(10))+1;
448	+	else HighestSigDigit = int(log(ref)/(log(10)));
449	+
450	+	float divider=pow(10.0,(double(HighestSigDigit-digits)));
451	+
452	+	stringstream result;
453	+	result << divider*int(central/divider+0.5) << " #pm " << divider*int(error/divider+0.5);
454	+	return result.str();
455		}
456
457	+
458		string EdgeFitter::RandomStorageFile() {
459		TRandom3 *r = new TRandom3(0);
460		int rho = (int)r->Uniform(1,10000000);
#	Line 213 | Line 467 | string EdgeFitter::RandomStorageFile() {
467		Yield EdgeFitter::Get_Z_estimate(float jzb_cut, int icut) {
468		if(MarcoDebug) write_error(__FUNCTION__,"Returning random Z yield");
469		Yield a(123,45,67); return a;
216	–
470		return PlottingSetup::allresults.predictions[icut].Zbkg;
471		}
472
#	Line 223 | Line 476 | Yield EdgeFitter::Get_T_estimate(float j
476		return PlottingSetup::allresults.predictions[icut].Flavorsym;
477		}
478
479	+	void EdgeFitter::DoFit(int is_data, float jzb_cut) {
480	+
481	+	stringstream prefix;
482	+	if(is_data==data) prefix << "data_";
483	+	if(is_data==mc) prefix << "mc_";
484	+	if(is_data==mcwithsignal) prefix << "mcwithS_";
485	+
486	+	prefix << EdgeFitter::Mode << "_" << jzb_cut;
487	+
488	+
489	+
490	+	RooRealVar mll("mll","m_{ll}",mllmin,mllmax,"GeV/c^{2}");
491	+	RooRealVar edgeWeight("edgeWeight","edgeWeight",0,1000,"");
492	+	RooCategory sample("sample","sample") ;
493	+	sample.defineType("SF");
494	+	//sample.defineType("mm");
495	+	sample.defineType("OF");
496	+
497	+	//RooDataSet combData("combData","combined data",mll,Index(sample),Import("SF",*SFSample),Import("mm",*mmSample),Import("OF",*OFSample));
498	+	RooDataSet combData("combData","combined data",RooArgSet(mll,edgeWeight),RooFit::Index(sample),RooFit::Import("SF",*SFSample),RooFit::Import("OF",*OFSample),RooFit::WeightVar(edgeWeight));
499	+
500	+
501	+	//First we make a fit to opposite flavor
502	+	RooRealVar fttbarOF("fttbarOF", "fttbarOF", 100, 0, 10000);
503	+	RooRealVar par1ttbarOF("par1ttbarOF", "par1ttbarOF", 1.6, 0.01, 4.0);
504	+	RooRealVar par2ttbarOF("par2ttbarOF", "par2ttbarOF", 1.0);
505	+	RooRealVar par3ttbarOF("par3ttbarOF", "par3ttbarOF", 0.028, 0.001, 1.0);
506	+	RooRealVar par4ttbarOF("par4ttbarOF", "par4ttbarOF", 2.0);
507	+	RooSUSYBkgPdf ttbarOF("ttbarOF","ttbarOF", mll , par1ttbarOF, par2ttbarOF, par3ttbarOF, par4ttbarOF);
508	+	RooAddPdf model_OF("model_OF","model_OF", ttbarOF, fttbarOF);
509	+	RooSimultaneous simPdfOF("simPdfOF","simultaneous pdf", sample) ;
510	+	simPdfOF.addPdf(model_OF,"OF");
511	+	RooFitResult *resultOF = simPdfOF.fitTo(combData, RooFit::Save(),RooFit::Extended(),RooFit::Minos(true));
512	+	dout << "============================= < OF results > =============================" << endl;
513	+	resultOF->Print();
514	+	dout << "============================= < /OF results > =============================" << endl;
515	+
516	+
517	+	RooPlot* frameO = mll.frame(RooFit::Bins(int((mllmax-mllmin)/5.0)),RooFit::Title("OF sample"));
518	+	frameO->GetXaxis()->CenterTitle(1);
519	+	frameO->GetYaxis()->CenterTitle(1);
520	+	combData.plotOn(frameO,RooFit::Name("OFdata"),RooFit::Cut("sample==sample::OF")) ;
521	+	simPdfOF.plotOn(frameO,RooFit::Slice(sample,"OF"),RooFit::Name("FullFit"),RooFit::ProjWData(sample,combData), RooFit::LineColor(kBlack)) ;
522	+	simPdfOF.plotOn(frameO,RooFit::Slice(sample,"OF"),RooFit::Name("TTbarOFonly"),RooFit::Components("ttbarOF"),RooFit::ProjWData(sample,combData),RooFit::LineStyle(kDashed)) ;
523	+
524	+	TCanvas* pof = new TCanvas("pof","pof") ;
525	+	pof->cd() ;
526	+	gPad->SetLeftMargin(0.15);
527	+	frameO->GetYaxis()->SetTitleOffset(1.4);
528	+	frameO->Draw();
529	+	if(is_data==data) DrawPrelim();
530	+	else DrawPrelim(PlottingSetup::luminosity,true);
531	+	if(EdgeFitter::FixedMEdge>=0) CompleteSave(pof,"Edge/OF__OFFitonly_"+prefix.str()+"__MEdgeFix_"+any2string(EdgeFitter::FixedMEdge),false,false);
532	+	else CompleteSave(pof,"Edge/OF__OFFitonly_"+prefix.str(),false,false);
533	+	delete pof;
534	+
535	+	if(resultOF->covQual()!=3) {
536	+	write_error(__FUNCTION__,"OF fit did not converge!!! Cannot continue!");
537	+	dout << "covQual is " << resultOF->covQual() << endl;
538	+	EdgeFitter::FixedMEdgeChi2=-1;
539	+	if(EdgeFitter::RejectPointIfNoConvergence) return;
540	+	} else {
541	+	write_info(__FUNCTION__,"OF fit converged");
542	+	}
543	+
544	+	float StartingMedge=70;
545	+	if(EdgeFitter::FixedMEdge>0) StartingMedge=EdgeFitter::FixedMEdge;
546	+
547	+
548	+	RooDataSet *ZDataSet = (RooDataSet*)EdgeFitter::AllData->reduce("id1==id2 && abs(mll-91.2)<20");
549	+
550	+	float maxZ = ZDataSet->sumEntries();
551	+	dout << "maxZ was set to " << maxZ << endl;
552	+	delete ZDataSet;
553	+
554	+
555	+	// Now same flavor
556	+	RooRealVar fzSF("fzSF", "fzSF", 39, 39, maxZ);
557	+	RooRealVar meanzSF("meanzSF", "meanzSF", 91.1876, 89, 95);
558	+	//RooRealVar sigmazSF("sigmazSF", "sigmazSF", 0.5);
559	+	RooRealVar sigmazSF("sigmazSF", "sigmazSF", 5, 0.5, 5);
560	+	RooRealVar widthzSF("widthzSF", "widthzSF", 2.94);
561	+	widthzSF.setConstant();
562	+
563	+	RooRealVar fttbarSF("fttbarSF", "fttbarSF", 100, 0, 100000);
564	+	RooRealVar par1ttbarSF("par1ttbarSF", "par1ttbarSF", 1.02*par1ttbarOF.getVal(), (1.02-0.07)*par1ttbarOF.getVal(), (1.02+0.07)*par1ttbarOF.getVal());
565	+
566	+	RooRealVar fsignalSF("fsignalSF", "fsignalSF", 0, 0, 300);
567	+	RooRealVar par1signalSF("par1signalSF", "par1signalSF", 45, 20, 100);
568	+	RooRealVar par2signalSF("par2signalSF", "par2signalSF", 2, 1, 10);
569	+	RooRealVar par3signalSF("par3signalSF", "par3signalSF", StartingMedge, 0, 300);
570	+
571	+	RooVoigtian zSF("zSF", "zSF", mll, meanzSF, widthzSF, sigmazSF);
572	+
573	+	if(EdgeFitter::FixedMEdge>0) par3signalSF.setConstant();
574	+
575	+	RooSUSYBkgPdf ttbarSF("ttbarSF","ttbarSF", mll , par1ttbarSF, par2ttbarOF, par3ttbarOF, par4ttbarOF);
576	+	RooSUSYTPdf signalSF("signalSF","signalSF", mll , par1signalSF, sigmazSF, par3signalSF);
577	+
578	+	RooAddPdf model_SF("model_SF","model_SF", RooArgList(zSF, ttbarSF, signalSF), RooArgList(fzSF, fttbarSF, fsignalSF));
579	+
580	+	RooSimultaneous simPdf("simPdf","simultaneous pdf",sample) ;
581	+	simPdf.addPdf(model_SF,"SF") ;
582	+	simPdf.addPdf(model_OF,"OF") ;
583	+
584	+	RooFitResult *result = simPdf.fitTo(combData, RooFit::Save(), RooFit::Extended(),RooFit::Minos(true));
585	+
586	+	if(result->covQual()!=3) {
587	+	write_error(__FUNCTION__,"Full fit did not converge!!! Cannot continue!");
588	+	dout << "covQual is " << result->covQual() << endl;
589	+	EdgeFitter::FixedMEdgeChi2=-1;
590	+	if(EdgeFitter::RejectPointIfNoConvergence) return;
591	+	} else {
592	+	write_info(__FUNCTION__,"Full fit converged");
593	+	}
594	+
595	+	dout << "============================= < OF results > =============================" << endl;
596	+	result->Print();
597	+	dout << "============================= < /OF results > =============================" << endl;
598	+
599	+
600	+	RooPlot* frame1 = mll.frame(RooFit::Bins(int((mllmax-mllmin)/5.0)),RooFit::Title("EE sample")) ;
601	+	frame1->GetXaxis()->CenterTitle(1);
602	+	frame1->GetYaxis()->CenterTitle(1);
603	+	combData.plotOn(frame1,RooFit::Name("SFdata"),RooFit::Cut("sample==sample::SF")) ;
604	+	simPdf.plotOn(frame1,RooFit::Slice(sample,"SF"),RooFit::Name("FullFit"),RooFit::ProjWData(sample,combData), RooFit::LineColor(kBlack)) ;
605	+	simPdf.plotOn(frame1,RooFit::Slice(sample,"SF"),RooFit::Name("TTbarSFonly"),RooFit::Components("ttbarSF"),RooFit::ProjWData(sample,combData),RooFit::LineStyle(kDashed)) ;
606	+	simPdf.plotOn(frame1,RooFit::Slice(sample,"SF"),RooFit::Name("DYSFonly"),RooFit::Components("zSF"), RooFit::ProjWData(sample, combData), RooFit::LineStyle(kDashed), RooFit::LineColor(kRed));
607	+	simPdf.plotOn(frame1,RooFit::Slice(sample,"SF"),RooFit::Name("SignalSFonly"),RooFit::Components("signalSF"), RooFit::ProjWData(sample, combData), RooFit::LineStyle(kDashed), RooFit::LineColor(kGreen));
608	+
609	+	EdgeFitter::FixedMEdgeChi2 = frame1->chiSquare("FullFit", "SFdata", 3);
610	+
611	+
612	+	dout << "Result   : " << endl;
613	+	dout << "f signal : " << fsignalSF.getVal() << " +/- " << fsignalSF.getError() << endl;
614	+	dout << "f ttbar  : " << fttbarSF.getVal() << " +/- " << fttbarSF.getError() << endl;
615	+	dout << "f tt OF  : " << fttbarOF.getVal() << " +/- " << fttbarOF.getError() << endl;
616	+	dout << "f z SF   : " << fzSF.getVal() << " +/- " << fzSF.getError() << endl;
617	+	dout << "#Chi^{2}/NDF     : " << EdgeFitter::FixedMEdgeChi2 << endl;
618	+
619	+	// The same plot for the cointrol sample slice
620	+	RooPlot* frame3 = mll.frame(RooFit::Bins(int((mllmax-mllmin)/5.0)),RooFit::Title("OF sample")) ;
621	+	frame3->GetXaxis()->CenterTitle(1);
622	+	frame3->GetYaxis()->CenterTitle(1);
623	+	frame3->SetMaximum(frame1->GetMaximum());
624	+	combData.plotOn(frame3,RooFit::Cut("sample==sample::OF")) ;
625	+	simPdf.plotOn(frame3,RooFit::Slice(sample,"OF"),RooFit::ProjWData(sample,combData), RooFit::LineColor(kBlack)) ;
626	+	simPdf.plotOn(frame3,RooFit::Slice(sample,"OF"),RooFit::Components("ttbarOF"),RooFit::ProjWData(sample,combData),RooFit::LineStyle(kDashed)) ;
627	+
628	+
629	+	TCanvas* c = new TCanvas("rf501_simultaneouspdf","rf403_simultaneouspdf") ;
630	+	c->cd() ;
631	+	gPad->SetLeftMargin(0.15);
632	+	frame1->GetYaxis()->SetTitleOffset(1.4);
633	+	frame1->Draw();
634	+	if(is_data==data) DrawPrelim();
635	+	else DrawPrelim(PlottingSetup::luminosity,true);
636	+	stringstream infotext;
637	+	infotext << "#splitline{Fit results (" << EdgeFitter::Mode << ">" << jzb_cut << "): }{#splitline{";
638	+	infotext << "N(Data) = " << EdgeFitter::SFSample->sumEntries() << "}{#splitline{";
639	+	infotext << "N(Z+Jets) = " << WriteWithError(fzSF.getVal(),fzSF.getError(),3) << "}{#splitline{";
640	+	infotext << "N(t#bar{t}) = " << WriteWithError(fttbarSF.getVal(),fttbarSF.getError(),3) << "}{#splitline{";
641	+	infotext << "N(signal) = " << WriteWithError(fsignalSF.getVal(),fsignalSF.getError(),3) << "}{";
642	+	infotext << "m_{edge} = " << WriteWithError(par3signalSF.getVal(),par3signalSF.getError(),3) << "}}}}}";
643	+
644	+	TLatex *infobox = new TLatex(0.57,0.75,infotext.str().c_str());
645	+	infobox->SetNDC();
646	+	infobox->SetTextSize(0.03);
647	+	infobox->Draw();
648	+	if(EdgeFitter::FixedMEdge>=0) CompleteSave(c,"Edge/"+prefix.str()+"_SF__MEdgeFix_"+any2string(EdgeFitter::FixedMEdge),false,false);
649	+	else CompleteSave(c,"Edge/"+prefix.str()+"_SF",false,false);
650	+	delete c;
651	+
652	+	TCanvas* e = new TCanvas("rf501_simultaneouspdfem","rf403_simultaneouspdfem") ;
653	+	e->cd();
654	+	gPad->SetLeftMargin(0.15);
655	+	frame3->GetYaxis()->SetTitleOffset(1.4);
656	+	frame3->Draw();
657	+	if(is_data==data) DrawPrelim();
658	+	else DrawPrelim(PlottingSetup::luminosity,true);
659	+	if(EdgeFitter::FixedMEdge>=0) CompleteSave(e,"Edge/"+prefix.str()+"_OF__MEdgeFix_"+any2string(EdgeFitter::FixedMEdge),false,false);
660	+	else CompleteSave(e,"Edge/"+prefix.str()+"_OF",false,false);
661	+	delete e;
662	+
663	+
664	+
665	+
666	+	/*  TCanvas* f = new TCanvas("rf501_simultaneouspdfem","rf403_simultaneouspdfem") ;
667	+	f->cd();
668	+	gPad->SetLeftMargin(0.15);
669	+	frame4->GetYaxis()->SetTitleOffset(1.4);
670	+	frame4->Draw();
671	+	if(is_data==data) DrawPrelim();
672	+	else DrawPrelim(PlottingSetup::luminosity,true);
673	+	CompleteSave(f,"Edge/"+prefix.str()+"_SF");
674	+	delete f;*/
675	+
676	+
677	+	/*
678	+	float maxZ=200;
679	+	RooWorkspace* wspace = new RooWorkspace();
680	+	stringstream mllvar;
681	+	mllvar << "mll[" << (mllmax-mllmin)/2 << "," << mllmin << "," << mllmax << "]";
682	+	wspace->factory(mllvar.str().c_str());
683	+	wspace->var("mll")->setBins(30);
684	+	wspace->factory("nSig[1.,0.,100.]");
685	+	wspace->factory(("nZ[0.04.,0.,"+any2string(maxZ)+"]").c_str());
686	+	wspace->factory("rME[1.12,1.05,1.19]");
687	+	wspace->factory("effUncert[1.]");
688	+	EdgeFitter::prepareLimits(wspace, true);
689	+	*/
690	+
691	+	write_warning(__FUNCTION__," A lot missing here to calculate limits");
692	+
693	+	}
694	+
695		void EdgeFitter::DoEdgeFit(string mcjzb, string datajzb, float DataPeakError, float MCPeakError, float jzb_cut, int icut, int is_data, TCut cut, TTree *signalevents=0) {
696
697	<	string storagefile=EdgeFitter::RandomStorageFile();
698	<	TFile *f = new TFile(storagefile.c_str(),"RECREATE");
699	<	EdgeFitter::InitializeVariables(iMllLow,iMllHigh,jzbHigh,cut);
700	<
701	<	Yield Zestimate=EdgeFitter::Get_Z_estimate(jzb_cut,icut);
233	<	Yield Testimate=EdgeFitter::Get_T_estimate(jzb_cut,icut);
234	<	cout << "Cut at JZB>" << jzb_cut << "; using estimates: " << endl;
235	<	cout << "       Z : " << Zestimate  << endl;
236	<	cout << "       T : " << Testimate  << endl;
697	>	TCut _cut(cut&&PlottingSetup::basiccut&&PlottingSetup::passtrig);
698	>
699	>	TFile *f = new TFile("workingfile.root","RECREATE");
700	>
701	>	EdgeFitter::InitializeVariables(PlottingSetup::iMllLow,PlottingSetup::iMllHigh,PlottingSetup::jzbHigh,_cut);
702
703		EdgeFitter::PrepareDatasets(is_data);
704	+
705	+	EdgeFitter::DrawDatasetContent(is_data);
706	+
707	+	RooFit::MsgLevel msglevel = RooMsgService::instance().globalKillBelow();
708	+	RooMsgService::instance().setGlobalKillBelow(RooFit::FATAL);
709	+
710	+
711	+	bool ScanMassRange=false;
712	+	float ScanSteps=5.0;//GeV
713	+
714	+
715	+
716	+	if(ScanMassRange) {
717	+	TFile *fscan = new TFile("fscan.root","UPDATE");
718	+	TGraph *gr = new TGraph();
719	+	stringstream GrName;
720	+	GrName << "ScanGraphFor_" << EdgeFitter::Mode << "_" << jzb_cut;
721	+	gr->SetName(GrName.str().c_str());
722
723	<	EdgeFitter::eeSample->Write();
724	<	EdgeFitter::emSample->Write();
725	<	EdgeFitter::mmSample->Write();
726	<	EdgeFitter::AllData->Write();
727	<	f->Close();
723	>	int i=0;
724	>	for(float tempMedge=10;tempMedge<=300;tempMedge+=ScanSteps) {
725	>	write_info(__FUNCTION__,"Now testing Medge="+any2string(tempMedge)+" for "+EdgeFitter::Mode+">"+any2string(jzb_cut));
726	>	EdgeFitter::FixedMEdge=tempMedge;
727	>	EdgeFitter::DoFit(is_data, jzb_cut);
728	>	if(EdgeFitter::FixedMEdgeChi2<0) continue;
729	>	gr->SetPoint(i,tempMedge,EdgeFitter::FixedMEdgeChi2);
730	>	i++;
731	>	}
732	>
733	>	TCanvas *ScanCan = new TCanvas("ScanCan","ScanCan",500,500);
734	>	gr->GetXaxis()->SetTitle("m_{edge}");
735	>	gr->GetXaxis()->CenterTitle();
736	>	gr->GetYaxis()->SetTitle("#Chi^{2} / NDF");
737	>	gr->GetYaxis()->CenterTitle();
738	>	gr->GetYaxis()->SetTitleOffset(0.95);
739	>	gr->GetXaxis()->SetTitleOffset(0.9);
740	>	gr->SetLineColor(kBlue);
741	>	gr->SetTitle("");
742	>	gr->Draw("AL");
743	>	stringstream ScanCanSave;
744	>	ScanCanSave << "Edge/MEdgeScan_"+EdgeFitter::Mode+"_" << jzb_cut;
745	>	if(is_data) DrawPrelim();
746	>	else DrawMCPrelim();
747	>	CompleteSave(ScanCan,ScanCanSave.str());
748	>	fscan->cd();
749	>	gr->Write();
750	>	delete ScanCan;
751	>	fscan->Close();
752	>	} else {
753	>	EdgeFitter::DoFit(is_data, jzb_cut);
754	>	}
755	>
756	>
757	>
758	>
759	>	EdgeFitter::DoFit(is_data, jzb_cut);
760	>	RooMsgService::instance().setGlobalKillBelow(msglevel);
761	>
762
763	<	write_warning(__FUNCTION__,"Work continues here");
763	>	f->Close();
764
248	–	if(EdgeFitter::MarcoDebug) write_warning(__FUNCTION__,"Need to uncomment the next line (remove the output file)");
249	–	//  gSystem->Exec(("rm "+storagefile).c_str());
765		}
766
767		void DoEdgeFit(string mcjzb, string datajzb, float DataPeakError, float MCPeakError, vector<float> jzb_cut, int is_data, TCut cut, TTree *signalevents=0) {
768	<	for(int icut=0;icut<jzb_cut.size();icut++) {
768	>
769	>	EdgeFitter::Mode="JZB";
770	>	if(mcjzb=="met[4]") EdgeFitter::Mode="MET";
771	>
772	>	for(int icut=0;icut<(int)jzb_cut.size();icut++) {
773		stringstream addcut;
774		if(is_data==1) addcut << "(" << datajzb << ">" << jzb_cut[icut] << ")";
775		if(is_data!=1) addcut << "(" << mcjzb << ">" << jzb_cut[icut] << ")";
776		TCut jcut(addcut.str().c_str());
777
778	+
779		EdgeFitter::DoEdgeFit(mcjzb, datajzb, DataPeakError, MCPeakError, jzb_cut[icut], icut, is_data, jcut&&cut, signalevents);
780
781		}

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