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#include <iostream> |
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#include <utility> |
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#include "TH1F.h" |
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#include "TObjArray.h" |
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#include "TFractionFitter.h" |
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#include "TRandom3.h" |
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#include "TCanvas.h" |
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#include "TSlider.h" |
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#include "TF1.h" |
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//gROOT->SetStyle("Plain"); |
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//gStyle->SetOptStat(0); |
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~toyMC(); |
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|
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void load_templates(); |
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void load_syst_templates(); |
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void load_ejets_templates(); |
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int do_fit(TH1F * _data); |
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|
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// |
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//_____ Fix bkg2 fraction to qcd_frac _________________________________ |
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// Do not fix if qcd_frac is negative |
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// |
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int do_fit(TH1F * _data, double qcd_frac=-1.0); |
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int generate_toy(int n_sig, int n_phys, int n_qcd); |
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int generate_toy_from_syst(int n_sig, int n_phys, int n_qcd); |
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void set_overflow_bins(TH1F * h); |
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void debug_hist(TH1F * h); |
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int fit_data(void); |
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int fit_data_stacked(void); |
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// returns pair<mean,width> |
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std::pair<double,double> do_toys(double n_sig, double n_bkg1, double n_bkg2, int n_exp=100); |
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TH1F * wzjets; |
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TH1F * qcd; |
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// templates for systematics |
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TH1F * ttbar_s; |
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TH1F * wzjets_s; |
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TH1F * qcd_s; |
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|
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int n_bins; |
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TObjArray * mc; |
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void toyMC::load_templates(){ |
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TFile * data_file = new TFile("./TMVApp-data-16may2009.root","READ"); |
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//TFile * data_file = new TFile("./TMVApp-data-16may2009.root","READ"); |
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TFile * data_file = new TFile("./TMVApp-data-31may2009.root","READ"); |
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TTree * t_data = (TTree *)data_file->Get("classifier"); |
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// |
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//_____ Phys template w and tW fixed |
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// |
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TFile * phys_template_file = new TFile("TMVApp-phys-30may2009.root"); |
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TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ nominal templates |
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// |
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TFile * ttbar_phys_template_file = new TFile("./TMVA.root","READ"); |
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TFile * qcd_template_file = new TFile("./TMVApp-qcd-16may2009.root","READ"); |
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TTree * t_data = (TTree *)data_file->Get("classifier"); |
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TTree * t_ttbar_phys = (TTree *)ttbar_phys_template_file->Get("TestTree"); |
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// |
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TTree * t_ttbar = (TTree *)ttbar_phys_template_file->Get("TestTree"); |
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//TTree * t_phys = (TTree *)ttbar_phys_template_file->Get("TestTree"); |
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TTree * t_qcd = (TTree *)qcd_template_file->Get("classifier"); |
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// |
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//_____ ISR/FSR |
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// |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-pedros-nominalISRFSR.root"); |
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//TTree * t_ttbar = (TTree *)ttbar_template_file->Get("classifier"); |
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// |
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//_____ systematics templates |
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// |
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/*********************** |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-jes-up-22may2009.root"); |
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//TFile * phys_template_file = new TFile("TMVApp-phys-jes-up-22may2009.root"); |
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//TFile * qcd_template_file = new TFile("TMVApp-qcd-jes-up-22may2009.root"); |
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// |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-jes-down-22may2009.root"); |
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//TFile * phys_template_file = new TFile("TMVApp-phys-jes-down-22may2009.root"); |
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//TFile * qcd_template_file = new TFile("TMVApp-qcd-jes-down-22may2009.root"); |
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// |
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//TTree * t_ttbar = (TTree *)ttbar_template_file->Get("classifier"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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//TTree * t_qcd = (TTree *)qcd_template_file->Get("classifier"); |
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************************/ |
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delete data; |
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delete ttbar; |
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delete wzjets; |
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t_data -> Draw("MVA_BDT>>data"); |
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pad->SaveAs("mu_data.eps"); |
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pad = c1->cd(2); |
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t_ttbar_phys -> Draw("MVA_BDT>>ttbar","type==1"); |
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t_ttbar -> Draw("MVA_BDT>>ttbar","type==1"); |
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//t_ttbar -> Draw("MVA_BDT>>ttbar"); |
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pad->SaveAs("mu_ttbar_template.eps"); |
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pad = c1->cd(3); |
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t_ttbar_phys -> Draw("MVA_BDT>>wzjets","type==0"); |
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//t_phys -> Draw("MVA_BDT>>wzjets","type==0"); |
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t_phys -> Draw("MVA_BDT>>wzjets"); |
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pad->SaveAs("mu_wzjets_template.eps"); |
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pad = c1->cd(4); |
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t_qcd -> Draw("MVA_BDT>>qcd"); |
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} |
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void toyMC::load_syst_templates(){ |
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//TFile * ttbar_template_file = new TFile("./TMVApp-phys-tauola-22may2009.root","READ"); |
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//TFile * ttbar_template_file = new TFile("TMVApp-ttbar-ISR_FSR_larger-23may2009.root"); |
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//TFile * ttbar_template_file = new TFile("TMVApp-ttbar-ISR_FSR_smaller-23may2009.root"); |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-pedros-nominalISRFSR.root"); |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-pedros-largerISRFSR.root"); |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-pedros-smallISRFSR.root"); |
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// |
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//_____ JES systematics |
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// |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-jes-up-22may2009.root"); |
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//TFile * phys_template_file = new TFile("TMVApp-phys-jes-up-22may2009.root"); |
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//TFile * qcd_template_file = new TFile("TMVApp-qcd-jes-up-22may2009.root"); |
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// |
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//TFile * ttbar_template_file = new TFile("TMVApp-TTJets-jes-down-22may2009.root"); |
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//TFile * phys_template_file = new TFile("TMVApp-phys-jes-down-22may2009.root"); |
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//TFile * qcd_template_file = new TFile("TMVApp-qcd-jes-down-22may2009.root"); |
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// |
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//TTree * t_ttbar = (TTree *)ttbar_template_file->Get("classifier"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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//TTree * t_qcd = (TTree *)qcd_template_file->Get("classifier"); |
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// |
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//_____ WJets threshold 20 GeV |
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// |
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//TFile * phys_template_file = new TFile("TMVApp-phys-WJets-threshold20-23may2009.root"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ WJets threshold 5 GeV |
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// |
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//TFile * phys_template_file = new TFile("TMVApp-phys-WJets-threshold5-23may2009.root"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ WJets Q^2 scale up |
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// |
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//TFile * phys_template_file = new TFile("TMVApp-phys-WJets-scaleup-28may2009.root"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ WJets Q^2 scale down |
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// |
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//TFile * phys_template_file = new TFile("TMVApp-phys-WJets-scaledown-28may2009.root"); |
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//TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ Phys template w and tW fixed |
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// |
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TFile * phys_template_file = new TFile("TMVApp-phys-30may2009.root"); |
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TTree * t_phys = (TTree *)phys_template_file->Get("classifier"); |
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// |
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//_____ nominal |
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// |
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TFile * ttbar_phys_template_file = new TFile("./TMVA.root","READ"); |
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TFile * qcd_template_file = new TFile("./TMVApp-qcd-16may2009.root","READ"); |
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// |
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TTree * t_ttbar = (TTree *)ttbar_phys_template_file->Get("TestTree"); |
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//TTree * t_ttbar = (TTree *)ttbar_template_file->Get("classifier"); |
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//TTree * t_phys = (TTree *)ttbar_phys_template_file->Get("TestTree"); |
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TTree * t_qcd = (TTree *)qcd_template_file->Get("classifier"); |
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|
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delete ttbar_s; |
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delete wzjets_s; |
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delete qcd_s; |
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ttbar_s = new TH1F("ttbar_s" ,"ttbar_s" ,n_bins, -0.8, 0.8); |
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wzjets_s = new TH1F("wzjets_s","wzjets_s",n_bins, -0.8, 0.8); |
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qcd_s = new TH1F("qcd_s" ,"qcd_s" ,n_bins, -0.8, 0.8); |
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|
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// |
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ttbar_s->SetFillColor(42); |
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//ttbar_s->SetFillStyle(4050); |
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wzjets_s->SetFillColor(46); |
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//wzjets_s->SetFillStyle(4050); |
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qcd_s->SetFillColor(48); |
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//TSlider *slider = 0; |
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// |
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|
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TCanvas * c1 = new TCanvas("canvas1","canvas1",800,600); |
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c1->Divide(2,2); |
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TVirtualPad * pad = c1->cd(1); |
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// |
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pad = c1->cd(2); |
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t_ttbar -> Draw("MVA_BDT>>ttbar_s","type==1"); |
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//t_ttbar -> Draw("MVA_BDT>>ttbar_s"); |
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pad->SaveAs("mu_ttbar_s_template.eps"); |
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// |
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pad = c1->cd(3); |
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//t_phys -> Draw("MVA_BDT>>wzjets_s","type==0"); |
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t_phys -> Draw("MVA_BDT>>wzjets_s"); |
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pad->SaveAs("mu_wzjets_s_template.eps"); |
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// |
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pad = c1->cd(4); |
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t_qcd -> Draw("MVA_BDT>>qcd_s"); |
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pad->SaveAs("mu_qcd_s_template.eps"); |
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|
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set_overflow_bins(ttbar_s); |
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set_overflow_bins(wzjets_s); |
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set_overflow_bins(qcd_s); |
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} |
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|
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|
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void toyMC::load_ejets_templates(){ |
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TFile * data_file = new TFile("./TMVApp-data-electron-18may2009.root","READ"); |
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//TFile * data_file = new TFile("./TMVApp-data-electron_noqcd.root","READ"); |
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} |
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|
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< |
int toyMC::do_fit(TH1F * _data){ |
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> |
int toyMC::do_fit(TH1F * _data, double qcd_frac){ |
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delete fit; |
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fit = new TFractionFitter(_data, mc); // initialise |
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|
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fit->Constrain(1,0.0,1.0); // constrain fraction 1 to be between 0 and 1 |
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fit->Constrain(2,0.0,1.0); |
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< |
//fit->Constrain(3,0.0,1.0); |
| 375 |
< |
|
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> |
if (qcd_frac<0.0){ |
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> |
fit->Constrain(3,0.0,1.0); |
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> |
} |
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> |
else{ |
| 378 |
> |
fit->Constrain(3,qcd_frac-0.000001,qcd_frac+0.000001); // constrain fraction 1 to be between 0 and 1 |
| 379 |
> |
} |
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//fit->Constrain(2,0.1651865,0.1651866); |
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//fit->Constrain(3,0.024999,0.025001); |
| 382 |
< |
fit->Constrain(3,0.176895306858,0.176895306860); |
| 382 |
> |
//fit->Constrain(3,0.176895306858,0.176895306860); |
| 383 |
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//fit->Constrain(3,0.37259,0.37261); |
| 384 |
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//fit->Constrain(3,0.036759,0.036761); // mu+jets true |
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//fit->Constrain(3,0.017379,0.017381); // mu+jets ABCD |
| 386 |
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//fit->Constrain(3,0.4422735,0.4422736); |
| 387 |
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// |
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– |
//double qcd_frac = (double)n_gen_bkg2/(double)(n_gen_sig+n_gen_bkg1+n_gen_bkg2); |
| 240 |
– |
//fit->Constrain(3,qcd_frac-0.000001,qcd_frac+0.000001); // constrain fraction 1 to be between 0 and 1 |
| 241 |
– |
// |
| 388 |
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fit->SetRangeX(1,n_bins); // use only some bins to fit |
| 389 |
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Int_t status = fit->Fit(); // perform the fit |
| 390 |
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if (status!=0) status = fit->Fit(); |
| 408 |
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} |
| 409 |
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*/ |
| 410 |
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|
| 411 |
+ |
// |
| 412 |
+ |
//_____ generates a pseudoexperiment, given n_events, smears by Poisson _ |
| 413 |
+ |
// |
| 414 |
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int toyMC::generate_toy(int n_sig, int n_bg, int n_qcd){ |
| 415 |
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int n_events=0; |
| 416 |
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delete toy_data; |
| 433 |
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for (int i=0;i<_nbg;i++){ |
| 434 |
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toy_data->Fill(wzjets->GetRandom()); |
| 435 |
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} |
| 436 |
+ |
|
| 437 |
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for (int i=0;i<_nqcd;i++){ |
| 438 |
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toy_data->Fill(qcd->GetRandom()); |
| 439 |
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} |
| 443 |
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//return _nsig; |
| 444 |
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} |
| 445 |
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|
| 446 |
+ |
// |
| 447 |
+ |
//_____ generates a pseudoexperiment, given n_events, smears by Poisson _ |
| 448 |
+ |
// |
| 449 |
+ |
int toyMC::generate_toy_from_syst(int n_sig, int n_bg, int n_qcd){ |
| 450 |
+ |
int n_events=0; |
| 451 |
+ |
delete toy_data; |
| 452 |
+ |
|
| 453 |
+ |
toy_data = new TH1F("toy_data" ,"toy_data" ,n_bins, -0.8, 0.8); |
| 454 |
+ |
|
| 455 |
+ |
int _nsig = _random.Poisson(n_sig); |
| 456 |
+ |
int _nbg = _random.Poisson(n_bg); |
| 457 |
+ |
int _nqcd = _random.Poisson(n_qcd); |
| 458 |
+ |
//int _nqcd = n_qcd; |
| 459 |
+ |
|
| 460 |
+ |
n_gen_sig = _nsig; |
| 461 |
+ |
n_gen_bkg1 = _nbg; |
| 462 |
+ |
n_gen_bkg2 = _nqcd; |
| 463 |
+ |
n_events = _nsig+_nbg+_nqcd; |
| 464 |
+ |
|
| 465 |
+ |
for (int i=0;i<_nsig;i++){ |
| 466 |
+ |
toy_data->Fill(ttbar_s->GetRandom()); |
| 467 |
+ |
} |
| 468 |
+ |
for (int i=0;i<_nbg;i++){ |
| 469 |
+ |
toy_data->Fill(wzjets_s->GetRandom()); |
| 470 |
+ |
} |
| 471 |
+ |
|
| 472 |
+ |
for (int i=0;i<_nqcd;i++){ |
| 473 |
+ |
toy_data->Fill(qcd_s->GetRandom()); |
| 474 |
+ |
} |
| 475 |
+ |
//toy_data->Draw(); |
| 476 |
+ |
set_overflow_bins(toy_data); |
| 477 |
+ |
return n_events; |
| 478 |
+ |
//return _nsig; |
| 479 |
+ |
} |
| 480 |
+ |
|
| 481 |
|
void toyMC::set_overflow_bins(TH1F * h){ |
| 482 |
|
Int_t _last_bin = h->GetNbinsX(); |
| 483 |
|
Double_t _overflow = h->GetBinContent(_last_bin+1); |
| 484 |
< |
Int_t n_entries = h->GetEntries(); |
| 484 |
> |
Int_t n_entries = (Int_t)h->GetEntries(); |
| 485 |
|
//h->ResetBit(TH1::kCanRebin); |
| 486 |
|
h->AddBinContent(1,h->GetBinContent(0)); |
| 487 |
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h->AddBinContent(_last_bin,_overflow); |
| 504 |
|
int toyMC::fit_data(){ |
| 505 |
|
//load_templates(); |
| 506 |
|
//load_ejets_templates(); |
| 507 |
< |
int _res = do_fit(data); |
| 507 |
> |
int _res = do_fit(data,0.0162116); |
| 508 |
|
int n_data = data->GetEntries(); |
| 509 |
|
TH1F * result = (TH1F*) fit->GetPlot(); |
| 510 |
|
result->SetFillColor(16); |
| 533 |
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} |
| 534 |
|
|
| 535 |
|
|
| 536 |
+ |
int toyMC::fit_data_stacked(){ |
| 537 |
+ |
//load_templates(); |
| 538 |
+ |
//load_ejets_templates(); |
| 539 |
+ |
int _res = do_fit(data,0.0162116); |
| 540 |
+ |
int n_data = data->GetEntries(); |
| 541 |
+ |
TH1F * result = (TH1F*) fit->GetPlot(); |
| 542 |
+ |
result->SetFillColor(16); |
| 543 |
+ |
//result->SetFillStyle(4050); |
| 544 |
+ |
data->SetMinimum(0); |
| 545 |
+ |
TCanvas * c = new TCanvas("canvas2","canvas2",800,600); |
| 546 |
+ |
data->Draw("Ep"); |
| 547 |
+ |
//result->Draw("same"); |
| 548 |
+ |
// |
| 549 |
+ |
Double_t value,error; |
| 550 |
+ |
fit->GetResult(0,value,error); |
| 551 |
+ |
ttbar->Scale(n_data*value/ttbar->Integral()); |
| 552 |
+ |
// |
| 553 |
+ |
fit->GetResult(1,value,error); |
| 554 |
+ |
wzjets->Scale(n_data*value/wzjets->Integral()); |
| 555 |
+ |
// |
| 556 |
+ |
fit->GetResult(2,value,error); |
| 557 |
+ |
qcd->Scale(n_data*value/qcd->Integral()); |
| 558 |
+ |
// |
| 559 |
+ |
wzjets->Add(qcd); |
| 560 |
+ |
ttbar->Add(wzjets); |
| 561 |
+ |
// |
| 562 |
+ |
ttbar->Draw("same"); |
| 563 |
+ |
wzjets->Draw("same"); |
| 564 |
+ |
qcd->Draw("same"); |
| 565 |
+ |
data->Draw("Ep:same"); |
| 566 |
+ |
// |
| 567 |
+ |
c->SaveAs("fit.eps"); |
| 568 |
+ |
return _res; |
| 569 |
+ |
} |
| 570 |
+ |
|
| 571 |
+ |
|
| 572 |
+ |
|
| 573 |
+ |
std::pair<double,double> toyMC::do_toys(double n_sig, double n_bkg1, double n_bkg2, int n_exp){ |
| 574 |
+ |
pair<double, double> result; |
| 575 |
|
|
| 352 |
– |
std::pair<double,double> toyMC::do_toys(double n_sig, double n_bkg1, double n_bkg2, int n_exp=100){ |
| 576 |
|
double n_total = n_sig+n_bkg1+n_bkg2; |
| 577 |
|
|
| 355 |
– |
//load_templates(); |
| 356 |
– |
//load_ejets_templates(); |
| 578 |
|
TH1F * toy_mean = new TH1F("mean" ,"ttbar signal yield" ,50, n_sig-5.0*sqrt(n_sig), n_sig+5.0*sqrt(n_sig)); |
| 579 |
|
TH1F * toy_error = new TH1F("error" ,"ttbar signal yield error" ,50, 0, 3.0*sqrt(n_sig)); |
| 580 |
|
TH1F * toy_pull = new TH1F("pull" ,"pull" ,50, -3, 3); |
| 582 |
|
toy_error->SetFillColor(44); |
| 583 |
|
toy_pull->SetFillColor(44); |
| 584 |
|
for (int i=0;i<n_exp;i++){ |
| 585 |
< |
generate_toy(n_sig,n_bkg1,n_bkg2); |
| 585 |
> |
double n_bkg2_smeared = n_bkg2; |
| 586 |
> |
/************ |
| 587 |
> |
//_____ smear qcd rate due to xsec uncertainty |
| 588 |
> |
// |
| 589 |
> |
n_bkg2_smeared = -1.0; |
| 590 |
> |
while (n_bkg2_smeared < 0.0){ |
| 591 |
> |
n_bkg2_smeared = _random.Gaus(n_bkg2,n_bkg2); |
| 592 |
> |
} |
| 593 |
> |
*************/ |
| 594 |
> |
//generate_toy(n_sig,n_bkg1,n_bkg2_smeared); |
| 595 |
> |
generate_toy_from_syst(n_sig,n_bkg1,n_bkg2_smeared); |
| 596 |
|
int _ttbar = n_gen_sig; |
| 597 |
< |
int status = do_fit(toy_data); |
| 597 |
> |
double n_gen_total = (double)(n_gen_sig + n_gen_bkg1 + n_gen_bkg2); |
| 598 |
> |
// |
| 599 |
> |
//_____ nominal |
| 600 |
> |
// |
| 601 |
> |
double qcd_rate = 9.5; |
| 602 |
> |
// |
| 603 |
> |
//_____ nominal |
| 604 |
> |
// |
| 605 |
> |
//double qcd_rate = 6.175; |
| 606 |
> |
//double qcd_rate = 16.625; |
| 607 |
> |
// |
| 608 |
> |
//double qcd_rate = 19.0; |
| 609 |
> |
//double qcd_rate = 0.0; |
| 610 |
> |
// ABCD uncertainty: |
| 611 |
> |
//double qcd_rate = 16.6; |
| 612 |
> |
//double qcd_rate = 2.4; |
| 613 |
> |
double qcd_rate_err = 7.1; |
| 614 |
> |
double qcd_rate_smeared = qcd_rate; |
| 615 |
> |
/************* |
| 616 |
> |
//_____ smearing of the ABCD prediction |
| 617 |
> |
// |
| 618 |
> |
double qcd_rate_smeared = -1.0; |
| 619 |
> |
while (qcd_rate_smeared < 0.0){ |
| 620 |
> |
qcd_rate_smeared = _random.Gaus(qcd_rate,qcd_rate_err); |
| 621 |
> |
} |
| 622 |
> |
**************/ |
| 623 |
> |
double qcd_frac = qcd_rate_smeared/(double)(n_gen_sig+n_gen_bkg1+n_gen_bkg2); |
| 624 |
> |
int status = do_fit(toy_data, qcd_frac); |
| 625 |
|
if (status==0){ |
| 626 |
|
Double_t value,error; |
| 627 |
|
fit->GetResult(0,value,error); |
| 628 |
< |
toy_mean->Fill(value*n_total); |
| 629 |
< |
toy_error->Fill(error*n_total); |
| 630 |
< |
//toy_pull->Fill((value-n_sig/n_total)/error); |
| 631 |
< |
toy_pull->Fill((value-(Double_t)_ttbar/n_total)/error); |
| 628 |
> |
toy_mean->Fill(value*n_gen_total); |
| 629 |
> |
toy_error->Fill(error*n_gen_total); |
| 630 |
> |
//toy_pull->Fill((value*n_gen_total-(Double_t)_ttbar)/n_gen_total/error); |
| 631 |
> |
toy_pull->Fill((value*n_gen_total-n_sig)/n_gen_total/error); |
| 632 |
|
} |
| 633 |
|
} |
| 634 |
|
TCanvas * c = new TCanvas("canvas","canvas",800,600); |
| 635 |
|
c->Divide(2,2); |
| 636 |
|
TVirtualPad * pad = c->cd(1); |
| 637 |
|
toy_mean->Fit("gaus"); |
| 638 |
+ |
TF1 * _fit = toy_mean->GetFunction("gaus"); |
| 639 |
+ |
result.first = _fit->GetParameter(1); |
| 640 |
+ |
result.second = _fit->GetParError(1); |
| 641 |
+ |
//result.second = _fit->GetParameter(2); |
| 642 |
|
pad->SaveAs("mean.eps"); |
| 643 |
|
pad = c->cd(2); |
| 644 |
|
toy_error->Draw(); |
| 647 |
|
toy_pull->Fit("gaus"); |
| 648 |
|
pad->SaveAs("pull.eps"); |
| 649 |
|
|
| 650 |
+ |
return result; |
| 651 |
|
} |
