29 std::string extraWeight(
"w_lumi/weight");
30 std::string extraWeightTopPt(
"w_lumi*w_toppt/weight");
34 TString folder_links=
"/homes/cawest/links/";
36 vector<TString> s_tt_MLM;
37 s_tt_MLM.push_back(
filestring(
"TTJets_TuneCUETP8M1_13TeV-madgraphMLM",
false));
39 vector<TString> s_tt_amcatnlo;
40 s_tt_amcatnlo.push_back(
filestring(
"TTJets_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8",
false));
42 vector<TString> s_tt_powheg;
43 s_tt_powheg.push_back(
filestring(
"TT_TuneCUETP8M1_13TeV-powheg-pythia8",
false));
46 vector<sfeats> Samples;
48 Samples.back().doStack =
false;
50 Samples.back().doStack =
false;
53 Samples.push_back(
sfeats(s_tt_amcatnlo,
"t#bar{t}, aMC@NLO (NLO, FxFx)", kBlack, 1,
cutandweight(
"1", extraWeight)));
54 Samples.back().doStack =
false;
58 vector<int> ra4_sam, ra4_sam_ns;
59 unsigned nsam(Samples.size());
60 for(
unsigned sam(0); sam < nsam; sam++){
61 ra4_sam.push_back(sam);
66 TString cuts(
"(nmus+nels)==1");
72 std::vector<TString> cutlist = {
"(nmus+nels)==0",
74 "(nmus+nels)==0&&nbm>=1&&mj>500&&njets>=6&&ht>1500",
75 "(nmus+nels)==1&&nbm>=1&&mj>500&&njets>=6&&ht>1200"};
76 for(
auto icut : cutlist) {
77 vars.push_back(
hfeats(
"ht",40, 0, 4000, ra4_sam,
"H_{T} (GeV)", icut));
78 vars.push_back(
hfeats(
"mj",25, 0, 2500, ra4_sam,
"M_{J} (GeV)", icut));
79 vars.push_back(
hfeats(
"nbm",6, 0, 6, ra4_sam,
"N_{b}", icut));
80 vars.push_back(
hfeats(
"njets",20, 0, 20, ra4_sam,
"N_{jets}", icut));
86 cuts =
"(nmus+nels)==1&&ht>1000&&ht<1500&&nbm>=1";
87 vars.push_back(
hfeats(
"njets",15, 0, 15, ra4_sam,
"N_{jets}", cuts));
88 vars.back().normalize =
true;
89 cuts =
"(nmus+nels)==1&&ht>1000&&ht<1500&&nbt>=1&&njets==5";
90 vars.push_back(
hfeats(
"nbt",6, 0, 6, ra4_sam,
"N_{b,tight}", cuts));
91 vars.back().normalize =
true;
92 cuts =
"(nmus+nels)==1&&ht>1000&&ht<1500&&nbm>=1&&njets==5";
93 vars.push_back(
hfeats(
"nbm",6, 0, 6, ra4_sam,
"N_{b}", cuts));
94 vars.back().normalize =
true;
95 vars.push_back(
hfeats(
"mj",12, 0, 600, ra4_sam,
"M_{J} (GeV)", cuts));
96 vars.back().normalize =
true;
97 vars.push_back(
hfeats(
"Max$(jets_pt)",20, 0, 1000, ra4_sam,
"p_{T1} (GeV)", cuts));
98 vars.back().normalize =
true;
99 vars.push_back(
hfeats(
"(jets_csv-0.89)/0.11", 10, 0, 1, ra4_sam,
"(CSV-CSV_{cut})/(CSV_{max}-CSV_{cut})", cuts));
100 vars.back().normalize =
true;
void plot_distributions(std::vector< sfeats > Samples, std::vector< hfeats > vars, TString luminosity="10", TString filetype=".eps", TString namestyle="LargeLabels", TString dir="1d", bool doRatio=false, bool showcuts=false)
std::string cutandweight(std::string cut, std::string weight)
TString filestring(TString dataset, bool isSkimmed=true)