def test_multiple_retrieval_vector(self):
"""
Test a TQTreeFormulaObservable can be created/retrieved via TQObservable
and retrieved again with exactly the same expression.
"""
o1 = TQObservable.getObservable("VecBranch(tau_pt)", self.tags)
self.assertTrue(o1)
self.assertTrue(o1.initialize(self.sample))
o2 = TQObservable.getObservable("VecBranch(tau_pt)", self.tags)
self.assertTrue(o2)
self.assertTrue(o2.initialize(self.sample))
self.assertEqual(o1, o2)
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertEqual(o1.getNevaluations(), 2)
self.assertAlmostEqual(o1.getValueAt(0), 1.42)
self.assertAlmostEqual(o1.getValueAt(1), 2.72)
self.assertEqual(o2.getNevaluations(), 2)
self.assertAlmostEqual(o2.getValueAt(0), 1.42)
self.assertAlmostEqual(o2.getValueAt(1), 2.72)
def test_multiple_retrieval_scalar_tags(self):
"""
Test a TQTreeFormulaObservable can be created/retrieved via TQObservable
and retrieved again with exactly the same expression when tags are
involved.
"""
o1 = TQObservable.getObservable("$(a)", self.tags)
self.assertTrue(o1)
self.assertTrue(o1.initialize(self.sample))
o2 = TQObservable.getObservable("$(a)", self.tags)
self.assertTrue(o2)
self.assertTrue(o2.initialize(self.sample))
o3 = TQObservable.getObservable("n_taus", self.tags)
self.assertTrue(o3)
self.assertTrue(o3.initialize(self.sample))
self.assertEqual(o1, o2)
self.assertEqual(o1, o3)
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertEqual(o2.getNevaluations(), 1)
self.assertAlmostEqual(o2.getValue(), 3.14)
self.assertEqual(o1.getNevaluations(), 1)
self.assertAlmostEqual(o1.getValue(), 3.14)
self.assertEqual(o2.getNevaluations(), 1)
self.assertAlmostEqual(o2.getValue(), 3.14)
def test_basic_retrieval(self):
"""
Test a TQTreeFormulaObservable can be created/retrieved via TQObservable.
"""
# scalar
obs = TQObservable.getObservable("n_taus", self.tags)
self.assertTrue(obs)
# vector
obs = TQObservable.getObservable("VecBranch(tau_pt)", self.tags)
self.assertTrue(obs)
def test_multiple_retrieval_different_spaces(self):
"""
Test a TQFilterObservable can be created/retrieved via TQObservable
and retrieved again with different number of spaces.
"""
o1 = TQObservable.getObservable("Filter($(a), [$(b)] > 3.)", self.tags)
self.assertTrue(o1)
o2 = TQObservable.getObservable("Filter($(a),[$(b)]> 3.)", self.tags)
self.assertTrue(o2)
self.assertEqual(o1, o2)
def test_multiple_retrieval(self):
"""
Test a TQFilterObservable can be created/retrieved via TQObservable
and retrieved again with exactly the same expression.
"""
o1 = TQObservable.getObservable("Filter($(a), $(b) > 3.)", self.tags)
self.assertTrue(o1)
o2 = TQObservable.getObservable("Filter($(a), $(b) > 3.)", self.tags)
self.assertTrue(o2)
self.assertEqual(o1, o2)
def test_multiple_retrieval_with_bools(self):
"""
Test a TQFilterObservable can be created/retrieved via TQObservable
and retrieved again with exactly the same expression when a boolean
tag is used in the cut expression.
"""
o1 = TQObservable.getObservable("Filter($(a), $(b) > 3. && $(c))", self.tags)
self.assertTrue(o1)
o2 = TQObservable.getObservable("Filter($(a), $(b) > 3. && $(c))", self.tags)
self.assertTrue(o2)
self.assertEqual(o1, o2)
def test_multiple_retrieval_with_bools_and_different_spaces(self):
"""
Test a TQFilterObservable can be created/retrieved via TQObservable
and retrieved again with different usage of white spaces when a boolean
tag is used in the cut expression.
"""
o1 = TQObservable.getObservable("Filter($(a), $(b) > 3. && $(c))", self.tags)
self.assertTrue(o1)
o2 = TQObservable.getObservable("Filter($(a),$(b)> 3. && $(c))", self.tags)
self.assertTrue(o2)
self.assertEqual(o1, o2)
def test_observable_expr_scalar(self):
"""
Test that the observable created from an expression with a scalar
branch returns the same expression again.
"""
obs = TQObservable.getObservable("n_taus", self.tags)
self.assertEqual(obs.getExpression(), "n_taus")
def test_observable_expr_vector(self):
"""
Test that the observable created from an expression with a vector
branch returns the same expression again.
"""
obs = TQObservable.getObservable("VecBranch(tau_pt)", self.tags)
self.assertEqual(obs.getExpression(), "VecBranch(tau_pt)")
def test_observable_type_vector(self):
"""
Test that the observable created from an expression with a vector
branch is a vector observable.
"""
obs = TQObservable.getObservable("VecBranch(tau_pt)", self.tags)
self.assertIsInstance(obs, TQTreeFormulaObservable)
self.assertEqual(obs.getObservableType(), TQObservable.vector)
def test_observable_type_scalar(self):
"""
Test that the observable created from an expression with a scalar
branch is a scalar observable.
"""
obs = TQObservable.getObservable("n_taus", self.tags)
self.assertIsInstance(obs, TQTreeFormulaObservable)
self.assertEqual(obs.getObservableType(), TQObservable.scalar)
def test_cut(self):
"""
Test that the observable does not return any value, when the second
argument is false.
"""
obs = TQObservable.getObservable("Filter($(a), $(b) > 4.)", self.tags)
self.assertTrue(obs.initialize(self.sample))
self.assertEqual(obs.getNevaluations(), 0)
def test_return_value(self):
"""
Test that the first argument is returned when the second argument is
true.
"""
obs = TQObservable.getObservable("Filter($(a), $(b) > 3.)", self.tags)
self.assertTrue(obs.initialize(self.sample))
self.assertEqual(obs.getNevaluations(), 1)
self.assertEqual(obs.getValueAt(0), 2.2)
def test_return_value_vector_at(self):
"""
Test the VecAT observable works with VecBranch.
"""
obs = TQObservable.getObservable("VecAT(VecBranch(tau_pt), 1)",
self.tags)
self.assertTrue(obs.initialize(self.sample))
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertAlmostEqual(obs.getValue(), 2.72)
def test_return_value_vector_at_by_10_outside(self):
"""
Test the VecAT observable works with VecBranch, when VecAt is divided
by 10.
"""
obs = TQObservable.getObservable("[VecAT(VecBranch(tau_pt), 1)] / 10",
self.tags)
self.assertTrue(obs.initialize(self.sample))
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertAlmostEqual(obs.getValue(), 0.272)
def test_return_value_scalar_tags(self):
"""
Test that the observable created from a scalar branch using tags
returns the correct value.
"""
obs = TQObservable.getObservable("$(a)", self.tags)
self.assertTrue(obs.initialize(self.sample))
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertEqual(obs.getNevaluations(), 1)
self.assertAlmostEqual(obs.getValue(), 3.14)
def test_return_value_vector_tags(self):
"""
Test that the observable created from a vector branch using tags
returns the correct value.
"""
obs = TQObservable.getObservable("VecBranch($(b))", self.tags)
self.assertTrue(obs.initialize(self.sample))
tree = self.sample.getTreeToken().getContentAsTObject()
tree.GetEntry(0)
self.assertEqual(obs.getNevaluations(), 2)
self.assertAlmostEqual(obs.getValueAt(0), 1.42)
self.assertAlmostEqual(obs.getValueAt(1), 2.72)
def test_basic_retrieval(self):
"""
Test a TQFilterObservable can be created/retrieved via TQObservable.
"""
obs = TQObservable.getObservable("Filter($(a), $(b) > 3.)", self.tags)
self.assertTrue(obs)
def main(samples, sample_to_run, extra_args):
index = int(extra_args[0])
sample_to_run_prefix = pathToUniqStr(sample_to_run)
isparallel = (sample_to_run != "")
#
#
# Define cuts
#
#
if index == -1: cuts = getWWWAnalysisCuts()
if index == 0: cuts = getWWWAnalysisCuts()
if index == 1: cuts = getWWWAnalysisCuts(jecvar_suffix="_up")
if index == 2: cuts = getWWWAnalysisCuts(jecvar_suffix="_dn")
if index == 3:
cuts = getWWWAnalysisCuts(genmet_prefix="gen", genmet_suffix="_gen")
#
#
# Define histograms
#
#
histojob_filename = ".histo.{}.cfg".format(sample_to_run_prefix)
f = open(histojob_filename, "w")
f.write("""
TH1F('MllSS' , '' , 180 , 0. , 300.) << (MllSS : '\#it{m}_{ll} [GeV]');
#@*/*: MllSS;
TH1F('DPhill' , '' , 180 , 0. , 3.1416) << (TMath::Abs(TVector2::Phi_mpi_pi(lep_phi[0] - lep_phi[1])) : '\#Delta\#phi_{ll}');
#@*/*: DPhill;
TH1F('MllSS_wide' , '' , 180 , 0. , 2000.) << (MllSS : '\#it{m}_{ll} [GeV]');
#@*/*: MllSS_wide;
TH1F('MllZ' , '' , 180 , 60. , 120.) << (MllSS : '\#it{m}_{ll} [GeV]');
#@*/*: MllZ;
TH1F('MllZZoom' , '' , 180 , 80. , 100.) << (MllSS : '\#it{m}_{ll} [GeV]');
#@*/*: MllZZoom;
TH1F('M3l' , '' , 180 , 0. , 150.) << (M3l : '\#it{m}_{lll} [GeV]');
#@*/*: M3l;
TH1F('Pt3lGCR' , '' , 180 , 0. , 100.) << (Pt3l : '\#it{p}_{T,lll} [GeV]');
#@*/*: Pt3lGCR;
TH1F('Pt3l' , '' , 180 , 0. , 300.) << (Pt3l : '\#it{p}_{T,lll} [GeV]');
#@*/*: Pt3l;
TH1F('Ptll' , '' , 180 , 0. , 300.) << (Pt3l : '\#it{p}_{T,lll} [GeV]');
#@*/*: Ptll;
TH1F('nvtx' , '' , 60 , 0. , 60. ) << (nVert : 'Nvtx');
#@*/*: nvtx;
TH1F('Mjj' , '' , 180 , 0. , 300.) << (Mjj : '\#it{m}_{jj} [GeV]');
#@*/*: Mjj;
TH1F('MjjL' , '' , 180 , 0. , 750.) << (MjjL : '\#it{m}_{jj,central,leading} [GeV]');
#@*/*: MjjL;
TH1F('DetajjL' , '' , 180 , 0. , 5.) << (DetajjL : '\#it{m}_{jj,central,leading} [GeV]');
#@*/*: DetajjL;
TH1F('MjjVBF' , '' , 180 , 0. , 750.) << (MjjVBF : '\#it{m}_{jj,central,leading} [GeV]');
#@*/*: MjjVBF;
TH1F('DetajjVBF' , '' , 180 , 0. , 8.) << (DetajjVBF : '\#it{m}_{jj,central,leading} [GeV]');
#@*/*: DetajjVBF;
TH1F('MET' , '' , 180 , 0. , 180.) << (met_pt : 'MET [GeV]');
#@*/*: MET;
TH2F('lep0_pt_vs_eta' , '' , {0, 0.9, 1.6, 1.9, 2.4}, {20, 30, 40, 50, 60, 70, 150, 2000} ) << (lep_eta[0] : '\#eta_{lead-lep}', lep_pt[0] : '\#it{p}_{T, lead-lep} [GeV]');
#@*/*: lep0_pt_vs_eta;
TH2F('lep1_pt_vs_eta' , '' , {0, 0.9, 1.6, 1.9, 2.4}, {20, 30, 40, 50, 60, 70, 150, 2000} ) << (lep_eta[1] : '\#eta_{trail-lep}', lep_pt[1] : '\#it{p}_{T, trail-lep} [GeV]');
#@*/*: lep1_pt_vs_eta;
TH1F('lep_pt0' , '' , 180 , 0. , 250 ) << (lep_pt[0] : '\#it{p}_{T, lead-lep} [GeV]');
#@*/*: lep_pt0;
TH1F('lep_pt1' , '' , 180 , 0. , 150 ) << (lep_pt[1] : '\#it{p}_{T, trail-lep} [GeV]');
#@*/*: lep_pt1;
TH1F('lep_pt2' , '' , 180 , 0. , 150 ) << (lep_pt[2] : '\#it{p}_{T, subtrail-lep} [GeV]');
#@*/*: lep_pt1;
TH1F('lep_eta0' , '' , 180 , -2.5 , 2.5 ) << (lep_eta[0] : '\#eta_{lead-lep}');
#@*/*: lep_eta0;
TH1F('lep_eta1' , '' , 180 , -2.5 , 2.5 ) << (lep_eta[1] : '\#eta_{trail-lep}');
#@*/*: lep_eta1;
TH1F('lep_phi0' , '' , 180 , -3.1416 , 3.1416 ) << (lep_phi[0] : '\#phi_{lead-lep}');
#@*/*: lep_phi0;
TH1F('lep_phi1' , '' , 180 , -3.1416, 3.1416 ) << (lep_phi[1] : '\#phi_{trail-lep}');
#@*/*: lep_phi1;
TH1F('lep_relIso03EAv2Lep0' , '' , 180 , 0.0 , 0.2 ) << (lep_relIso03EAv2Lep[0] : 'I_{R=0.3,EA,Lep, lead-lep}');
#@*/*: lep_relIso03EAv2Lep0;
TH1F('lep_relIso03EAv2Lep1' , '' , 180 , 0.0 , 0.2 ) << (lep_relIso03EAv2Lep[1] : 'I_{R=0.3,EA,Lep, trail-lep}');
#@*/*: lep_relIso03EAv2Lep1;
TH1F('lep_relIso03EAv2Lep2' , '' , 180 , 0.0 , 0.2 ) << (lep_relIso03EAv2Lep[2] : 'I_{R=0.3,EA,Lep, trail-lep}');
#@*/*: lep_relIso03EAv2Lep2;
#TH1F('nj' , '' , 7 , 0. , 7. ) << (nj : 'N_{jet}');
#@*/*: nj;
#TH1F('nj30' , '' , 7 , 0. , 7. ) << (nj30 : 'N_{jet}');
#@*/*: nj30;
#TH1F('nb' , '' , 5 , 0. , 5. ) << (nb : 'N_{b-jet}');
#@*/*: nb;
TH1F('jets_pt0' , '' , 180 , 0. , 250 ) << (jets_p4[0].pt() : '\#it{p}_{T, lead-jet} [GeV]');
#@*/*: jets_pt0;
TH1F('jets_pt1' , '' , 180 , 0. , 150 ) << (jets_p4[1].pt() : '\#it{p}_{T, trail-jet} [GeV]');
#@*/*: jets_pt1;
TH1F('jets_eta0' , '' , 180 , -5.0 , 5.0 ) << (jets_p4[0].eta() : '\#eta_{lead-jet}');
#@*/*: jets_eta0;
TH1F('jets_eta1' , '' , 180 , -5.0 , 5.0 ) << (jets_p4[1].eta() : '\#eta_{trail-jet}');
#@*/*: jets_eta1;
TH1F('jets_phi0' , '' , 180 , -3.1416, 3.1416 ) << (jets_p4[0].phi() : '\#phi_{lead-jet}');
#@*/*: jets_phi0;
TH1F('jets_phi1' , '' , 180 , -3.1416, 3.1416 ) << (jets_p4[1].phi() : '\#phi_{trail-jet}');
#@*/*: jets_phi1;
TH1F('MTmax3L' , '' , 180 , 0. , 300.) << ([MTMax3L] : '\#it{m}_{T,max} [GeV]');
#@*/*: MTmax3L;
TH1F('MT3rd' , '' , 180 , 0. , 300.) << (MT3rd : '\#it{m}_{T,3rd} [GeV]');
#@*/*: MT3rd;
TH1F('Mlvlvjj' , '' , 180 , 0. , 1000.) << ([MTlvlvjj] : '\#it{m}_{lvlvjj} [GeV]');
#@*/*: Mlvlvjj;
TH1F('Mlvlvjj_wide' , '' , 180 , 0. , 3000.) << ([MTlvlvjj] : '\#it{m}_{lvlvjj} [GeV]');
#@*/*: Mlvlvjj_wide;
TH1F('MTlvlv' , '' , 180 , 0. , 1000.) << ([MTlvlv] : '\#it{m}_{T,lvlv} [GeV]');
#@*/*: MTlvlv;
@BTCRSSeeFull: lep_pt0, lep_pt1, MET;
@BTCRSSemFull: lep_pt0, lep_pt1, MET;
@BTCRSSmmFull: lep_pt0, lep_pt1, MET;
@BTCRSideSSeeFull: lep_pt0, lep_pt1, MET;
@BTCRSideSSemFull: lep_pt0, lep_pt1, MET;
@BTCRSideSSmmFull: lep_pt0, lep_pt1, MET;
@LMETCRSSeeFull: lep_pt0, lep_pt1, MET, Mjj;
@LMETCRSSemFull: lep_pt0, lep_pt1, MET, Mjj;
@LMETCRSSmmFull: lep_pt0, lep_pt1, MET, Mjj;
@SRSSeeFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SRSSemFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SRSSmmFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SideSSeeFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SideSSemFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SideSSmmFull/*: MllSS_wide, MTlvlv, Mjj, Mlvlvjj_wide, lep_pt0, lep_pt1, lep_pt2, DPhill;
@SR0SFOSFull/* :MllSS_wide, MTlvlv, lep_pt0, lep_pt1, lep_pt2;
@SR1SFOSFull/* :MllSS_wide, MTlvlv, lep_pt0, lep_pt1, lep_pt2;
@SR2SFOSFull/* :MllSS_wide, MTlvlv, lep_pt0, lep_pt1, lep_pt2;
""")
f.close()
#
#
# Book Analysis Jobs (Histogramming, Cutflow, Event lists, etc.)
#
#
histojob = TQHistoMakerAnalysisJob()
histojob.importJobsFromTextFiles(histojob_filename, cuts, "*",
True if not isparallel else False)
# Analysis jobs
cutflowjob = TQCutflowAnalysisJob("cutflow")
cuts.addAnalysisJob(cutflowjob, "*")
# Eventlist jobs (use this if we want to print out some event information in a text format e.g. run, lumi, evt or other variables.)
eventlistjob = TQEventlistAnalysisJob("eventlist")
eventlist_filename = ".eventlist.{}.cfg".format(sample_to_run_prefix)
f = open(eventlist_filename, "w")
f.write("""
lepton: run << run, lumi << lumi, evt << evt;
@SRSSeeFull: lepton;
@SRSSemFull: lepton;
@SRSSmmFull: lepton;
@SideSSeeFull: lepton;
@SideSSemFull: lepton;
@SideSSmmFull: lepton;
@SR0SFOSFull: lepton;
@SR1SFOSFull: lepton;
@SR2SFOSFull: lepton;
@WZCRSSeeFull: lepton;
@WZCRSSemFull: lepton;
@WZCRSSmmFull: lepton;
@WZCR1SFOSFull: lepton;
@WZCR2SFOSFull: lepton;
""")
f.close()
eventlistjob.importJobsFromTextFiles(eventlist_filename, cuts, "*",
True if not isparallel else False)
#
#
# Add custom tqobservable that can do more than just string based draw statements
#
#
from QFramework import TQObservable, TQWWWMTMax3L, TQWWWClosureEvtType, TQWWWVariables
customobservables = {}
customobservables["MTMax3L"] = TQWWWMTMax3L("")
customobservables["MTMax3L_up"] = TQWWWMTMax3L("_up")
customobservables["MTMax3L_dn"] = TQWWWMTMax3L("_dn")
customobservables["MTlvlvjj"] = TQWWWVariables("MTlvlvjj")
customobservables["MTlvlv"] = TQWWWVariables("MTlvlv")
TQObservable.addObservable(customobservables["MTMax3L"], "MTMax3L")
TQObservable.addObservable(customobservables["MTMax3L_up"], "MTMax3L_up")
TQObservable.addObservable(customobservables["MTMax3L_dn"], "MTMax3L_dn")
TQObservable.addObservable(customobservables["MTlvlvjj"], "MTlvlvjj")
TQObservable.addObservable(customobservables["MTlvlv"], "MTlvlv")
# Print cuts and numebr of booked analysis jobs for debugging purpose
if not isparallel:
cuts.printCut("trd")
#
#
# Set object "generalization" (i.e. merging histograms)
#
#
#samples.getSampleFolder("/typebkg/prompt/Other").setTagBool(".asv.generalize.counter", True)
#samples.getSampleFolder("/typebkg/prompt/Other").setTagBool(".asv.generalize.histograms", True)
#samples.getSampleFolder("/typebkg/lostlep/Other").setTagBool(".asv.generalize.counter", True)
#samples.getSampleFolder("/typebkg/lostlep/Other").setTagBool(".asv.generalize.histograms", True)
#samples.getSampleFolder("/typebkg/qflip/Other").setTagBool(".asv.generalize.counter", True)
#samples.getSampleFolder("/typebkg/qflip/Other").setTagBool(".asv.generalize.histograms", True)
#samples.getSampleFolder("/typebkg/photon/Other").setTagBool(".asv.generalize.counter", True)
#samples.getSampleFolder("/typebkg/photon/Other").setTagBool(".asv.generalize.histograms", True)
#samples.getSampleFolder("/typebkg/fakes/Other").setTagBool(".asv.generalize.counter", True)
#samples.getSampleFolder("/typebkg/fakes/Other").setTagBool(".asv.generalize.histograms", True)
#
#
# Loop over the samples
#
#
# setup a visitor to actually loop over ROOT files
vis = TQAnalysisSampleVisitor(cuts, True)
# Run the job!
if sample_to_run:
samples.visitSampleFolders(vis, "{}".format(sample_to_run))
else:
samples.visitSampleFolders(vis)
# Write the output histograms and cutflow cut values and etc.
prefix = "output"
if sample_to_run: prefix = ".output_{}".format(sample_to_run_prefix)
if index == 0: samples.writeToFile("{}_normal.root".format(prefix), True)
if index == 1: samples.writeToFile("{}_jec_up.root".format(prefix), True)
if index == 2: samples.writeToFile("{}_jec_dn.root".format(prefix), True)
if index == 3: samples.writeToFile("{}_gen_met.root".format(prefix), True)
os.system("rm {}".format(eventlist_filename))
os.system("rm {}".format(histojob_filename))
def main(index, mode, donotrun):
# Determine JEC mode
jecvar = ""
if mode == 1: jecvar = "_up"
if mode == 2: jecvar = "_dn"
#
#
# Create the master TQSampleFolder
#
#
samples = TQSampleFolder("samples")
#
#
# Connect input baby ntuple
#
#
connectNtuples(samples, samplescfgpath, nfspath, ">4", ">5")
#
#
# Define cuts
#
#
PreselCuts = [
["1", "{$(usefakeweight)?1.:evt_scale1fb*35.9}"],
["1", "{$(usefakeweight)?1.:purewgt}"],
["Flag_AllEventFilters", "1"],
["nj30>=1", "1"],
["firstgoodvertex==0", "1"],
["evt_passgoodrunlist", "1"],
["mc_HLT_SingleIsoMu17+mc_HLT_SingleIsoEl17", "1"],
]
PreselCutExpr, PreselWgtExpr = combexpr(PreselCuts)
# Complicated string construction for looes and tight ID muon
mu_loosetemp = "(TMath::Abs(lep_eta[{idx}]<2.4))*(abs(lep_dz[{idx}])<0.1)*(abs(lep_dxy[{idx}])<0.05)*(abs(lep_ip3d[{idx}])<0.015)*(abs(lep_ip3derr[{idx}]/lep_ip3d[{idx}])<4.)*(abs(lep_pterr[{idx}]/lep_trk_pt[{idx}])<0.2)*(lep_isMediumPOG[{idx}])*(lep_relIso03EAv2Lep[{idx}]<0.4)*(lep_pt[{idx}]>20.)"
mu_tighttemp = "({loose})*(lep_relIso03EAv2Lep[{idx}]<0.03)".format(
loose=mu_loosetemp, idx="{idx}")
leadmu_loose = mu_loosetemp.format(idx="0")
leadmu_tight = mu_tighttemp.format(idx="0")
trailmu_loose = mu_loosetemp.format(idx="1")
trailmu_tight = mu_tighttemp.format(idx="1")
bothmu_loose = "({})&&({})".format(leadmu_loose, trailmu_loose)
bothmu_tight = "({})&&({})".format(leadmu_tight, trailmu_tight)
# Complicated string construction for looes and tight ID muon
mu3l_loosetemp = "(TMath::Abs(lep_eta[{idx}]<2.4))*(abs(lep_dz[{idx}])<0.1)*(abs(lep_dxy[{idx}])<0.05)*(abs(lep_ip3d[{idx}])<0.015)*(abs(lep_ip3derr[{idx}]/lep_ip3d[{idx}])<4.)*(abs(lep_pterr[{idx}]/lep_trk_pt[{idx}])<0.2)*(lep_isMediumPOG[{idx}])*(lep_relIso03EAv2Lep[{idx}]<0.4)*(lep_pt[{idx}]>20.)"
mu3l_tighttemp = "({loose})*(lep_relIso03EAv2Lep[{idx}]<0.07)".format(
loose=mu3l_loosetemp, idx="{idx}")
leadmu3l_loose = mu3l_loosetemp.format(idx="0")
leadmu3l_tight = mu3l_tighttemp.format(idx="0")
trailmu3l_loose = mu3l_loosetemp.format(idx="1")
trailmu3l_tight = mu3l_tighttemp.format(idx="1")
bothmu3l_loose = "({})&&({})".format(leadmu3l_loose, trailmu3l_loose)
bothmu3l_tight = "({})&&({})".format(leadmu3l_tight, trailmu3l_tight)
# Complicated string construction for looes and tight ID electron
el_loosetemp = "(TMath::Abs(lep_eta[{idx}]<2.4))*(abs(lep_dz[{idx}])<0.1)*(abs(lep_dxy[{idx}])<0.05)*(abs(lep_ip3d[{idx}])<0.01)*(lep_tightCharge[{idx}]==2)*((abs(lep_etaSC[{idx}])<=1.479)*(lep_MVA[{idx}]>0.941)+(abs(lep_etaSC[{idx}])>1.479)*(lep_MVA[{idx}]>0.925))*(lep_isTriggerSafe_v1[{idx}])*(lep_relIso03EAv2Lep[{idx}]<0.4)*(lep_pt[{idx}]>20.)"
el_tighttemp = "({loose})*(lep_relIso03EAv2Lep[{idx}]<0.03)".format(
loose=el_loosetemp, idx="{idx}")
leadel_loose = el_loosetemp.format(idx="0")
leadel_tight = el_tighttemp.format(idx="0")
trailel_loose = el_loosetemp.format(idx="1")
trailel_tight = el_tighttemp.format(idx="1")
bothel_loose = "({})&&({})".format(leadel_loose, trailel_loose)
bothel_tight = "({})&&({})".format(leadel_tight, trailel_tight)
# Complicated string construction for looes and tight ID electron for three lepton region
el3l_loosetemp = "(TMath::Abs(lep_eta[{idx}]<2.4))*(abs(lep_dz[{idx}])<0.1)*(abs(lep_dxy[{idx}])<0.05)*(abs(lep_ip3d[{idx}])<0.015)*((abs(lep_etaSC[{idx}])<=1.479)*(lep_MVA[{idx}]>0.92)+(abs(lep_etaSC[{idx}])>1.479)*(lep_MVA[{idx}]>0.88))*(lep_isTriggerSafe_v1[{idx}])*(lep_relIso03EAv2Lep[{idx}]<0.4)*(lep_pt[{idx}]>20.)"
el3l_tighttemp = "({loose})*(lep_relIso03EAv2Lep[{idx}]<0.05)".format(
loose=el3l_loosetemp, idx="{idx}")
leadel3l_loose = el3l_loosetemp.format(idx="0")
leadel3l_tight = el3l_tighttemp.format(idx="0")
trailel3l_loose = el3l_loosetemp.format(idx="1")
trailel3l_tight = el3l_tighttemp.format(idx="1")
bothel3l_loose = "({})&&({})".format(leadel3l_loose, trailel3l_loose)
bothel3l_tight = "({})&&({})".format(leadel3l_tight, trailel3l_tight)
# Expressions to divide heavy flavor and !(heavy flavor)
leadhf = "((lep_motherIdSS[0]==-1)+(lep_motherIdSS[0]==-2))"
leadlf = "((lep_motherIdSS[0]!=-1)*(lep_motherIdSS[0]!=-2))"
trailhf = "((lep_motherIdSS[1]==-1)+(lep_motherIdSS[1]==-2))"
traillf = "((lep_motherIdSS[1]!=-1)*(lep_motherIdSS[1]!=-2))"
# MT expression (as I forgot to add a one lepton MT variable in the WWW baby.)
MTexpr = "(TMath::Sqrt(2*met" + jecvar + "_pt*lep_pt[0]*(1.0-TMath::Cos(lep_phi[0]-met" + jecvar + "_phi))))"
# One lepton kinematic selection
onelep_cuts = "(jets" + jecvar + "_p4[0].pt()>40.)"
twolep_cuts = "(lep_pdgId[0]*lep_pdgId[1]>0)*(nj30" + jecvar + ">=2)" # if removing bveto
twolepos_cuts = "(lep_pdgId[0]*lep_pdgId[1]<0)"
# Electroweak control region selection
# TwoMuHLT17/Mll_Z fSumw[1]=155.889, x=90, error=1.35664
# TwoElHLT17/Mll_Z fSumw[1]=650.599, x=90, error=18.1318
# The reason they are not integer is because the prescales are run/lumi dependent and this number is an "effective" prescale value calculated by comparing MC to data in a dilepton z-peak from this trigger
hlt_mu17_prescale = 155.889
hlt_el17_prescale = 650.599
onelepewkcr_cuts = "(jets" + jecvar + "_p4[0].pt()>40.)*(met_pt>30.)"
onelepewkcr2_cuts = "(jets" + jecvar + "_p4[0].pt()>40.)*(lep_pt[0]>30.)*(met_pt<20.)"
onelepewkcr3_cuts = "(jets" + jecvar + "_p4[0].pt()>40.)*(lep_pt[0]>50.)"
onelepmr_cuts = "(met_pt<20.)*(" + MTexpr + "<20.)*(jets" + jecvar + "_p4[0].pt()>40.)"
oneleptrig_cuts = "(abs(lep_pdgId[0])==11)*(mc_HLT_SingleIsoEl17)+(abs(lep_pdgId[0])==13)*(mc_HLT_SingleIsoMu17)"
oneleptrig_wgts = "{$(usefakeweight)?([abs(lep_pdgId[0])==11])*([mc_HLT_SingleIsoEl17])*(" + str(
hlt_el17_prescale
) + ")+([abs(lep_pdgId[0])==13])*([mc_HLT_SingleIsoMu17])*(" + str(
hlt_mu17_prescale) + "):1.}"
onelepnvtx_wgts = "{$(usefakeweight)?1.:([abs(lep_pdgId[0])==11])*([TH1Map:nvtxreweight.root:OneElTightEWKCR3NoNvtxRewgt_nvtx([nVert])])+([abs(lep_pdgId[0])==13])*([TH1Map:nvtxreweight.root:OneMuTightEWKCR3NoNvtxRewgt_nvtx([nVert])])}"
# These weights are for closure tests. The closure tests are performed for same-sign channel only.
weight_elcomb = "([abs(lep_pdgId[0])==11])*([TH2Map:qcd_fakerates.root:qcdel([abs(lep_eta[0])],[lep_pt[0]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[0]-0.03))])])+([abs(lep_pdgId[1])==11])*([TH2Map:qcd_fakerates.root:qcdel([abs(lep_eta[1])],[lep_pt[1]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[1]-0.03))])])"
weight_el = "([abs(lep_pdgId[0])==11])*([TH2Map:qcd_fakerates.root:qcdelbcToE([abs(lep_eta[0])],[lep_pt[0]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[0]-0.03))])])+([abs(lep_pdgId[1])==11])*([TH2Map:qcd_fakerates.root:qcdelbcToE([abs(lep_eta[1])],[lep_pt[1]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[1]-0.03))])])"
weight_mu = "([abs(lep_pdgId[0])==13])*([TH2Map:qcd_fakerates.root:qcdmu([abs(lep_eta[0])],[lep_pt[0]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[0]-0.03))])])+([abs(lep_pdgId[1])==13])*([TH2Map:qcd_fakerates.root:qcdmu([abs(lep_eta[1])],[lep_pt[1]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[1]-0.03))])])"
weight_elEM1D = "([abs(lep_pdgId[0])==11])*([TH1Map:qcd_fakerates.root:qcdelEM1D([lep_pt[0]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[0]-0.03))])])+([abs(lep_pdgId[1])==11])*([TH1Map:qcd_fakerates.root:qcdelEM1D([lep_pt[1]*(1.0+TMath::Max(0.0, lep_relIso03EAv2Lep[1]-0.03))])])"
# TQCut objects
tqcuts = {}
tqcuts["Presel"] = TQCut("Presel", "Presel", PreselCutExpr, PreselWgtExpr)
tqcuts["OneLep"] = TQCut(
"OneLep", "OneLep",
"(nVlep==1)*({})*({})".format(oneleptrig_cuts, onelep_cuts),
"({})*({})".format(oneleptrig_wgts, onelepnvtx_wgts))
tqcuts["OneLepNoNvtxRewgt"] = TQCut(
"OneLepNoNvtxRewgt", "OneLepNoNvtxRewgt",
"(nVlep==1)*({})*({})".format(oneleptrig_cuts, onelep_cuts),
"({})".format(oneleptrig_wgts))
tqcuts["TwoLep"] = TQCut("TwoLep", "TwoLep",
"(nVlep==2)*({})".format(twolep_cuts), "1")
tqcuts["TwoLepOS"] = TQCut("TwoLepOS", "TwoLepOS",
"(nVlep==2)*({})".format(twolepos_cuts), "1")
tqcuts["OneLepMR"] = TQCut("OneLepMR", "OneLepMR",
"(nVlep==1)*({})".format(onelepmr_cuts), "1")
tqcuts["OneLepEWKCR"] = TQCut("OneLepEWKCR", "OneLepEWKCR",
"(nVlep==1)*({})".format(onelepewkcr_cuts),
"1")
tqcuts["OneLepEWKCR2"] = TQCut("OneLepEWKCR2", "OneLepEWKCR2",
"(nVlep==1)*({})".format(onelepewkcr2_cuts),
"1")
tqcuts["OneLepEWKCR3"] = TQCut("OneLepEWKCR3", "OneLepEWKCR3",
"(nVlep==1)*({})".format(onelepewkcr3_cuts),
"1")
tqcuts["OneLepEWKCR3NoNvtxRewgt"] = TQCut(
"OneLepEWKCR3NoNvtxRewgt", "OneLepEWKCR3NoNvtxRewgt",
"(nVlep==1)*({})".format(onelepewkcr3_cuts), "1")
tqcuts["OneMu"] = TQCut("OneMu", "OneMu", "(abs(lep_pdgId[0])==13)", "1")
tqcuts["OneMuLoose"] = TQCut("OneMuLoose", "OneMuLoose", leadmu_loose, "1")
tqcuts["OneMuTight"] = TQCut("OneMuTight", "OneMuTight", leadmu_tight, "1")
tqcuts["OneMu3lLoose"] = TQCut("OneMu3lLoose", "OneMu3lLoose",
leadmu3l_loose, "1")
tqcuts["OneMu3lTight"] = TQCut("OneMu3lTight", "OneMu3lTight",
leadmu3l_tight, "1")
tqcuts["OneEl"] = TQCut("OneEl", "OneEl", "(abs(lep_pdgId[0])==11)", "1")
tqcuts["OneElLoose"] = TQCut("OneElLoose", "OneElLoose", leadel_loose, "1")
tqcuts["OneElTight"] = TQCut("OneElTight", "OneElTight", leadel_tight, "1")
tqcuts["OneEl3lLoose"] = TQCut("OneEl3lLoose", "OneEl3lLoose",
leadel3l_loose, "1")
tqcuts["OneEl3lTight"] = TQCut("OneEl3lTight", "OneEl3lTight",
leadel3l_tight, "1")
tqcuts["OneMuEWKCR"] = TQCut("OneMuEWKCR", "OneMuEWKCR",
"(abs(lep_pdgId[0])==13)", "1")
tqcuts["OneElEWKCR"] = TQCut("OneElEWKCR", "OneElEWKCR",
"(abs(lep_pdgId[0])==11)", "1")
tqcuts["OneMuTightEWKCR"] = TQCut("OneMuTightEWKCR", "OneMuTightEWKCR",
leadmu_tight, "1")
tqcuts["OneElTightEWKCR"] = TQCut("OneElTightEWKCR", "OneElTightEWKCR",
leadel_tight, "1")
tqcuts["OneMu3lTightEWKCR"] = TQCut("OneMu3lTightEWKCR",
"OneMu3lTightEWKCR", leadmu3l_tight,
"1")
tqcuts["OneEl3lTightEWKCR"] = TQCut("OneEl3lTightEWKCR",
"OneEl3lTightEWKCR", leadel3l_tight,
"1")
tqcuts["OneMuEWKCR2"] = TQCut("OneMuEWKCR2", "OneMuEWKCR2",
"(abs(lep_pdgId[0])==13)", "1")
tqcuts["OneElEWKCR2"] = TQCut("OneElEWKCR2", "OneElEWKCR2",
"(abs(lep_pdgId[0])==11)", "1")
tqcuts["OneMuTightEWKCR2"] = TQCut("OneMuTightEWKCR2", "OneMuTightEWKCR2",
leadmu_tight, "1")
tqcuts["OneElTightEWKCR2"] = TQCut("OneElTightEWKCR2", "OneElTightEWKCR2",
leadel_tight, "1")
tqcuts["OneMu3lTightEWKCR2"] = TQCut("OneMu3lTightEWKCR2",
"OneMu3lTightEWKCR2", leadmu3l_tight,
"1")
tqcuts["OneEl3lTightEWKCR2"] = TQCut("OneEl3lTightEWKCR2",
"OneEl3lTightEWKCR2", leadel3l_tight,
"1")
tqcuts["OneMuEWKCR3"] = TQCut("OneMuEWKCR3", "OneMuEWKCR3",
"(abs(lep_pdgId[0])==13)", "1")
tqcuts["OneElEWKCR3"] = TQCut("OneElEWKCR3", "OneElEWKCR3",
"(abs(lep_pdgId[0])==11)", "1")
tqcuts["OneMuTightEWKCR3"] = TQCut("OneMuTightEWKCR3", "OneMuTightEWKCR3",
leadmu_tight, "1")
tqcuts["OneElTightEWKCR3"] = TQCut("OneElTightEWKCR3", "OneElTightEWKCR3",
leadel_tight, "1")
tqcuts["OneMu3lTightEWKCR3"] = TQCut("OneMu3lTightEWKCR3",
"OneMu3lTightEWKCR3", leadmu3l_tight,
"1")
tqcuts["OneEl3lTightEWKCR3"] = TQCut("OneEl3lTightEWKCR3",
"OneEl3lTightEWKCR3", leadel3l_tight,
"1")
tqcuts["OneMuEWKCR3NoNvtxRewgt"] = TQCut("OneMuEWKCR3NoNvtxRewgt",
"OneMuEWKCR3NoNvtxRewgt",
"(abs(lep_pdgId[0])==13)", "1")
tqcuts["OneElEWKCR3NoNvtxRewgt"] = TQCut("OneElEWKCR3NoNvtxRewgt",
"OneElEWKCR3NoNvtxRewgt",
"(abs(lep_pdgId[0])==11)", "1")
tqcuts["OneMuTightEWKCR3NoNvtxRewgt"] = TQCut(
"OneMuTightEWKCR3NoNvtxRewgt", "OneMuTightEWKCR3NoNvtxRewgt",
leadmu_tight, "1")
tqcuts["OneElTightEWKCR3NoNvtxRewgt"] = TQCut(
"OneElTightEWKCR3NoNvtxRewgt", "OneElTightEWKCR3NoNvtxRewgt",
leadel_tight, "1")
tqcuts["OneMu3lTightEWKCR3NoNvtxRewgt"] = TQCut(
"OneMu3lTightEWKCR3NoNvtxRewgt", "OneMu3lTightEWKCR3NoNvtxRewgt",
leadmu3l_tight, "1")
tqcuts["OneEl3lTightEWKCR3NoNvtxRewgt"] = TQCut(
"OneEl3lTightEWKCR3NoNvtxRewgt", "OneEl3lTightEWKCR3NoNvtxRewgt",
leadel3l_tight, "1")
tqcuts["TwoMu"] = TQCut(
"TwoMu", "TwoMu",
"([ClosureEvtType]==0)*[(abs(lep_pdgId[0]*lep_pdgId[1])==143)]*[(abs(lep_pdgId[0])==11)*(lep_pass_VVV_cutbased_tight[0])+(abs(lep_pdgId[1])==11)*(lep_pass_VVV_cutbased_tight[1])]",
"1") # one any muon and one real tight electron with two total leptons
tqcuts["TwoMuLoose"] = TQCut(
"TwoMuLoose", "TwoMuLoose",
"(abs(lep_pdgId[0])==13)*({})+(abs(lep_pdgId[1])==13)*({})".format(
leadmu_loose, trailmu_loose), "1")
tqcuts["TwoMuTight"] = TQCut(
"TwoMuTight", "TwoMuTight",
"(abs(lep_pdgId[0])==13)*({})+(abs(lep_pdgId[1])==13)*({})".format(
leadmu_tight, trailmu_tight), "1")
tqcuts["TwoMuLoosePredict"] = TQCut(
"TwoMuLoosePredict", "TwoMuLoosePredict",
"(abs(lep_pdgId[0])==13)*({})+(abs(lep_pdgId[1])==13)*({})".format(
leadmu_tight, trailmu_tight), "1")
tqcuts["TwoMuTightPredict"] = TQCut(
"TwoMuTightPredict", "TwoMuTightPredict",
"(abs(lep_pdgId[0])==13)*({})*(!({}))+(abs(lep_pdgId[1])==13)*({})*(!({}))"
.format(leadmu_loose, leadmu_tight, trailmu_loose,
trailmu_tight), weight_mu)
tqcuts["TwoMuLoosePredictBVeto"] = TQCut(
"TwoMuLoosePredictBVeto", "TwoMuLoosePredictBVeto", "(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==13)*({})+(abs(lep_pdgId[1])==13)*({}))".
format(leadmu_tight, trailmu_tight), "1")
tqcuts["TwoMuTightPredictBVeto"] = TQCut(
"TwoMuTightPredictBVeto", "TwoMuTightPredictBVeto", "(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==13)*({})*(!({}))+(abs(lep_pdgId[1])==13)*({})*(!({})))"
.format(leadmu_loose, leadmu_tight, trailmu_loose, trailmu_tight),
weight_mu)
tqcuts["TwoEl"] = TQCut(
"TwoEl", "TwoEl",
"([ClosureEvtType]==1)*[(abs(lep_pdgId[0]*lep_pdgId[1])==143)]*[(abs(lep_pdgId[0])==13)*(lep_pass_VVV_cutbased_tight[0])+(abs(lep_pdgId[1])==13)*(lep_pass_VVV_cutbased_tight[1])]",
"1") # one any electron and one real tight muon with two total leptons
tqcuts["TwoElLoose"] = TQCut(
"TwoElLoose", "TwoElLoose",
"(abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({})".format(
leadel_loose, trailel_loose), "1")
tqcuts["TwoElTight"] = TQCut(
"TwoElTight", "TwoElTight",
"(abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({})".format(
leadel_tight, trailel_tight), "1")
tqcuts["TwoElLoosePredict"] = TQCut(
"TwoElLoosePredict", "TwoElLoosePredict",
"(abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({})".format(
leadel_tight, trailel_tight), "1")
tqcuts["TwoElTightPredict"] = TQCut(
"TwoElTightPredict", "TwoElTightPredict",
"(abs(lep_pdgId[0])==11)*({})*(!({}))+(abs(lep_pdgId[1])==11)*({})*(!({}))"
.format(leadel_loose, leadel_tight, trailel_loose,
trailel_tight), weight_el)
tqcuts["TwoElLoosePredictHF"] = TQCut(
"TwoElLoosePredictHF", "TwoElLoosePredictHF",
"(abs(lep_pdgId[0])==11)*({})*({})+(abs(lep_pdgId[1])==11)*({})*({})".
format(leadel_tight, leadhf, trailel_tight, trailhf), "1")
tqcuts["TwoElTightPredictHF"] = TQCut(
"TwoElTightPredictHF", "TwoElTightPredictHF",
"(abs(lep_pdgId[0])==11)*({})*(!({}))*({})+(abs(lep_pdgId[1])==11)*({})*(!({}))*({})"
.format(leadel_loose, leadel_tight, leadhf, trailel_loose,
trailel_tight, trailhf), weight_el)
tqcuts["TwoElLoosePredictEM1DLF"] = TQCut(
"TwoElLoosePredictEM1DLF", "TwoElLoosePredictEM1DLF",
"(abs(lep_pdgId[0])==11)*({})*({})+(abs(lep_pdgId[1])==11)*({})*({})".
format(leadel_tight, leadlf, trailel_tight, traillf), "1")
tqcuts["TwoElTightPredictEM1DLF"] = TQCut(
"TwoElTightPredictEM1DLF", "TwoElTightPredictEM1DLF",
"(abs(lep_pdgId[0])==11)*({})*(!({}))*({})+(abs(lep_pdgId[1])==11)*({})*(!({}))*({})"
.format(leadel_loose, leadel_tight, leadlf, trailel_loose,
trailel_tight, traillf), weight_elEM1D)
tqcuts["TwoElLoosePredictComb"] = TQCut(
"TwoElLoosePredictComb", "TwoElLoosePredictComb",
"(abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({})".format(
leadel_tight, trailel_tight), "1")
tqcuts["TwoElTightPredictComb"] = TQCut(
"TwoElTightPredictComb", "TwoElTightPredictComb",
"(abs(lep_pdgId[0])==11)*({})*(!({}))+(abs(lep_pdgId[1])==11)*({})*(!({}))"
.format(leadel_loose, leadel_tight, trailel_loose,
trailel_tight), weight_elcomb)
tqcuts["TwoElLoosePredictBVeto"] = TQCut(
"TwoElLoosePredictBVeto", "TwoElLoosePredictBVeto", "(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({}))".
format(leadel_tight, trailel_tight), "1")
tqcuts["TwoElTightPredictBVeto"] = TQCut(
"TwoElTightPredictBVeto", "TwoElTightPredictBVeto", "(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*(!({}))+(abs(lep_pdgId[1])==11)*({})*(!({})))"
.format(leadel_loose, leadel_tight, trailel_loose, trailel_tight),
weight_el)
tqcuts["TwoElLoosePredictBVetoHF"] = TQCut(
"TwoElLoosePredictBVetoHF", "TwoElLoosePredictBVetoHF",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*({})+(abs(lep_pdgId[1])==11)*({})*({}))"
.format(leadel_tight, leadhf, trailel_tight, trailhf), "1")
tqcuts["TwoElTightPredictBVetoHF"] = TQCut(
"TwoElTightPredictBVetoHF", "TwoElTightPredictBVetoHF",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*(!({}))*({})+(abs(lep_pdgId[1])==11)*({})*(!({}))*({}))"
.format(leadel_loose, leadel_tight, leadhf, trailel_loose,
trailel_tight, trailhf), weight_el)
tqcuts["TwoElLoosePredictBVetoEM1DLF"] = TQCut(
"TwoElLoosePredictBVetoEM1DLF", "TwoElLoosePredictBVetoEM1DLF",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*({})+(abs(lep_pdgId[1])==11)*({})*({}))"
.format(leadel_tight, leadlf, trailel_tight, traillf), "1")
tqcuts["TwoElTightPredictBVetoEM1DLF"] = TQCut(
"TwoElTightPredictBVetoEM1DLF", "TwoElTightPredictBVetoEM1DLF",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*(!({}))*({})+(abs(lep_pdgId[1])==11)*({})*(!({}))*({}))"
.format(leadel_loose, leadel_tight, leadlf, trailel_loose,
trailel_tight, traillf), weight_elEM1D)
tqcuts["TwoElLoosePredictBVetoComb"] = TQCut(
"TwoElLoosePredictBVetoComb", "TwoElLoosePredictBVetoComb",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})+(abs(lep_pdgId[1])==11)*({}))".
format(leadel_tight, trailel_tight), "1")
tqcuts["TwoElTightPredictBVetoComb"] = TQCut(
"TwoElTightPredictBVetoComb", "TwoElTightPredictBVetoComb",
"(nb" + jecvar +
"==0)*((abs(lep_pdgId[0])==11)*({})*(!({}))+(abs(lep_pdgId[1])==11)*({})*(!({})))"
.format(leadel_loose, leadel_tight, trailel_loose, trailel_tight),
weight_elcomb)
tqcuts["TwoMuHLT8"] = TQCut(
"TwoMuHLT8", "TwoMuHLT8",
"(mc_HLT_SingleIsoMu8)*(MllSS>60.)*(MllSS<120.)", "1")
tqcuts["TwoMuHLT17"] = TQCut(
"TwoMuHLT17", "TwoMuHLT17",
"(mc_HLT_SingleIsoMu17)*(MllSS>60.)*(MllSS<120.)", "1")
tqcuts["TwoElHLT8"] = TQCut(
"TwoElHLT8", "TwoElHLT8",
"(mc_HLT_SingleIsoEl8)*(MllSS>60.)*(MllSS<120.)", "1")
tqcuts["TwoElHLT17"] = TQCut(
"TwoElHLT17", "TwoElHLT17",
"(mc_HLT_SingleIsoEl17)*(MllSS>60.)*(MllSS<120.)", "1")
# Linking TQCut objects
tqcuts["Presel"].addCut(tqcuts["OneLep"])
tqcuts["Presel"].addCut(tqcuts["OneLepNoNvtxRewgt"])
tqcuts["Presel"].addCut(tqcuts["TwoLep"])
tqcuts["Presel"].addCut(tqcuts["TwoLepOS"])
tqcuts["OneLep"].addCut(tqcuts["OneLepMR"])
tqcuts["OneLep"].addCut(tqcuts["OneLepEWKCR"])
tqcuts["OneLep"].addCut(tqcuts["OneLepEWKCR2"])
tqcuts["OneLep"].addCut(tqcuts["OneLepEWKCR3"])
tqcuts["OneLepNoNvtxRewgt"].addCut(tqcuts["OneLepEWKCR3NoNvtxRewgt"])
tqcuts["OneLepMR"].addCut(tqcuts["OneMu"])
tqcuts["OneMu"].addCut(tqcuts["OneMuLoose"])
tqcuts["OneMuLoose"].addCut(tqcuts["OneMuTight"])
tqcuts["OneMu"].addCut(tqcuts["OneMu3lLoose"])
tqcuts["OneMu3lLoose"].addCut(tqcuts["OneMu3lTight"])
tqcuts["OneLepMR"].addCut(tqcuts["OneEl"])
tqcuts["OneEl"].addCut(tqcuts["OneElLoose"])
tqcuts["OneElLoose"].addCut(tqcuts["OneElTight"])
tqcuts["OneEl"].addCut(tqcuts["OneEl3lLoose"])
tqcuts["OneEl3lLoose"].addCut(tqcuts["OneEl3lTight"])
tqcuts["OneLepEWKCR"].addCut(tqcuts["OneMuEWKCR"])
tqcuts["OneLepEWKCR"].addCut(tqcuts["OneElEWKCR"])
tqcuts["OneMuEWKCR"].addCut(tqcuts["OneMuTightEWKCR"])
tqcuts["OneElEWKCR"].addCut(tqcuts["OneElTightEWKCR"])
tqcuts["OneMuEWKCR"].addCut(tqcuts["OneMu3lTightEWKCR"])
tqcuts["OneElEWKCR"].addCut(tqcuts["OneEl3lTightEWKCR"])
tqcuts["OneLepEWKCR2"].addCut(tqcuts["OneMuEWKCR2"])
tqcuts["OneLepEWKCR2"].addCut(tqcuts["OneElEWKCR2"])
tqcuts["OneMuEWKCR2"].addCut(tqcuts["OneMuTightEWKCR2"])
tqcuts["OneElEWKCR2"].addCut(tqcuts["OneElTightEWKCR2"])
tqcuts["OneMuEWKCR2"].addCut(tqcuts["OneMu3lTightEWKCR2"])
tqcuts["OneElEWKCR2"].addCut(tqcuts["OneEl3lTightEWKCR2"])
tqcuts["OneLepEWKCR3"].addCut(tqcuts["OneMuEWKCR3"])
tqcuts["OneLepEWKCR3"].addCut(tqcuts["OneElEWKCR3"])
tqcuts["OneMuEWKCR3"].addCut(tqcuts["OneMuTightEWKCR3"])
tqcuts["OneElEWKCR3"].addCut(tqcuts["OneElTightEWKCR3"])
tqcuts["OneMuEWKCR3"].addCut(tqcuts["OneMu3lTightEWKCR3"])
tqcuts["OneElEWKCR3"].addCut(tqcuts["OneEl3lTightEWKCR3"])
tqcuts["OneLepEWKCR3NoNvtxRewgt"].addCut(tqcuts["OneMuEWKCR3NoNvtxRewgt"])
tqcuts["OneLepEWKCR3NoNvtxRewgt"].addCut(tqcuts["OneElEWKCR3NoNvtxRewgt"])
tqcuts["OneMuEWKCR3NoNvtxRewgt"].addCut(
tqcuts["OneMuTightEWKCR3NoNvtxRewgt"])
tqcuts["OneElEWKCR3NoNvtxRewgt"].addCut(
tqcuts["OneElTightEWKCR3NoNvtxRewgt"])
tqcuts["OneMuEWKCR3NoNvtxRewgt"].addCut(
tqcuts["OneMu3lTightEWKCR3NoNvtxRewgt"])
tqcuts["OneElEWKCR3NoNvtxRewgt"].addCut(
tqcuts["OneEl3lTightEWKCR3NoNvtxRewgt"])
tqcuts["TwoLep"].addCut(tqcuts["TwoMu"])
tqcuts["TwoMu"].addCut(tqcuts["TwoMuLoosePredict"])
tqcuts["TwoMu"].addCut(tqcuts["TwoMuTightPredict"])
tqcuts["TwoMu"].addCut(tqcuts["TwoMuLoosePredictBVeto"])
tqcuts["TwoMu"].addCut(tqcuts["TwoMuTightPredictBVeto"])
tqcuts["TwoMu"].addCut(tqcuts["TwoMuLoose"])
tqcuts["TwoMuLoose"].addCut(tqcuts["TwoMuTight"])
tqcuts["TwoLep"].addCut(tqcuts["TwoEl"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredict"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredict"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictComb"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictComb"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictHF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictHF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictEM1DLF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictEM1DLF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictBVeto"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictBVeto"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictBVetoComb"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictBVetoComb"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictBVetoHF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictBVetoHF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoosePredictBVetoEM1DLF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElTightPredictBVetoEM1DLF"])
tqcuts["TwoEl"].addCut(tqcuts["TwoElLoose"])
tqcuts["TwoElLoose"].addCut(tqcuts["TwoElTight"])
tqcuts["TwoLepOS"].addCut(tqcuts["TwoMuHLT8"])
tqcuts["TwoLepOS"].addCut(tqcuts["TwoMuHLT17"])
tqcuts["TwoLepOS"].addCut(tqcuts["TwoElHLT8"])
tqcuts["TwoLepOS"].addCut(tqcuts["TwoElHLT17"])
# Grand cut
cuts = tqcuts["Presel"]
#
#
# Define histograms
#
#
# N.B. Any 2D histogram must have "_vs_" in the name. This is an important conventino for the makeplot.py script to be able to distinguish the 1D vs. 2D histogram.
filename = ".histo.mr.{}.cfg".format(index)
f = open(filename, "w")
f.write("""
TH2F('lep_pt_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{20, 30, 40, 50, 60, 70, 150, 2000}} ) << (abs(lep_eta[0]) : '|\#eta|', lep_pt[0] : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_pt_vs_eta;
TH2F('lep_ptcorr_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}} ) << (abs(lep_eta[0]) : '|\#eta|', TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.) : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_ptcorr_vs_eta;
TH2F('lep_ptcorrcoarse_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << (abs(lep_eta[0]) : '|\#eta|', TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.) : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_ptcorrcoarse_vs_eta;
TH2F('lep_ptcorrcoarse_vs_etacoarse' , '' , {{0, 1.6, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << (abs(lep_eta[0]) : '|\#eta|', TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.) : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_ptcorrcoarse_vs_etacoarse;
TH2F('el3l_ptcorrcoarse_vs_etacoarse' , '' , {{0, 1.6, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << (abs(lep_eta[0]) : '|\#eta|', TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.05)),119.) : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: el3l_ptcorrcoarse_vs_etacoarse;
TH2F('mu3l_ptcorrcoarse_vs_etacoarse' , '' , {{0, 1.6, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << (abs(lep_eta[0]) : '|\#eta|', TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.07)),119.) : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: mu3l_ptcorrcoarse_vs_etacoarse;
TH1F('lep_pt' , '' , 180 , 0. , 250 ) << (lep_pt[0] : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_pt;
TH1F('lep_pt' , '' , 180 , 0. , 250 ) << (lep_pt[0] : '\#it{{p}}_{{T}} [GeV]');
@OneLep/*: lep_pt;
TH1F('lep_pdgId' , '' , 40 , -20. , 20 ) << (lep_pdgId[0] : 'Lepton PDG ID');
@OneLep/*: lep_pdgId;
TH1F('lep_ptcorr' , '' , 180 , 0. , 250 ) << (lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)) : '\#it{{p}}_{{T, cone-corr}} [GeV]');
@OneLep/*: lep_ptcorr;
TH1F('lep_ptcorrvarbin' , '' , {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}}) << (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.) : '\#it{{p}}_{{T, cone-corr}} [GeV]');
@OneLep/*: lep_ptcorrvarbin;
TH1F('lep_ptcorrvarbincoarse' , '' , {{0., 10., 20., 25., 30., 40., 120.}}) << (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.) : '\#it{{p}}_{{T, cone-corr}} [GeV]');
@OneLep/*: lep_ptcorrvarbincoarse;
TH1F('el3l_ptcorrvarbincoarse' , '' , {{0., 10., 20., 25., 30., 40., 120.}}) << (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.05)),119.) : '\#it{{p}}_{{T, cone-corr}} [GeV]');
@OneLep/*: el3l_ptcorrvarbincoarse;
TH1F('mu3l_ptcorrvarbincoarse' , '' , {{0., 10., 20., 25., 30., 40., 120.}}) << (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.07)),119.) : '\#it{{p}}_{{T, cone-corr}} [GeV]');
@OneLep/*: mu3l_ptcorrvarbincoarse;
TH1F('lep_yield' , '' , 1, 0, 1) << (0 : 'yield');
@OneLep/*: lep_yield;
TH1F('lep_eta' , '' , 180 , -2.5 , 2.5 ) << (lep_eta[0] : '\#eta');
@OneLep/*: lep_eta;
TH1F('lep_etavarbin' , '' , {{-2.5, -2.1, -1.6, -1.0, 0.0, 1.0, 1.6, 2.1, 2.5}} ) << (lep_eta[0] : '\#eta');
@OneLep/*: lep_etavarbin;
TH1F('lep_relIso03EAv2Lep' , '' , 180 , 0.0 , 0.6 ) << (lep_relIso03EAv2Lep[0] : 'I_{{R=0.3,EA,Lep}}');
@OneLep/*: lep_relIso03EAv2Lep;
TH1F('mu_ptcorrvarbin' , '' , {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}}) << ((TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==13)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoMu/*: mu_ptcorrvarbin;
TH1F('mu_ptcorrvarbincoarse' , '' , {{0., 10., 20., 25., 30., 40., 120.}}) << ((TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==13)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoMu/*: mu_ptcorrvarbincoarse;
TH1F('mu_yield' , '' , 1, 0, 1) << (0 : 'yield');
@TwoMu/*: mu_yield;
TH2F('mu_ptcorr_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==13)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==13) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==13)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoMu/*: mu_ptcorr_vs_eta;
TH2F('mu_ptcorrcoarse_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 10., 20., 25., 30., 40., 60., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==13)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==13) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==13)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoMu/*: mu_ptcorrcoarse_vs_eta;
TH2F('mu_ptcorrcoarse_vs_etacoarse' , '' , {{0, 1.6, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==13)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==13) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==13)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoMu/*: mu_ptcorrcoarse_vs_etacoarse;
TH1F('mu_pt' , '' , 180 , 0., 250) << ((lep_pt[0])*(abs(lep_pdgId[0])==13)+(lep_pt[1])*(abs(lep_pdgId[1])==13) : '\#it{{p}}_{{T, \#mu}} [GeV]');
@TwoMu/*: mu_pt;
TH1F('mu_eta' , '' , 180 , -2.5, 2.5) << ((lep_eta[0])*(abs(lep_pdgId[0])==13)+(lep_eta[1])*(abs(lep_pdgId[1])==13) : '\#eta_{{\#mu}}');
@TwoMu/*: mu_eta;
TH1F('mu_etavarbin' , '' , {{-2.5, -2.1, -1.6, -1.0, 0.0, 1.0, 1.6, 2.1, 2.5}} ) << (lep_eta[0] : '\#eta');
@TwoMu/*: mu_etavarbin;
TH1F('mu_relIso03EAv2Lep' , '' , 180 , 0., 0.6) << ((lep_relIso03EAv2Lep[0])*(abs(lep_pdgId[0])==13)+(lep_relIso03EAv2Lep[1])*(abs(lep_pdgId[1])==13) : 'I_{{R=0.3,EA,Lep,\#mu}}');
@TwoMu/*: mu_relIso03EAv2Lep;
TH2F('el_ptcorr_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==11)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==11) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==11)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoEl/*: el_ptcorr_vs_eta;
TH2F('el_ptcorrcoarse_vs_eta' , '' , {{0, 0.9, 1.6, 1.9, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==11)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==11) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==11)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoEl/*: el_ptcorrcoarse_vs_eta;
TH2F('el_ptcorrcoarse_vs_etacoarse' , '' , {{0, 1.6, 2.4}}, {{0., 10., 20., 25., 30., 40., 120.}} ) << ((abs(lep_eta[0]))*(abs(lep_pdgId[0])==11)+(abs(lep_eta[1]))*(abs(lep_pdgId[1])==11) : '|\#eta|', (TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==11)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, cone-corr, mu}} [GeV]');
@TwoEl/*: el_ptcorrcoarse_vs_etacoarse;
TH1F('el_ptcorrvarbin' , '' , {{0., 5., 10., 15., 20., 25., 30., 35., 40., 45., 60., 80., 120.}}) << ((TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==11)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, cone-corr, el}} [GeV]');
@TwoEl/*: el_ptcorrvarbin;
TH1F('el_ptcorrvarbincoarse' , '' , {{0., 10., 20., 25., 30., 40., 120.}}) << ((TMath::Min(lep_pt[0]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[0]-0.03)),119.))*(abs(lep_pdgId[0])==11)+(TMath::Min(lep_pt[1]*(1.+TMath::Max(0.,lep_relIso03EAv2Lep[1]-0.03)),119.))*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, cone-corr, el}} [GeV]');
@TwoEl/*: el_ptcorrvarbincoarse;
TH1F('el_yield' , '' , 1, 0, 1) << (0 : 'yield');
@TwoEl/*: el_yield;
TH1F('el_pt' , '' , 180 , 0., 250) << ((lep_pt[0])*(abs(lep_pdgId[0])==11)+(lep_pt[1])*(abs(lep_pdgId[1])==11) : '\#it{{p}}_{{T, el}} [GeV]');
@TwoEl/*: el_pt;
TH1F('el_eta' , '' , 180 , -2.5, 2.5) << ((lep_eta[0])*(abs(lep_pdgId[0])==11)+(lep_eta[1])*(abs(lep_pdgId[1])==11) : '\#eta_{{el}}');
@TwoEl/*: el_eta;
TH1F('el_etavarbin' , '' , {{-2.5, -2.1, -1.6, -1.0, 0.0, 1.0, 1.6, 2.1, 2.5}} ) << (lep_eta[0] : '\#eta');
@TwoEl/*: el_etavarbin;
TH1F('el_relIso03EAv2Lep' , '' , 180 , 0., 0.6) << ((lep_relIso03EAv2Lep[0])*(abs(lep_pdgId[0])==11)+(lep_relIso03EAv2Lep[1])*(abs(lep_pdgId[1])==11) : 'I_{{R=0.3,EA,Lep,el}}');
@TwoEl/*: el_relIso03EAv2Lep;
TH1F('Mjj_el' , '' , 180 , 0., 180. ) << ({Mjj} : '\#it{{m}}_{{jj}} [GeV]');
@TwoEl/*: Mjj_el;
TH1F('Mjj_mu' , '' , 180 , 0., 180. ) << ({Mjj} : '\#it{{m}}_{{jj}} [GeV]');
@TwoMu/*: Mjj_mu;
TH1F('Mll_el' , '' , 180 , 0., 180. ) << (MllSS : '\#it{{m}}_{{ll}} [GeV]');
@TwoEl/*: Mll_el;
TH1F('Mll_mu' , '' , 180 , 0., 180. ) << (MllSS : '\#it{{m}}_{{ll}} [GeV]');
@TwoMu/*: Mll_mu;
TH1F('DPhill_el' , '' , 180 , 0., 3.1416 ) << (TMath::Abs(TVector2::Phi_mpi_pi(lep_phi[0]-lep_phi[1])) : '\#it{{m}}_{{ll}} [GeV]');
@TwoEl/*: DPhill_el;
TH1F('DPhill_mu' , '' , 180 , 0., 3.1416 ) << (TMath::Abs(TVector2::Phi_mpi_pi(lep_phi[0]-lep_phi[1])) : '\#it{{m}}_{{ll}} [GeV]');
@TwoMu/*: DPhill_mu;
TH1F('MET_el' , '' , 180 , 0., 180. ) << ({MET} : 'MET [GeV]');
@TwoEl/*: MET_el;
TH1F('MET_mu' , '' , 180 , 0., 180. ) << ({MET} : 'MET [GeV]');
@TwoMu/*: MET_mu;
TH1F('MTmax_el' , '' , 180 , 0., 180. ) << ({MTmax} : '\#it{{m}}_{{T,max}} [GeV]');
@TwoEl/*: MTmax_el;
TH1F('MTmax_mu' , '' , 180 , 0., 180. ) << ({MTmax} : '\#it{{m}}_{{T,max}} [GeV]');
@TwoMu/*: MTmax_mu;
TH1F('nb_el' , '' , 5, 0., 5.) << ({nb} : 'N_{{b-jets}}');
@TwoEl/*: nb_el;
TH1F('nb_mu' , '' , 5, 0., 5.) << ({nb} : 'N_{{b-jets}}');
@TwoMu/*: nb_mu;
TH1F('nj30_el' , '' , 5, 0., 5.) << ({nj30} : 'N_{{jets,30,cent}}');
@TwoEl/*: nj30_el;
TH1F('nj30_mu' , '' , 5, 0., 5.) << ({nj30} : 'N_{{jets,30,cent}}');
@TwoMu/*: nj30_mu;
TH1F('nj_el' , '' , 5, 0., 5.) << ({nj} : 'N_{{jets,all}}');
@TwoEl/*: nj_el;
TH1F('nj_mu' , '' , 5, 0., 5.) << ({nj} : 'N_{{jets,all}}');
@TwoMu/*: nj_mu;
TH1F('Mll_Z' , '' , 180 , 60., 120. ) << (MllSS : '\#it{{m}}_{{ll}} [GeV]');
@TwoLepOS/*: Mll_Z;
TH1F('MTOneLep' , '' , 180 , 0., 180. ) << ({MT} : '\#it{{m}}_{{T}} [GeV]');
@*/*: MTOneLep;
TH1F('MTOneLepFixed' , '' , 20 , 0., 200. ) << ({MT} : '\#it{{m}}_{{T}} [GeV]');
@*/*: MTOneLepFixed;
TH1F('nvtx' , '' , 60 , 0., 60. ) << (nVert : 'N_{{vtx}}');
@*/*: nvtx;
""".format(Mjj="Mjj" + jecvar,
MET="met" + jecvar + "_pt",
nb="nb" + jecvar,
nj30="nj30" + jecvar,
nj="nj" + jecvar,
MT=MTexpr,
MTmax="MTmax" + jecvar))
f.close()
#
#
# Book Analysis Jobs (Histogramming, Cutflow, Event lists)
#
#
histojob = TQHistoMakerAnalysisJob()
histojob.importJobsFromTextFiles(filename, cuts, "*",
True if index < 0 else False)
# Analysis jobs
cutflowjob = TQCutflowAnalysisJob("cutflow")
cuts.addAnalysisJob(cutflowjob, "*")
# Eventlist jobs (use this if we want to print out some event information in a text format e.g. run, lumi, evt or other variables.)
#eventlistjob = TQEventlistAnalysisJob("eventlist")
#eventlistjob.importJobsFromTextFiles("eventlist.cfg", cuts, "*", True)
# Print cuts and numebr of booked analysis jobs for debugging purpose
if index < 0:
samples.printContents("t[*status]dr")
cuts.printCut("trd")
return
#
#
# Add custom tqobservable that can do more than just string based draw statements
#
#
from QFramework import TQWWWMTOneLep, TQWWWClosureEvtType
customobservables = {}
customobservables["MTOneLep"] = TQWWWMTOneLep("MTOneLep")
customobservables["ClosureEvtType"] = TQWWWClosureEvtType("ClosureEvtType")
TQObservable.addObservable(customobservables["MTOneLep"], "MTOneLep")
TQObservable.addObservable(customobservables["ClosureEvtType"],
"ClosureEvtType")
#
#
# Loop over the samples
#
#
# setup a visitor to actually loop over ROOT files
vis = TQAnalysisSampleVisitor(cuts, True)
#vis.setMaxEvents(30000) # to debug by restricting the looping to 30k max events
if index >= 0:
# Get all sample lists
sample_names, sample_full_names = getSampleLists(samples)
# Select the job based on the index
sample_name = sample_names[index]
sample_full_name = sample_full_names[sample_name]
# Run the job!
samples.visitSampleFolders(vis, "/*/{}".format(sample_full_name))
# Write the output histograms and cutflow cut values and etc.
samples.writeToFile(".output_{}.root".format(sample_name), True)
else:
# Run the job!
samples.visitSampleFolders(vis)
# Write the output histograms and cutflow cut values and etc.
samples.writeToFile("output.root", True)