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Updating FCC-ee mH recoil mumu example to work with edm4hep v1 format (…
…#400) * updating mH recoil mumu example to work with edm4hep v1, adding also histmaker and plots scripts as used in FCC SW tutorial * fix test file needed by FCCAnalysis_analysis_example_run_analysis * adapt build&test to work with edm4hep v1 format with temporary changes/ommissions to be able to develop further on this branch * fix comments in test * cleanup/changes from review of PR#400 * add missing end quote --------- Co-authored-by: Birgit Stapf <[email protected]>
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| Original file line number | Diff line number | Diff line change |
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| # list of processes (mandatory) | ||
| processList = { | ||
| #'p8_ee_ZZ_ecm240':{'fraction':1}, | ||
| #'p8_ee_WW_ecm240':{'fraction':1}, | ||
| #'wzp6_ee_mumuH_ecm240':{'fraction':1}, | ||
| # 'p8_ee_WW_mumu_ecm240': {'fraction':1, 'crossSection': 0.25792}, | ||
| # 'p8_ee_ZZ_mumubb_ecm240': {'fraction':1, 'crossSection': 2 * 1.35899 * 0.034 * 0.152}, | ||
| # 'p8_ee_ZH_Zmumu_ecm240': {'fraction':1, 'crossSection': 0.201868 * 0.034}, | ||
| 'p8_ee_ZZ_ecm240': {'fraction':1, 'crossSection': 0.25792}, | ||
| 'p8_ee_WW_ecm240': {'fraction':1, 'crossSection': 2 * 1.35899 * 0.034 * 0.152}, | ||
| 'p8_ee_ZH_ecm240': {'fraction':1, 'crossSection': 0.201868 * 0.034}, | ||
| } | ||
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| # Production tag when running over EDM4Hep centrally produced events, this points to the yaml files for getting sample statistics (mandatory) | ||
| #prodTag = "FCCee/winter2023/IDEA/" | ||
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| # Link to the dictonary that contains all the cross section informations etc... (mandatory) | ||
| procDict = "FCCee_procDict_winter2023_IDEA.json" | ||
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| # additional/custom C++ functions, defined in header files (optional) | ||
| includePaths = ["functions.h"] | ||
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| # Define the input dir (optional) | ||
| #inputDir = "outputs/FCCee/higgs/mH-recoil/mumu/stage1" | ||
| inputDir = "/eos/experiment/fcc/hh/tutorials/edm4hep_tutorial_data/" | ||
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| #Optional: output directory, default is local running directory | ||
| outputDir = "./histmaker_outputs/" | ||
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| # optional: ncpus, default is 4, -1 uses all cores available | ||
| nCPUS = -1 | ||
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| # scale the histograms with the cross-section and integrated luminosity | ||
| doScale = True | ||
| intLumi = 5000000 # 5 /ab | ||
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| # define some binning for various histograms | ||
| bins_p_mu = (2000, 0, 200) # 100 MeV bins | ||
| bins_m_ll = (2000, 0, 200) # 100 MeV bins | ||
| bins_p_ll = (2000, 0, 200) # 100 MeV bins | ||
| bins_recoil = (200000, 0, 200) # 1 MeV bins | ||
| bins_cosThetaMiss = (10000, 0, 1) | ||
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| bins_theta = (500, -5, 5) | ||
| bins_eta = (600, -3, 3) | ||
| bins_phi = (500, -5, 5) | ||
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| bins_count = (50, 0, 50) | ||
| bins_charge = (10, -5, 5) | ||
| bins_iso = (500, 0, 5) | ||
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| # build_graph function that contains the analysis logic, cuts and histograms (mandatory) | ||
| def build_graph(df, dataset): | ||
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| results = [] | ||
| df = df.Define("weight", "1.0") | ||
| weightsum = df.Sum("weight") | ||
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| # define some aliases to be used later on | ||
| df = df.Alias("Particle0", "_Particle_daughters.index") | ||
| df = df.Alias("Particle1", "_Particle_parents.index") | ||
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| df = df.Alias("MCRecoAssociations0", "_MCRecoAssociations_from.index") | ||
| df = df.Alias("MCRecoAssociations1", "_MCRecoAssociations_to.index") | ||
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| df = df.Alias("Muon0", "Muon_objIdx.index") | ||
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| # get all the leptons from the collection | ||
| df = df.Define("muons_all", "FCCAnalyses::ReconstructedParticle::get(Muon0, ReconstructedParticles)") | ||
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| # select leptons with momentum > 20 GeV | ||
| df = df.Define("muons", "FCCAnalyses::ReconstructedParticle::sel_p(20)(muons_all)") | ||
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| df = df.Define("muons_p", "FCCAnalyses::ReconstructedParticle::get_p(muons)") | ||
| df = df.Define("muons_theta", "FCCAnalyses::ReconstructedParticle::get_theta(muons)") | ||
| df = df.Define("muons_phi", "FCCAnalyses::ReconstructedParticle::get_phi(muons)") | ||
| df = df.Define("muons_q", "FCCAnalyses::ReconstructedParticle::get_charge(muons)") | ||
| df = df.Define("muons_no", "FCCAnalyses::ReconstructedParticle::get_n(muons)") | ||
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| # compute the muon isolation and store muons with an isolation cut of 0.25 in a separate column muons_sel_iso | ||
| df = df.Define("muons_iso", "FCCAnalyses::ZHfunctions::coneIsolation(0.01, 0.5)(muons, ReconstructedParticles)") | ||
| df = df.Define("muons_sel_iso", "FCCAnalyses::ZHfunctions::sel_iso(0.25)(muons, muons_iso)") | ||
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| # baseline histograms, before any selection cuts (store with _cut0) | ||
| results.append(df.Histo1D(("muons_p_cut0", "", *bins_p_mu), "muons_p")) | ||
| results.append(df.Histo1D(("muons_theta_cut0", "", *bins_theta), "muons_theta")) | ||
| results.append(df.Histo1D(("muons_phi_cut0", "", *bins_phi), "muons_phi")) | ||
| results.append(df.Histo1D(("muons_q_cut0", "", *bins_charge), "muons_q")) | ||
| results.append(df.Histo1D(("muons_no_cut0", "", *bins_count), "muons_no")) | ||
| results.append(df.Histo1D(("muons_iso_cut0", "", *bins_iso), "muons_iso")) | ||
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| ######### | ||
| ### CUT 0: all events | ||
| ######### | ||
| df = df.Define("cut0", "0") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut0")) | ||
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| ######### | ||
| ### CUT 1: at least 1 muon with at least one isolated one | ||
| ######### | ||
| df = df.Filter("muons_no >= 1 && muons_sel_iso.size() > 0") | ||
| df = df.Define("cut1", "1") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut1")) | ||
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| ######### | ||
| ### CUT 2 :at least 2 opposite-sign (OS) leptons | ||
| ######### | ||
| df = df.Filter("muons_no >= 2 && abs(Sum(muons_q)) < muons_q.size()") | ||
| df = df.Define("cut2", "2") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut2")) | ||
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| # now we build the Z resonance based on the available leptons. | ||
| # the function resonanceBuilder_mass_recoil returns the best lepton pair compatible with the Z mass (91.2 GeV) and recoil at 125 GeV | ||
| # the argument 0.4 gives a weight to the Z mass and the recoil mass in the chi2 minimization | ||
| # technically, it returns a ReconstructedParticleData object with index 0 the di-lepton system, index and 2 the leptons of the pair | ||
| df = df.Define("zbuilder_result", "FCCAnalyses::ZHfunctions::resonanceBuilder_mass_recoil(91.2, 125, 0.4, 240, false)(muons, MCRecoAssociations0, MCRecoAssociations1, ReconstructedParticles, Particle, Particle0, Particle1)") | ||
| df = df.Define("zmumu", "Vec_rp{zbuilder_result[0]}") # the Z | ||
| df = df.Define("zmumu_muons", "Vec_rp{zbuilder_result[1],zbuilder_result[2]}") # the leptons | ||
| df = df.Define("zmumu_m", "FCCAnalyses::ReconstructedParticle::get_mass(zmumu)[0]") # Z mass | ||
| df = df.Define("zmumu_p", "FCCAnalyses::ReconstructedParticle::get_p(zmumu)[0]") # momentum of the Z | ||
| df = df.Define("zmumu_recoil", "FCCAnalyses::ReconstructedParticle::recoilBuilder(240)(zmumu)") # compute the recoil based on the reconstructed Z | ||
| df = df.Define("zmumu_recoil_m", "FCCAnalyses::ReconstructedParticle::get_mass(zmumu_recoil)[0]") # recoil mass | ||
| df = df.Define("zmumu_muons_p", "FCCAnalyses::ReconstructedParticle::get_p(zmumu_muons)") # get the momentum of the 2 muons from the Z resonance | ||
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| ######### | ||
| ### CUT 3: Z mass window | ||
| ######### | ||
| df = df.Filter("zmumu_m > 86 && zmumu_m < 96") | ||
| df = df.Define("cut3", "3") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut3")) | ||
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| ######### | ||
| ### CUT 4: Z momentum | ||
| ######### | ||
| df = df.Filter("zmumu_p > 20 && zmumu_p < 70") | ||
| df = df.Define("cut4", "4") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut4")) | ||
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| ######### | ||
| ### CUT 5: cosThetaMiss | ||
| ######### | ||
| df = df.Define("missingEnergy", "FCCAnalyses::ZHfunctions::missingEnergy(240., ReconstructedParticles)") | ||
| #df = df.Define("cosTheta_miss", "FCCAnalyses::get_cosTheta_miss(missingEnergy)") | ||
| df = df.Define("cosTheta_miss", "FCCAnalyses::ZHfunctions::get_cosTheta_miss(MissingET)") | ||
| results.append(df.Histo1D(("cosThetaMiss_cut4", "", *bins_cosThetaMiss), "cosTheta_miss")) # plot it before the cut | ||
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| df = df.Filter("cosTheta_miss < 0.98") | ||
| df = df.Define("cut5", "5") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut5")) | ||
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| ######### | ||
| ### CUT 6: recoil mass window | ||
| ######### | ||
| df = df.Filter("zmumu_recoil_m < 140 && zmumu_recoil_m > 120") | ||
| df = df.Define("cut6", "6") | ||
| results.append(df.Histo1D(("cutFlow", "", *bins_count), "cut6")) | ||
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| ######################## | ||
| # Final histograms | ||
| ######################## | ||
| results.append(df.Histo1D(("zmumu_m", "", *bins_m_ll), "zmumu_m")) | ||
| results.append(df.Histo1D(("zmumu_recoil_m", "", *bins_recoil), "zmumu_recoil_m")) | ||
| results.append(df.Histo1D(("zmumu_p", "", *bins_p_ll), "zmumu_p")) | ||
| results.append(df.Histo1D(("zmumu_muons_p", "", *bins_p_mu), "zmumu_muons_p")) | ||
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| return results, weightsum |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,107 @@ | ||
| import ROOT | ||
|
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| # global parameters | ||
| intLumi = 1. | ||
| intLumiLabel = "L = 5 ab^{-1}" | ||
| ana_tex = 'e^{+}e^{-} #rightarrow ZH #rightarrow #mu^{+}#mu^{-} + X' | ||
| delphesVersion = '3.4.2' | ||
| energy = 240.0 | ||
| collider = 'FCC-ee' | ||
| formats = ['png','pdf'] | ||
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| outdir = './histmaker_outputs/' | ||
| inputDir = './histmaker_outputs/' | ||
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| plotStatUnc = True | ||
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| colors = {} | ||
| colors['ZH'] = ROOT.kRed | ||
| colors['WW'] = ROOT.kBlue+1 | ||
| colors['ZZ'] = ROOT.kGreen+2 | ||
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| #procs = {} | ||
| #procs['signal'] = {'ZH':['wzp6_ee_mumuH_ecm240']} | ||
| #procs['backgrounds'] = {'WW':['p8_ee_WW_ecm240'], 'ZZ':['p8_ee_ZZ_ecm240']} | ||
| procs = {} | ||
| procs['signal'] = {'ZH':['p8_ee_ZH_ecm240']} | ||
| # procs['signal'] = {'ZH':['p8_ee_ZH_Zmumu_ecm240']} | ||
| #procs['backgrounds'] = {'WW':['p8_ee_WW_mumu_ecm240'], 'ZZ':['p8_ee_ZZ_mumubb_ecm240']} | ||
| procs['backgrounds'] = {'ZZ':['p8_ee_ZZ_ecm240']} | ||
| # procs['backgrounds'] = {'ZZ':['p8_ee_ZZ_mumubb_ecm240']} | ||
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| legend = {} | ||
| legend['ZH'] = 'ZH' | ||
| legend['WW'] = 'WW' | ||
| legend['ZZ'] = 'ZZ' | ||
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| hists = {} | ||
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| hists["zmumu_recoil_m"] = { | ||
| "output": "zmumu_recoil_m", | ||
| "logy": False, | ||
| "stack": True, | ||
| "rebin": 100, | ||
| "xmin": 120, | ||
| "xmax": 140, | ||
| "ymin": 0, | ||
| "ymax": 2500, | ||
| "xtitle": "Recoil (GeV)", | ||
| "ytitle": "Events / 100 MeV", | ||
| } | ||
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| hists["zmumu_p"] = { | ||
| "output": "zmumu_p", | ||
| "logy": False, | ||
| "stack": True, | ||
| "rebin": 2, | ||
| "xmin": 0, | ||
| "xmax": 80, | ||
| "ymin": 0, | ||
| "ymax": 2000, | ||
| "xtitle": "p(#mu^{#plus}#mu^{#minus}) (GeV)", | ||
| "ytitle": "Events ", | ||
| } | ||
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| hists["zmumu_m"] = { | ||
| "output": "zmumu_m", | ||
| "logy": False, | ||
| "stack": True, | ||
| "rebin": 2, | ||
| "xmin": 86, | ||
| "xmax": 96, | ||
| "ymin": 0, | ||
| "ymax": 3000, | ||
| "xtitle": "m(#mu^{#plus}#mu^{#minus}) (GeV)", | ||
| "ytitle": "Events ", | ||
| } | ||
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| hists["cosThetaMiss_cut4"] = { | ||
| "output": "cosThetaMiss_cut4", | ||
| "logy": True, | ||
| "stack": True, | ||
| "rebin": 10, | ||
| "xmin": 0, | ||
| "xmax": 1, | ||
| "ymin": 10, | ||
| "ymax": 100000, | ||
| "xtitle": "cos(#theta_{miss})", | ||
| "ytitle": "Events ", | ||
| "extralab": "Before cos(#theta_{miss}) cut", | ||
| } | ||
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| # hists["cutFlow"] = { | ||
| # "output": "cutFlow", | ||
| # "logy": True, | ||
| # "stack": True, | ||
| # "xmin": 0, | ||
| # "xmax": 6, | ||
| # "ymin": 1e4, | ||
| # "ymax": 1e11, | ||
| # "xtitle": ["All events", "#geq 1 #mu^{#pm} + ISO", "#geq 2 #mu^{#pm} + OS", "86 < m_{#mu^{+}#mu^{#minus}} < 96", "20 < p_{#mu^{+}#mu^{#minus}} < 70", "|cos#theta_{miss}| < 0.98", "120 < m_{rec} < 140"], | ||
| # "ytitle": "Events ", | ||
| # "scaleSig": 10 | ||
| # } |