SignificanceScan.py

import ROOT

def SignificanceScan(var="evalDNN_HH"):
    sigFile = "/eos/user/r/rasharma/post_doc_ihep/double-higgs/ntuples/January_2021_Production/DNN_Evaluate_HHWWyyDNN_NewModel6_E700_LR10em4_B150_VarMixV1MaxBRmvCorr_Trial1_BalanceYields/GluGluToHHTo2G4Q_node_cHHH1_2017.root"
    # bkgFiles = ["/eos/user/r/rasharma/post_doc_ihep/double-higgs/ntuples/January_2021_Production/DNN_Evaluate_HHWWyyDNN_NewModel6_E700_LR10em4_B150_VarMixV1MaxBRmvCorr_Trial1_BalanceYields/Data_2017.root"]
    bkgFiles = ["/eos/user/r/rasharma/post_doc_ihep/double-higgs/ntuples/January_2021_Production/DNN_Evaluate_HHWWyyDNN_NewModel6_E700_LR10em4_B150_VarMixV1MaxBRmvCorr_Trial1_BalanceYields/Data_2017.root", "/eos/user/r/rasharma/post_doc_ihep/double-higgs/ntuples/January_2021_Production/DNN_Evaluate_HHWWyyDNN_NewModel6_E700_LR10em4_B150_VarMixV1MaxBRmvCorr_Trial1_BalanceYields/Data_2018.root"]

    fileCount = 0

    # Open the input ROOT file
    f = ROOT.TFile.Open(sigFile)

    # Get the tree from the file
    t = f.Get("GluGluToHHTo2G4Q_node_cHHH1_13TeV_HHWWggTag_1")

    fBkg = ROOT.TFile.Open(bkgFiles[fileCount])
    fBkg2 = ROOT.TFile.Open(bkgFiles[fileCount+1])
    tBkg = fBkg.Get("Data_13TeV_HHWWggTag_1")
    tBkg2 = fBkg2.Get("Data_13TeV_HHWWggTag_1")

    # Create a histogram to store the values of the branch
    h = ROOT.TH1D("h", "evalDNN_HH", 25, 0, 1)
    hBkg = ROOT.TH1D("hBkg", "evalDNN_HH", 25, 0, 1)

    # Fill the histogram with the values of the branch
    t.Draw("%s>>h" % var, "weight")
    tBkg.Draw("%s>>+hBkg" % var, "(1)")
    tBkg2.Draw("%s>>+hBkg" % var, "(1)")

    # hBkg.Print()

    # for file in bkgFiles:
    #     fBkgLoop = ROOT.TFile.Open(file)
    #     tBkgLoop = fBkgLoop.Get("Data_13TeV_HHWWggTag_1")
    #     tBkgLoop.Draw("%s>>hBkg" % var, "(1)","")
    #     print(file,tBkgLoop.GetEntries())
    #     hBkg.Print()


    h.Print()
    hBkg.Print()

    g = ROOT.TGraph()
    for i in range(1, h.GetNbinsX() + 1):
        S = h.GetBinContent(i)
        B = hBkg.GetBinContent(i)
        X = h.GetBinCenter(i)
        Z = 0.0
        if S + B != 0:
            Z = S / ROOT.TMath.Sqrt(S + B)
        g.SetPoint(i - 1, X, Z)

    # Draw the histogram
    c = ROOT.TCanvas("c", "Significance Scan", 1200, 600)
    g.SetTitle("Significance Scan")
    g.GetXaxis().SetTitle(var)
    g.GetYaxis().SetTitle("Significance (S / #sqrt{S+B})")
    g.SetLineColor(2)
    g.SetLineWidth(-802)
    g.SetMarkerColor(4)
    g.SetMarkerStyle(21)
    g.Draw("APL")
    c.SaveAs("XYS.pdf")


SignificanceScan("evalDNN_HH")