コード例 #1
0
def fitNBkg(ibdt, fullbkg):

    slope = RooRealVar("slope", "slope", 0.5, -10, 10)
    bkg_exp = RooExponential("bkg_exp", "exponential", slope, theBMass)

    cut = cut_base + '&& bdt_prob > %s' % (ibdt)

    theBMass.setRange('sigRangeMC', B0Mass_ - 3 * dict_sigma[ibdt],
                      B0Mass_ + 3 * dict_sigma[ibdt])

    databkg = fullbkg.reduce(RooArgSet(theBMass, mumuMass, mumuMassE), cut)
    r = bkg_exp.fitTo(databkg, RooFit.Save(), ROOT.RooFit.Range('left,right'))

    frame = theBMass.frame()
    databkg.plotOn(frame, RooFit.Binning(70), RooFit.MarkerSize(.7))
    bkg_exp.plotOn(frame, )

    # bkg_exp.fixCoefRange('left,right')

    nbkg = RooRealVar('nbkg', 'bkg n', 1000, 0, 550000)
    ebkg = RooExtendPdf('ebkg', 'ebkg', bkg_exp, nbkg, 'sigRangeMC')
    ebkg.fitTo(databkg, ROOT.RooFit.Range('left,right'))
    ebkg.plotOn(frame, RooFit.LineStyle(ROOT.kDashed),
                RooFit.LineColor(ROOT.kGreen + 1), RooFit.Range(4.9, 5.6))
    frame.Draw()

    dict_b_v1[ibdt] = [nbkg.getVal(), nbkg.getError()]
コード例 #2
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def fitNBkg(ibdt, fullbkg, isample):

    slope = RooRealVar("slope", "slope", 0.5, -10, 10)
    bkg_exp = RooExponential("bkg_exp", "exponential", slope, theBMass)

    cut = cut_base + '&& bdt_prob > %s' % (ibdt)

    theBMass.setRange('sigRangeMC', B0Mass_ - 3 * dict_sigma[ibdt],
                      B0Mass_ + 3 * dict_sigma[ibdt])

    databkg = fullbkg.reduce(RooArgSet(theBMass, mumuMass, mumuMassE), cut)
    r = bkg_exp.fitTo(databkg, RooFit.Save(), ROOT.RooFit.Range('left,right'),
                      RooFit.PrintLevel(-1))

    frame = theBMass.frame()
    databkg.plotOn(frame, RooFit.Binning(70), RooFit.MarkerSize(.7))
    bkg_exp.plotOn(frame, )
    canv = ROOT.TCanvas()
    frame.Draw()

    nbkg = RooRealVar('nbkg', 'bkg n', 1000, 0, 550000)
    ebkg = RooExtendPdf(
        'ebkg', 'ebkg', bkg_exp, nbkg,
        'sigRangeMC')  ## here imposing the range to calculate bkg yield
    ebkg.fitTo(databkg, ROOT.RooFit.Range('left,right'), RooFit.PrintLevel(-1))
    ebkg.plotOn(frame, RooFit.LineStyle(ROOT.kDashed),
                RooFit.LineColor(ROOT.kGreen + 1), RooFit.Range(4.9, 5.6))
    frame.Draw()
    #     canv.SaveAs('bkg_fit_bdt%f_sample%i.pdf'%(ibdt,isample))

    dict_b_v1[ibdt] = [nbkg.getVal(), nbkg.getError()]
コード例 #3
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def RooFitSig(mbbarray, bdtarray, weightarray, TC_mass, binstart, binend):

    fitstart = 40
    fitend = 150

    mbbarray = range(200)
    bdtarray = range(200)
    weightarray = range(200)

    mass = RooRealVar("X", "m(bb)[GeV]", fitstart, fitend)
    BDT = RooRealVar("BDT", "BDT", -1, 100)
    weight = RooRealVar("weight", "weight", -100, 200)

    branchnames = ["X", "BDT", "weight"]

    dtype = np.dtype([(branchnames[idx], np.float64)
                      for idx in range(len(branchnames))])
    treearray = np.array([(mbbarray[idx], bdtarray[idx], weightarray[idx])
                          for idx in range(len(mbbarray))], dtype)

    tree = rnp.array2tree(treearray)

    m0 = RooRealVar("m0", "m0", TC_mass * 1., TC_mass * 1. - 60.,
                    TC_mass * 1. + 60.)
    m02 = RooRealVar("m02", "m02", TC_mass * 1., TC_mass * 1. - 60.,
                     TC_mass * 1. + 60.)
    alpha = RooRealVar("alpha", "alpha", 1.295, 1.0, 1.6)
    sigma2 = RooRealVar("sigma2", "sigma2", 35, 8., 100)
    n = RooRealVar("n", "n", 5, 1, 35)

    mean = RooRealVar("mean", "mean of gaussian", 750, 0, 6000)
    sigma = RooRealVar("sigma", "width of gaussian", 90, 38, 300)

    gauss = RooGaussian("gauss", "gaussian PDF", mass, m0, sigma)
    gauss2 = RooGaussian("gauss2", "gaussian PDF", mass, m02, sigma2)
    CBshape = RooCBShape("CBshape", "Crystal Ball PDF", mass, m0, sigma2,
                         alpha, n)

    ##PDF normalization
    num1 = RooRealVar("num1", "number of events", 400, 0, 5000)

    ##relative weight of 2 PDFs
    f = RooRealVar("f", "f", 0.95, 0.6, 1)

    sigPdf = RooAddPdf("sigPdf", "Signal PDF", RooArgList(CBshape, gauss),
                       RooArgList(f))
    extPdf = RooExtendPdf("extPdf", "extPdf", sigPdf, num1)
    data = RooDataSet("data", "data", tree, RooArgSet(mass, BDT, weight),
                      "BDT>0", "weight")

    xframe = mass.frame()
    mass.setBins(20)
    data.plotOn(xframe)
    extPdf.plotOn(
        xframe)  #,Normalization(1.0,RooAbsReal.RelativeExpected),LineColor(1))

    hist = extPdf.createHistogram("X", fitend - fitstart)
    hist.SetAxisRange(binstart, binend)
    return deepcopy(hist)
コード例 #4
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ファイル: test_RooMCstudy.py プロジェクト: wvieri/new_git
xArg = RooArgSet(x)

N_times_experiments = 1000
N_number_of_events = 500

# gauss 16
mean16 = RooRealVar("mean16","mean of gaussian",-1,-10,10)
sigma16 = RooRealVar("sigma16","width of gaussian",2,0.1,10)

gauss16 = RooGaussian("gauss16","gaussian PDF",x,mean16,sigma16)

nGauss16  = RooRealVar("nGauss16", "nGauss16", N_number_of_events ,  0. ,1000 )

gauss16_ext =  RooExtendPdf("gauss16_ext",  "extended p.d.f", gauss16,  nGauss16)

gauss16_ext.plotOn( xframe10 )

# RooMCStudy
mgr1 = RooMCStudy(gauss16_ext , gauss16_ext , xArg )
mgr1.generateAndFit( N_times_experiments , N_number_of_events )

# plot

list_par = [mean16, sigma16, nGauss16]

list_frame1 = RooMCStudy_box( mgr1 , list_par )



# -------------------------------------------
# plot and save
コード例 #5
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ファイル: test_addPDF_extPDF.py プロジェクト: wvieri/new_git
print "for gauss3 before fit"
print "mean3: ", mean3.Print()," sigma3: ",sigma3.Print()
print "nGauss3: ", nGauss3.Print()


# fit
gauss3_ext.fitTo(data1)

# plot

norm3 = nGauss3.getVal()

#gauss3_ext.plotOn(xframe2, RooFit.LineColor(RooFit.kRed))
#gauss3_ext.plotOn(xframe2, RooFit.Normalization(norm3, RooAbsReal.NumEvent), RooFit.LineColor(RooFit.kRed))
gauss3_ext.plotOn(xframe2, RooFit.Normalization(1.0, RooAbsReal.RelativeExpected), RooFit.LineColor(RooFit.kRed))

#gauss3.plotOn(xframe2, RooFit.Normalization(norm3, RooAbsReal.NumEvent), RooFit.LineColor(RooFit.kRed))

data1.plotOn(xframe2)
gauss1.plotOn(xframe2,RooFit.LineColor(RooFit.kBlue))

print "for data1"
print "number of events: ", data1.sumEntries()

print "for gauss3 after fit"
print "mean3: ", mean3.Print()," sigma3: ",sigma3.Print()
print "nGauss3: ", nGauss3.Print()

# -------------------------------------------
# 3. Add PDF = gauss4 + gauss5
コード例 #6
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ファイル: test_fit_SB_plot.py プロジェクト: wvieri/new_git
print "iLeft: ", iLeft.getVal()
print "iTotal: ", iTotal.getVal()

#iLeft = gauss11_ext.createIntegral(xArg, RooFit.Range("left_gaussian_range"))
#iTotal = gauss11_ext.createIntegral(xArg, RooFit.Range("whole_range"))

#print "without NormSet"
#print "iLeft: ", iLeft.getVal()
#print "iTotal: ", iTotal.getVal()

n_total_evaluate = nGauss11.getVal() / iLeft.getVal()
print "n_total_evaluate: ", n_total_evaluate

#gauss11_ext.plotOn(xframe7,RooFit.Normalization( n_total_evaluate , RooAbsReal.NumEvent), RooFit.Range("whole_range"), RooFit.LineColor(RooFit.kRed))
#gauss11_ext.plotOn(xframe7,RooFit.Normalization( nGauss11.getVal() , RooAbsReal.NumEvent), RooFit.Range("whole_range"), RooFit.LineColor(RooFit.kRed))
gauss11_ext.plotOn(xframe7,RooFit.Normalization( nGauss11.getVal() , RooAbsReal.NumEvent), RooFit.Range("left_gaussian_range"), RooFit.LineColor(RooFit.kRed))

#gauss11_ext.plotOn(xframe7,RooFit.Normalization( nGauss11.getVal() , RooAbsReal.NumEvent), RooFit.Range("whole_range"), RooFit.LineColor(RooFit.kRed),RooFit.DrawOption("F"), RooFit.FillColor(RooFit.kRed), RooFit.FillStyle(1001) )


#data3.plotOn(xframe7)
data3_half.plotOn(xframe7)

#gauss11.plotOn(xframe7,RooFit.LineColor(RooFit.kRed))

# -------------------------------------------
# 8. use combined PDF to fit SB only and test fixAddCoefRange

xframe8 = x.frame(RooFit.Title("8. use combined PDF to fit SB only and test fixAddCoefRange"))

# gauss 12
コード例 #7
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ファイル: PlotBkg.py プロジェクト: hbakhshi/HaNaMiniAnalyzer
norm.Print()
mass_var = multipdf.getVariables().first()
mass_var.setRange("HiggsMassWindow5",120,130)
mass_var.setRange("HiggsMassWindow2",123,127)
mass_var.setRange("HiggsMassWindow10",115,135)
mass_var.setRange("WholeRange",100,180)
frame = mass_var.frame()
option = "AL"
pdf_information = {}

multipdf.plotOn( frame )
for pdf_index in range(0,multipdf.getNumPdfs()):
    pdf_ = multipdf.getPdf( pdf_index )
    print pdf_.GetName() + "_Normalized" , pdf_.GetTitle()
    pdf = RooExtendPdf( pdf_.GetName() + "_Normalized" , pdf_.GetTitle() , pdf_ , norm )
    pdf.plotOn( frame , RooFit.DrawOption(option) , RooFit.LineColor( colors[pdf_index] ) , RooFit.LineStyle(0) , RooFit.LineWidth(3) , RooFit.Range("WholeRange") )
    totalInt = pdf.createIntegral( RooArgSet(mass_var) ,RooFit.Range("WholeRange"))
    #totalInt.Print() , RooFit.NormSet( RooArgSet(mass_var) ),
    fracInt5 = pdf.createIntegral( RooArgSet(mass_var) ,RooFit.Range("HiggsMassWindow5"))
    fracInt2 = pdf.createIntegral( RooArgSet(mass_var) ,RooFit.Range("HiggsMassWindow2"))
    fracInt10 = pdf.createIntegral( RooArgSet(mass_var) ,RooFit.Range("HiggsMassWindow10"))
    #fracInt.Print()
    if "A" in option :
        option = "L"
    pdf_information[ pdf_index ] = { "name":pdf.GetName() , "pdf":pdf , "ratio5":fracInt5.getVal()/totalInt.getVal(), "ratio2":fracInt2.getVal()/totalInt.getVal(), "ratio10":fracInt10.getVal()/totalInt.getVal() }

doSig = False
if len(sys.argv) > 3 :
    fsigName = sys.argv[2]
    fsig = TFile.Open( fsigName )
    sigPdf = fsig.Get( sys.argv[3] )