ResolutionModel=tres.model(),
Bins=bin_spec,
Relative=rel_spec,
)
pdf = Single_Exponent_Time(Name="pdf", time=t, resolutionModel=res_model)
pdf = pdf.pdf()
gen_observables = [t, hlt1_excl_biased, hlt2_unbiased, hlt2_biased]
## Get proto data
proto_data = None
if options.protodata:
proto_file = TFile.Open(options.protodata)
if not proto_file.IsOpen():
raise OSError
for key in proto_file.GetListOfKeys():
if key.GetClassName() == "RooDataSet":
proto_data = key.ReadObj()
break
else:
raise RunTimeError
if not proto_data:
raise RunTimeError
## run the toy
toy.set_fit_opts(**dict(Verbose=False))
toy.run(Observables=gen_observables, Pdf=pdf, GenPdf=pdf, ProtoData=proto_data)
toy.write_output()
gexp_frac = RealVar(Name = "gexp_frac", Value = 0.1, MinMax = (0.0001, 0.9999))
add_model = AddModel("add_model", Models = [gexp_model, gauss_model], Fractions = [gexp_frac], ConditionalObservables = [st])
from ROOT import RooDecay as Decay
peak_tau = RealVar(Name = "peak_tau", Value = 0, Constant = True)
peak = Pdf(Name = "peak", Type = Decay, Parameters = [t_diff, peak_tau, add_model, 'SingleSided'], ConditionalObservables = [st])
## peak2 = Pdf(Name = "peak2", Type = Decay, Parameters = [t_diff, peak_tau, gexp_model, 'SingleSided'], ConditionalObservables = [st])
## peak3 = Pdf(Name = "peak3", Type = Decay, Parameters = [t_diff, peak_tau, gauss_model, 'SingleSided'], ConditionalObservables = [st])
# signal component
from P2VV.Parameterizations.MassPDFs import LP2011_Signal_Mass as Signal_Mass
sig_m = Signal_Mass(Name = 'sig_m', mass = m)
signal = Component('signal', (sig_m.pdf(), st_pdf, peak), Yield = (150000, 10000, 1000000))
sig_mass_pdf = buildPdf(Components = (signal, background), Observables = (m,), Name = 'sig_mass_pdf')
signal_name = signal.GetName()
mass_pdf = sig_mass_pdf
fitOpts = dict(NumCPU = 4, Timer = 1, Save = True, Minimizer = 'Minuit2', Optimize = 2, Offset = True,
Verbose = False)
gen_pdf = buildPdf(Components = (signal,), Observables = (t_diff, st), Name = 'gen_pdf')
fit_pdf = buildPdf(Components = (signal,), Observables = (t_diff,), Name = 'fit_pdf')
toy.set_fit_opts(**dict(Verbose = False))
toy.run(Observables = [t_diff, st], Pdf = fit_pdf, GenPdf = gen_pdf)
