from OstapTutor.TestVars1 import m_psi,m_ups
import Ostap.FitModels as Models
signal_psi = Models.CB2_pdf('Jpsi' ,
mass = m_psi ,
sigma = 0.013 ,
mean = 3.096 )
signal_psi.aL.fix(1.8)
signal_psi.aR.fix(1.8)
signal_psi.nL.fix(1.8)
signal_psi.nR.fix(1.8)
## define model for J/psi
model_psi = Models.Fit1D( signal = signal_psi ,
background = Models.Bkg_pdf ( 'BJpsi' , mass = m_psi ) )
## define the model for Y
model_Y = Models.Manca2_pdf ( m_ups , power = 0 ,
m1s = 9.4539e+00 ,
sigma = 4.03195e-02 )
model_Ypsi = Models.MancaX_pdf ( model_Y ,
signal_psi ,
suffix = '' )
# ==========================================================================================
# The END
# ==========================================================================================
signal_Lc = Models.Lc_pdf(mass=m_Lc,
name='Lc',
mean=2.2884e+00,
sigma=5.1856e-03)
model_D0 = Models.Fit1D(signal=signal_D0, bpower=1)
model_Dp = Models.Fit1D(signal=signal_Dp, bpower=1)
model_Ds = Models.Fit1D(signal=signal_Ds, bpower=1)
model_Lc = Models.Fit1D(signal=signal_Lc, bpower=1)
model_Y0 = Models.Manca_pdf(m_ups, power=1, name='Y0')
model_Y1 = Models.Manca2_pdf(m_ups,
power=2,
name='Y1',
m1s=9.4539e+00,
sigma=4.03195e-02)
model_Y2 = Models.Manca2_pdf(m_ups,
power=1,
name='Y2',
m1s=model_Y1.m1s,
sigma=model_Y1.s1s,
alphaL=model_Y1.aL,
alphaR=model_Y1.aR,
nL=model_Y1.nL,
nR=model_Y1.nR)
signal_D0.mean.fix(1.8652e+00)
signal_Dp.mean.fix(1.8694e+00)
