mK = 0.49369
mPion = 0.1396
bw = cpp.Gaudi.Math.Phi0(1.0195, 0.0043, mK)
signal = Models.BreitWigner_pdf('BW0',
bw,
mass=m_phi,
gamma=0.0043,
mean=1.0195,
convolution=0.0015)
## Phase space as background:
ps = cpp.Gaudi.Math.PhaseSpaceNL(2 * mK, 10.0, 2, 5)
bkg = Models.PSPol_pdf('PS0', mass=m_phi, phasespace=ps, power=1)
f2 = cpp.Gaudi.Math.Flatte2(0.980, 165, 4.21, mPion, mPion, mK, mK)
flatte = Models.Flatte2_pdf('F20', f2, mass=m_phi, m0_980=1.000, m0g1=0.165)
flatte.mean.fix(0.980)
model = Models.Fit1D(signal=signal, othersignals=[flatte], background=bkg)
model.S.fix(10000)
model.B.fix(5000)
model.S_1.fix(5000)
data = model.pdf.generate(varset, 20000)
if 0 != result.status() or 3 != result.covQual():
logger.warning('Fit is not perfect MIGRAD=%d QUAL=%d ' %
(result.status(), result.covQual()))
print result
else:
print "\tPoly4e tau= %s " % result(m_p4e.tau.GetName())[0]
for phi in m_p4e.phis:
print "\tPoly4e: phi= %s " % phi.ve()
models.append(m_p4e)
# =============================================================================
logger.info("Test Poly(4)*PS -Distribution")
# =============================================================================
ps = cpp.Gaudi.Math.PhaseSpaceNL(0, 20, 2, 4)
m_ps = Models.PSPol_pdf('PS', x, ps, power=4)
with rooSilent():
result, f = m_ps.fitTo(dataset2)
result, f = m_ps.fitTo(dataset2)
if 0 != result.status() or 3 != result.covQual():
logger.warning('Fit is not perfect MIGRAD=%d QUAL=%d ' %
(result.status(), result.covQual()))
print result
else:
for phi in m_ps.phis:
print "\tPoly3ps: phi= %s " % phi.ve()
models.append(m_ps)
sigPhi0 = Models.BreitWigner_pdf('Phi0',
bw,
mean=1.0195,
gamma=0.0043,
mass=m_phi,
convolution=0.0005)
sigPhi = sigPhi0
ps2 = cpp.Gaudi.Math.PhaseSpaceNL(2 * 0.4937, 5.278 - 3.096, 2, 3)
model0 = Models.Fit2D(
signal_1=sigB,
signal_2=sigPhi0,
##
bkg2=Models.PSPol_pdf('PSP0', m_phi, ps2, power=1),
bkgB=Models.PSPol_pdf('PSB0', m_phi, ps2, power=1),
suffix='_GEN')
model0.bkg1.tau.fix(0)
model0.bkgA.tau.fix(0)
model0.ss.fix(1000)
model0.sb.fix(300)
model0.bs.fix(300)
model0.bb.fix(300)
model1 = Models.Fit2D(
signal_1=sigB,
signal_2=sigPhi,
##
bkg2=Models.PSPol_pdf('PSP', m_phi, ps2, power=1),
