def _estimate(self, region, channel, setup):
if setup.verbose:
printHeader("MC prediction for %s channel %s" %
(self.name, channel))
if channel == 'all':
return sum([
self.cachedEstimate(region, c, setup)
for c in ['MuMu', 'EE', 'EMu']
], u_float(0., 0.))
else:
preSelection = setup.preselection('MC', channel=channel)
cut = "&&".join([
region.cutString(setup.sys['selectionModifier']),
preSelection['cut']
])
weight = preSelection['weightStr']
if setup.verbose:
print "Using cut %s and weight %s" % (cut, weight)
if not self.sample[channel].has_key('chain'):
loadChain(self.sample[channel])
return setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(self.sample[channel]['chain'],
cutString=cut,
weight=weight,
returnError=True))
def _estimate(self, region, channel, setup):
printHeader("DD DY prediction for %s channel %s" %(self.name, channel))
#Sum of all channels for 'all'
if channel=='all':
return sum( [ self.cachedEstimate(region, c, setup) for c in ['MuMu', 'EE', 'EMu'] ], u_float(0.,0.) )
#MC based for 'EMu'
elif channel=='EMu':
preSelection = setup.preselection('MC', zWindow="allZ", channel=channel)
cut = "&&".join([region.cutString(setup.sys['selectionModifier']), preSelection['cut'] ])
weight = preSelection['weightStr']
if setup.verbose:
print "Using cut %s and weight %s"%(cut, weight)
return setup.lumi[channel]/1000. * u_float( getYieldFromChain(setup.sample['DY'][channel]['chain'], cutString = cut, weight=weight, returnError = True) )
#Data driven for EE and MuMu
else:
preSelection = setup.preselection('MC', zWindow="offZ", channel=channel)
weight = preSelection['weightStr']
assert abs(1.-setup.lumi[channel]/setup.sample['Data'][channel]['lumi'])<0.01, "Lumi specified in setup %f does not match lumi in data sample %f in channel %s"%(setup.lumi[channel], setup.sample['Data'][channel]['lumi'], channel)
cut_offZ_1b = "&&".join([region.cutString(setup.sys['selectionModifier']), setup.selection('MC', channel=channel, zWindow = 'offZ', **setup.defaultParameters(update={'nBTags':(1,-1)}))['cut'] ])
cut_onZ_1b = "&&".join([region.cutString(setup.sys['selectionModifier']), setup.selection('MC', channel=channel, zWindow = 'onZ', **setup.defaultParameters(update={'nBTags':(1,-1)}))['cut'] ])
cut_onZ_0b = "&&".join([region.cutString(setup.sys['selectionModifier']), setup.selection('MC', channel=channel, zWindow = 'onZ', **setup.defaultParameters(update={'nBTags':(0,0)}))['cut'] ])
cut_data_onZ_0b = "&&".join([region.cutString(setup.sys['selectionModifier']), setup.selection('Data', channel=channel, zWindow = 'onZ', **setup.defaultParameters(update={'nBTags':(0,0)}) )['cut'] ])
# R1 = DY-MC (offZ, 1b) / DY-MC (onZ, 1b)
# R2 = DY-MC (onZ, 1b) / DY-MC (onZ, 0b)
# DY-est = R1*R2*(Data(2l, onZ, 0b) - EWK(onZ, 0b)) = DY-MC (offZ, 1b) / DY-MC (onZ, 0b) *( Data(2l, onZ, 0b) - EWK(onZ, 0b))
yield_offZ_1b = setup.lumi[channel]/1000.*u_float( getYieldFromChain(setup.sample['DY'][channel]['chain'], cutString = cut_offZ_1b, weight=weight, returnError = True))
if setup.verbose: print "yield_offZ_1b: %s"%yield_offZ_1b
yield_onZ_0b = setup.lumi[channel]/1000.*u_float( getYieldFromChain(setup.sample['DY'][channel]['chain'], cutString = cut_onZ_0b, weight=weight, returnError = True))
if setup.verbose: print "yield_onZ_0b: %s"%yield_onZ_0b
yield_data = u_float( getYieldFromChain(setup.sample['Data'][channel]['chain'], cutString = cut_data_onZ_0b, weight=weight, returnError = True))
if setup.verbose: print "yield_data: %s (for cut: %s \n with weight: %s)"%(yield_data, cut_data_onZ_0b, weight)
#electroweak subtraction
print "\n Substracting electroweak backgrounds from data: \n"
yield_other = u_float(0., 0.)
for s in ['TTJets' , 'TTZ' , 'other']:
yield_other += setup.lumi[channel]/1000.*u_float(getYieldFromChain(setup.sample[s][channel]['chain'], cutString = cut_onZ_0b, weight=weight, returnError=True))
if setup.verbose: print "yield_other_onZ_0b %s added, now: %s"%(s, yield_other)
normRegYield = yield_data - yield_other
if normRegYield.val<0: print "\n !!!Warning!!! \n Negative normalization region yield data: (%s), MC: (%s) \n"%(yield_data, yield_other)
mcRatio = yield_offZ_1b / yield_onZ_0b
res = mcRatio * normRegYield
print "mcRatio is: ", mcRatio
return res
def _estimate(self, region, channel, setup):
if setup.verbose: printHeader("MC prediction for %s channel %s" %(self.name, channel))
if channel=='all':
return sum( [ self.cachedEstimate(region, c, setup) for c in ['MuMu', 'EE', 'EMu'] ], u_float(0., 0.) )
else:
preSelection = setup.preselection('MC', channel=channel)
cut = "&&".join([region.cutString(setup.sys['selectionModifier']), preSelection['cut']])
weight = preSelection['weightStr']
if setup.verbose:
print "Using cut %s and weight %s"%(cut, weight)
if not self.sample[channel].has_key('chain'):
loadChain(self.sample[channel])
return setup.lumi[channel]/1000.*u_float(getYieldFromChain(self.sample[channel]['chain'], cutString = cut, weight=weight, returnError = True) )
def _estimate(self, region, channel, setup):
printHeader("DD DY prediction for %s channel %s" %
(self.name, channel))
#Sum of all channels for 'all'
if channel == 'all':
return sum([
self.cachedEstimate(region, c, setup)
for c in ['MuMu', 'EE', 'EMu']
], u_float(0., 0.))
#MC based for 'EMu'
elif channel == 'EMu':
preSelection = setup.preselection('MC',
zWindow="allZ",
channel=channel)
cut = "&&".join([
region.cutString(setup.sys['selectionModifier']),
preSelection['cut']
])
weight = preSelection['weightStr']
if setup.verbose:
print "Using cut %s and weight %s" % (cut, weight)
return setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample['DY'][channel]['chain'],
cutString=cut,
weight=weight,
returnError=True))
#Data driven for EE and MuMu
else:
preSelection = setup.preselection('MC',
zWindow="offZ",
channel=channel)
weight = preSelection['weightStr']
assert abs(
1. -
setup.lumi[channel] / setup.sample['Data'][channel]['lumi']
) < 0.01, "Lumi specified in setup %f does not match lumi in data sample %f in channel %s" % (
setup.lumi[channel], setup.sample['Data'][channel]['lumi'],
channel)
cut_offZ_1b = "&&".join([
region.cutString(setup.sys['selectionModifier']),
setup.selection(
'MC',
channel=channel,
zWindow='offZ',
**setup.defaultParameters(update={'nBTags': (1,
-1)}))['cut']
])
cut_onZ_1b = "&&".join([
region.cutString(setup.sys['selectionModifier']),
setup.selection(
'MC',
channel=channel,
zWindow='onZ',
**setup.defaultParameters(update={'nBTags': (1,
-1)}))['cut']
])
cut_onZ_0b = "&&".join([
region.cutString(setup.sys['selectionModifier']),
setup.selection(
'MC',
channel=channel,
zWindow='onZ',
**setup.defaultParameters(update={'nBTags': (0,
0)}))['cut']
])
cut_data_onZ_0b = "&&".join([
region.cutString(setup.sys['selectionModifier']),
setup.selection(
'Data',
channel=channel,
zWindow='onZ',
**setup.defaultParameters(update={'nBTags': (0,
0)}))['cut']
])
# R1 = DY-MC (offZ, 1b) / DY-MC (onZ, 1b)
# R2 = DY-MC (onZ, 1b) / DY-MC (onZ, 0b)
# DY-est = R1*R2*(Data(2l, onZ, 0b) - EWK(onZ, 0b)) = DY-MC (offZ, 1b) / DY-MC (onZ, 0b) *( Data(2l, onZ, 0b) - EWK(onZ, 0b))
yield_offZ_1b = setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample['DY'][channel]['chain'],
cutString=cut_offZ_1b,
weight=weight,
returnError=True))
if setup.verbose: print "yield_offZ_1b: %s" % yield_offZ_1b
yield_onZ_0b = setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample['DY'][channel]['chain'],
cutString=cut_onZ_0b,
weight=weight,
returnError=True))
if setup.verbose: print "yield_onZ_0b: %s" % yield_onZ_0b
yield_data = u_float(
getYieldFromChain(setup.sample['Data'][channel]['chain'],
cutString=cut_data_onZ_0b,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_data: %s (for cut: %s \n with weight: %s)" % (
yield_data, cut_data_onZ_0b, weight)
#electroweak subtraction
print "\n Substracting electroweak backgrounds from data: \n"
yield_other = u_float(0., 0.)
for s in ['TTJets', 'TTZ', 'other']:
yield_other += setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample[s][channel]['chain'],
cutString=cut_onZ_0b,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_other_onZ_0b %s added, now: %s" % (
s, yield_other)
normRegYield = yield_data - yield_other
if normRegYield.val < 0:
print "\n !!!Warning!!! \n Negative normalization region yield data: (%s), MC: (%s) \n" % (
yield_data, yield_other)
mcRatio = yield_offZ_1b / yield_onZ_0b
res = mcRatio * normRegYield
print "mcRatio is: ", mcRatio
return res
def _estimate(self, region, channel, setup):
printHeader("DD TTZ prediction for '%s' channel %s" %(self.name, channel))
#Sum of all channels for 'all'
if channel=='all':
return sum( [ self.cachedEstimate(region, c, channel, setup) for c in ['MuMu', 'EE', 'EMu'] ] )
else:
#Data driven for EE, EMu and MuMu.
preSelection = setup.preselection('MC', channel=channel)
#check lumi consistency
assert abs(1.-setup.lumi[channel]/setup.sample['Data'][channel]['lumi'])<0.01, "Lumi specified in setup %f does not match lumi in data sample %f in channel %s"%(setup.lumi[channel], setup.sample['Data'][channel]['lumi'], channel)
selection_MC_2l = "&&".join([region.cutString(setup.sys['selectionModifier']), preSelection['cut']])
weight = preSelection['weightStr']
yield_MC_2l = setup.lumi[channel]/1000.*u_float(getYieldFromChain(setup.sample['TTZ'][channel]['chain'], cutString = selection_MC_2l, weight=weight, returnError = True) )
if setup.verbose: print "yield_MC_2l: %s"%yield_MC_2l
muonSelection_loosePt = looseMuIDString(ptCut=10)
electronSelection_loosePt = looseEleIDString(ptCut=10)
#mu_mu_mu
MuMuMuSelection = "nGoodMuons>=2" + '&&' + muonSelection_loosePt + "==3"
if setup.parameters['useTriggers']: MuMuMuSelection += '&&HLT_3mu'
#e_e_e
EEESelection = "nGoodElectrons>=2" + '&&' + electronSelection_loosePt + "==3"
if setup.parameters['useTriggers']: EEESelection += '&&HLT_3e'
#e_e_mu
EEMuSelection = "(nGoodMuons+nGoodElectrons)>=2" + "&&" + electronSelection_loosePt + "==2&&" + muonSelection_loosePt + "==1"
if setup.parameters['useTriggers']: EEMuSelection += '&&HLT_2e1mu'
#mu_mu_e
MuMuESelection = "(nGoodMuons+nGoodElectrons)>=2" + "&&" + electronSelection_loosePt + "==1&&" + muonSelection_loosePt + "==2"
if setup.parameters['useTriggers']: MuMuESelection += '&&HLT_2mu1e'
MC_hadronSelection = setup.selection('MC', hadronicSelection = True,
**setup.defaultParameters(update={'nJets': self.nJets, 'nBTags':self.nMediumBTags, 'metMin': 0., 'metSigMin':0., 'dPhiJetMet':0. })
)['cut']
data_hadronSelection = setup.selection('Data', hadronicSelection = True,
**setup.defaultParameters(update={'nJets': self.nJets, 'nBTags':self.nMediumBTags, 'metMin': 0., 'metSigMin':0., 'dPhiJetMet':0. })
)['cut']
#loose bjet selection added here
if self.nLooseBTags[0]>=0:
MC_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)>='+str(self.nLooseBTags[0])
data_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)>='+str(self.nLooseBTags[0])
if self.nLooseBTags[1]>=0:
MC_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)<='+str(self.nLooseBTags[1])
data_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)<='+str(self.nLooseBTags[1])
MC_MuMuMu = "&&".join([
MC_hadronSelection,
MuMuMuSelection,
"abs(mlmZ_mass-91.2)<10"
])
MC_EEE = "&&".join([
MC_hadronSelection,
EEESelection,
"abs(mlmZ_mass-91.2)<10"
])
MC_EEMu = "&&".join([
MC_hadronSelection,
EEMuSelection,
"abs(mlmZ_mass-91.2)<10"
])
MC_MuMuE = "&&".join([
MC_hadronSelection,
MuMuESelection,
"abs(mlmZ_mass-91.2)<10"
])
MC_3l = "(("+MC_MuMuMu+")||("+MC_EEE+")||("+MC_EEMu+")||("+MC_MuMuE+"))"
data_MuMuMu = "&&".join([
data_hadronSelection,
MuMuMuSelection,
"abs(mlmZ_mass-91.2)<10"
])
data_EEE = "&&".join([
data_hadronSelection,
EEESelection,
"abs(mlmZ_mass-91.2)<10"
])
data_EEMu = "&&".join([
data_hadronSelection,
EEMuSelection,
"abs(mlmZ_mass-91.2)<10"
])
data_MuMuE = "&&".join([
data_hadronSelection,
MuMuESelection,
"abs(mlmZ_mass-91.2)<10"
])
######yield_MC_3l computed for ALL channels but lumi changes slightly here depending on channel
yield_MC_3l = setup.lumi[channel]/1000.*u_float( getYieldFromChain(setup.sample['TTZ'][channel]['chain'], cutString = MC_3l, weight=weight, returnError = True))
if setup.verbose: print "yield_MC_looseSelection_3l: %s"%yield_MC_3l
yield_data_MuMuMu = u_float( getYieldFromChain(setup.sample['Data']['MuMu']['chain'], cutString = data_MuMuMu, weight=weight, returnError = True))
if setup.verbose: print "yield_data_looseSelection_MuMuMu: %s"%yield_data_MuMuMu
yield_data_EEE = u_float( getYieldFromChain(setup.sample['Data']['EE']['chain'], cutString = data_EEE, weight=weight, returnError = True))
if setup.verbose: print "yield_data_looseSelection_EEE: %s"%yield_data_EEE
yield_data_EMu = u_float( getYieldFromChain(setup.sample['Data']['EMu']['chain'], cutString = "(("+data_MuMuE+')||('+data_EEMu+'))', weight=weight, returnError = True))
if setup.verbose: print "yield_data_looseSelection_EMu: %s"%yield_data_EMu
yield_data_3l = yield_data_MuMuMu+yield_data_EEE+yield_data_EMu
if setup.verbose: print "yield_data_3l: %s"%yield_data_3l
#electroweak subtraction
print "\n Substracting electroweak backgrounds from data: \n"
yield_other = u_float(0., 0.)
for s in ['TTJets' , 'DY', 'other']:
yield_other+= setup.lumi[channel]/1000.* u_float(getYieldFromChain(setup.sample[s][channel]['chain'], cutString = MC_3l, weight=weight, returnError=True))
if setup.verbose: print "yield_looseSelection_other %s added, now: %s"%(s, yield_other)
normRegYield = yield_data_3l - yield_other
if normRegYield.val<0: print "\n !!!Warning!!! \n Negative normalization region yield data: (%s), MC: (%s) \n"%(yield_data_3l, yield_other)
print "normRegYield", normRegYield
print "\n Control Region predictys ", normRegYield, " TTZ events in data; ", yield_MC_3l, " TTZ events in MC. Ratio ---> ", (normRegYield/yield_MC_3l)
print "DD-TTZ ---> ", (normRegYield/yield_MC_3l)*yield_MC_2l
return (normRegYield/yield_MC_3l)*yield_MC_2l
def _estimate(self, region, channel, setup):
printHeader("DD TTZ prediction for '%s' channel %s" %
(self.name, channel))
#Sum of all channels for 'all'
if channel == 'all':
return sum([
self.cachedEstimate(region, c, channel, setup)
for c in ['MuMu', 'EE', 'EMu']
])
else:
#Data driven for EE, EMu and MuMu.
preSelection = setup.preselection('MC', channel=channel)
#check lumi consistency
assert abs(
1. -
setup.lumi[channel] / setup.sample['Data'][channel]['lumi']
) < 0.01, "Lumi specified in setup %f does not match lumi in data sample %f in channel %s" % (
setup.lumi[channel], setup.sample['Data'][channel]['lumi'],
channel)
selection_MC_2l = "&&".join([
region.cutString(setup.sys['selectionModifier']),
preSelection['cut']
])
weight = preSelection['weightStr']
yield_MC_2l = setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample['TTZ'][channel]['chain'],
cutString=selection_MC_2l,
weight=weight,
returnError=True))
if setup.verbose: print "yield_MC_2l: %s" % yield_MC_2l
muonSelection_loosePt = looseMuIDString(ptCut=10)
electronSelection_loosePt = looseEleIDString(ptCut=10)
#mu_mu_mu
MuMuMuSelection = "nGoodMuons>=2" + '&&' + muonSelection_loosePt + "==3"
if setup.parameters['useTriggers']: MuMuMuSelection += '&&HLT_3mu'
#e_e_e
EEESelection = "nGoodElectrons>=2" + '&&' + electronSelection_loosePt + "==3"
if setup.parameters['useTriggers']: EEESelection += '&&HLT_3e'
#e_e_mu
EEMuSelection = "(nGoodMuons+nGoodElectrons)>=2" + "&&" + electronSelection_loosePt + "==2&&" + muonSelection_loosePt + "==1"
if setup.parameters['useTriggers']: EEMuSelection += '&&HLT_2e1mu'
#mu_mu_e
MuMuESelection = "(nGoodMuons+nGoodElectrons)>=2" + "&&" + electronSelection_loosePt + "==1&&" + muonSelection_loosePt + "==2"
if setup.parameters['useTriggers']: MuMuESelection += '&&HLT_2mu1e'
MC_hadronSelection = setup.selection(
'MC',
hadronicSelection=True,
**setup.defaultParameters(
update={
'nJets': self.nJets,
'nBTags': self.nMediumBTags,
'metMin': 0.,
'metSigMin': 0.,
'dPhiJetMet': 0.
}))['cut']
data_hadronSelection = setup.selection(
'Data',
hadronicSelection=True,
**setup.defaultParameters(
update={
'nJets': self.nJets,
'nBTags': self.nMediumBTags,
'metMin': 0.,
'metSigMin': 0.,
'dPhiJetMet': 0.
}))['cut']
#loose bjet selection added here
if self.nLooseBTags[0] >= 0:
MC_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)>=' + str(
self.nLooseBTags[0])
data_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)>=' + str(
self.nLooseBTags[0])
if self.nLooseBTags[1] >= 0:
MC_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)<=' + str(
self.nLooseBTags[1])
data_hadronSelection += '&&Sum$(Jet_pt>30&&abs(Jet_eta)<2.4&&Jet_id&&Jet_btagCSV>0.605)<=' + str(
self.nLooseBTags[1])
MC_MuMuMu = "&&".join([
MC_hadronSelection, MuMuMuSelection, "abs(mlmZ_mass-91.2)<10"
])
MC_EEE = "&&".join(
[MC_hadronSelection, EEESelection, "abs(mlmZ_mass-91.2)<10"])
MC_EEMu = "&&".join(
[MC_hadronSelection, EEMuSelection, "abs(mlmZ_mass-91.2)<10"])
MC_MuMuE = "&&".join(
[MC_hadronSelection, MuMuESelection, "abs(mlmZ_mass-91.2)<10"])
MC_3l = "((" + MC_MuMuMu + ")||(" + MC_EEE + ")||(" + MC_EEMu + ")||(" + MC_MuMuE + "))"
data_MuMuMu = "&&".join([
data_hadronSelection, MuMuMuSelection, "abs(mlmZ_mass-91.2)<10"
])
data_EEE = "&&".join(
[data_hadronSelection, EEESelection, "abs(mlmZ_mass-91.2)<10"])
data_EEMu = "&&".join([
data_hadronSelection, EEMuSelection, "abs(mlmZ_mass-91.2)<10"
])
data_MuMuE = "&&".join([
data_hadronSelection, MuMuESelection, "abs(mlmZ_mass-91.2)<10"
])
######yield_MC_3l computed for ALL channels but lumi changes slightly here depending on channel
yield_MC_3l = setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample['TTZ'][channel]['chain'],
cutString=MC_3l,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_MC_looseSelection_3l: %s" % yield_MC_3l
yield_data_MuMuMu = u_float(
getYieldFromChain(setup.sample['Data']['MuMu']['chain'],
cutString=data_MuMuMu,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_data_looseSelection_MuMuMu: %s" % yield_data_MuMuMu
yield_data_EEE = u_float(
getYieldFromChain(setup.sample['Data']['EE']['chain'],
cutString=data_EEE,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_data_looseSelection_EEE: %s" % yield_data_EEE
yield_data_EMu = u_float(
getYieldFromChain(setup.sample['Data']['EMu']['chain'],
cutString="((" + data_MuMuE + ')||(' +
data_EEMu + '))',
weight=weight,
returnError=True))
if setup.verbose:
print "yield_data_looseSelection_EMu: %s" % yield_data_EMu
yield_data_3l = yield_data_MuMuMu + yield_data_EEE + yield_data_EMu
if setup.verbose: print "yield_data_3l: %s" % yield_data_3l
#electroweak subtraction
print "\n Substracting electroweak backgrounds from data: \n"
yield_other = u_float(0., 0.)
for s in ['TTJets', 'DY', 'other']:
yield_other += setup.lumi[channel] / 1000. * u_float(
getYieldFromChain(setup.sample[s][channel]['chain'],
cutString=MC_3l,
weight=weight,
returnError=True))
if setup.verbose:
print "yield_looseSelection_other %s added, now: %s" % (
s, yield_other)
normRegYield = yield_data_3l - yield_other
if normRegYield.val < 0:
print "\n !!!Warning!!! \n Negative normalization region yield data: (%s), MC: (%s) \n" % (
yield_data_3l, yield_other)
print "normRegYield", normRegYield
print "\n Control Region predictys ", normRegYield, " TTZ events in data; ", yield_MC_3l, " TTZ events in MC. Ratio ---> ", (
normRegYield / yield_MC_3l)
print "DD-TTZ ---> ", (normRegYield / yield_MC_3l) * yield_MC_2l
return (normRegYield / yield_MC_3l) * yield_MC_2l
