def get_jo(mass=125, mode='VBF'):
"""
Determine width from yellowhiggs report
and output a jo file for a given m_H
"""
best_mass = sorted(masses_yh, key=lambda m: abs(m - float(mass)))[0]
width = br(best_mass, '2boson')[0]
print '%s: Mass = %s; Width = %s (calculated with m_H = %s)' % (mode, mass, width, best_mass)
if mode == 'VBF':
return vbf.format(mass, width)
elif mode == 'gg':
return ggh.format(mass, width)
else:
raise RuntimeError('Wrong mode !')
def get_jo(mass=125, mode='VBF'):
"""
Determine width from yellowhiggs report
and output a jo file for a given m_H
"""
best_mass = sorted(masses_yh, key=lambda m: abs(m - float(mass)))[0]
width = br(best_mass, '2boson')[0]
print '%s: Mass = %s; Width = %s (calculated with m_H = %s)' % (
mode, mass, width, best_mass)
if mode == 'VBF':
return vbf.format(mass, width)
elif mode == 'gg':
return ggh.format(mass, width)
else:
raise RuntimeError('Wrong mode !')
def BR_YR3(mass, productionmode):
if productionmode in ("ZH", "ttH") and mass < 300:
result = BR_fromoldspreadsheet(productionmode, mass)
if 120 <= mass <= 130:
result *= YR4data_BR_ZZ[mass] / yellowhiggs.br(mass, "ZZ")[0]
if productionmode == "ZH":
result *= filterefficiencyZH[
mass].nominal_value / oldfilterefficiencyZH
return result
mass = int(str(mass))
try:
result = yellowhiggs.br(mass, "llll(e,mu,tau)")[0]
except ValueError:
return .5 * (BR_YR3(mass + 1, productionmode) +
BR_YR3(mass - 1, productionmode))
if productionmode in ("ggH", "VBF", "WplusH", "WminusH"):
if 120 <= mass <= 130:
result *= YR4data_BR_4l[mass] / yellowhiggs.br(
mass, "llll(e,mu,tau)")[0]
return result
if 120 <= mass <= 130: assert False
#need to get ZZ2l2x BR
#from the comment here: https://github.com/CJLST/HHZZbb/blob/454fffb5842f470e71e89348a6de7a8d30f4a813/AnalysisStep/test/prod/samples_2016_MC.csv#L5-L6
#it doesn't say how to get BR(H->ZZ*->2L2nu) or BR(H->WW*->2L2nu)
#llnunu = ZZllnunu + WWlnulnu
# = ZZllnunu + 9*WWemununu
# = ZZllnunu + 9*emununu
result += yellowhiggs.br(mass, "llqq(e,mu,tau)")[0] + yellowhiggs.br(
mass,
"llnunu(e,mu,tau)")[0] - 9 * yellowhiggs.br(mass, "enuemunumu")[0]
if productionmode == "ZH":
result *= filterefficiencyZH[mass].nominal_value
elif productionmode == "ttH":
result *= filterefficiencyttH[mass].nominal_value
else:
assert False, productionmode
return result
def histfactory(self, sample, category, systematics=False,
rec=None, weights=None, mva=False,
uniform=False, nominal=None):
if not systematics:
return
if len(self.modes) != 1:
raise TypeError(
'histfactory sample only valid for single production mode')
if len(self.masses) != 1:
raise TypeError(
'histfactory sample only valid for single mass point')
# isolation systematic
sample.AddOverallSys(
'ATLAS_ANA_HH_{0:d}_Isolation'.format(self.year),
1. - 0.06,
1. + 0.06)
mode = self.modes[0]
if mode in ('Z', 'W'):
_uncert_mode = 'VH'
else:
_uncert_mode = self.MODES_WORKSPACE[mode]
if self.year == 2011:
energy = 7
elif self.year == 2012:
energy = 8
else:
raise ValueError(
"collision energy is unknown for year {0:d}".format(self.year))
# QCD_SCALE
for qcd_scale_term, qcd_scale_mode, qcd_scale_category, values in self.QCD_SCALE:
if qcd_scale_mode == _uncert_mode and qcd_scale_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(qcd_scale_term, low, high)
# UE UNCERTAINTY
for ue_term, ue_mode, ue_category, values in self.UE_UNCERT:
if ue_mode == _uncert_mode and ue_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(ue_term, low, high)
# PDF ACCEPTANCE UNCERTAINTY (OverallSys)
for pdf_term, pdf_mode, pdf_category, values in self.PDF_ACCEPT_NORM_UNCERT:
if pdf_mode == _uncert_mode and pdf_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(pdf_term, low, high)
sample_nom = sample.hist
# PDF ACCEPTANCE UNCERTAINTY (HistoSys) ONLY FOR MVA
if mva:
for pdf_term, pdf_mode, pdf_category, hist_names in self.PDF_ACCEPT_SHAPE_UNCERT:
if pdf_mode == _uncert_mode and pdf_category == category.name:
high_name, low_name = hist_names.format(energy).split('/')
high_shape, low_shape = self.PDF_ACCEPT_file[high_name], self.PDF_ACCEPT_file[low_name]
if len(high_shape) != len(sample.hist):
log.warning("skipping pdf acceptance shape systematic "
"since histograms are not compatible")
continue
high = sample_nom.Clone(shallow=True, name=sample_nom.name + '_{0}_UP'.format(pdf_term))
low = sample_nom.Clone(shallow=True, name=sample_nom.name + '_{0}_DOWN'.format(pdf_term))
high *= high_shape
low *= low_shape
histsys = histfactory.HistoSys(
pdf_term, low=low, high=high)
sample.AddHistoSys(histsys)
#mixing Norms
if self.SM:
log.info('adding norm factor')
sample.AddNormFactor('ATLAS_epsilon', 1., -200., 200., False)
elif self.BSM:
log.info('adding norm factor')
sample.AddNormFactor('ATLAS_epsilon_rejected', 1., -200., 200., False)
else:
log.info('no norms for {0}'.format(self.name))
# BR_tautau
_, (br_up, br_down) = yellowhiggs.br(
self.mass, 'tautau', error_type='factor')
sample.AddOverallSys('ATLAS_BR_tautau', br_down, br_up)
# <NormFactor Name="mu_BR_tautau" Val="1" Low="0" High="200" />
sample.AddNormFactor('mu_BR_tautau', 1., 0., 200., True)
#mu_XS[energy]_[mode]
#_, (xs_up, xs_down) = yellowhiggs.xs(
# energy, self.mass, self.MODES_DICT[self.mode][0],
# error_type='factor')
#sample.AddOverallSys(
# 'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
# xs_down, xs_up)
sample.AddNormFactor(
'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
1., 0., 200., True)
# https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/HSG4Uncertainties
# pdf uncertainty
if mode == 'gg':
if energy == 8:
sample.AddOverallSys('pdf_Higgs_gg', 0.93, 1.08)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_gg', 0.92, 1.08)
else:
if energy == 8:
sample.AddOverallSys('pdf_Higgs_qq', 0.97, 1.03)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_qq', 0.98, 1.03)
# EWK NLO CORRECTION FOR VBF ONLY
if mode == 'VBF':
sample.AddOverallSys('NLO_EW_Higgs', 0.98, 1.02)
# QCDscale_ggH3in HistoSys ONLY FOR MVA
# also see ggH3in script
if mva and mode == 'gg' and category.name == 'vbf':
Rel_Error_2j = 0.215
Error_exc = 0.08613046469238815 # Abs error on the exclusive xsec
xsec_exc = 0.114866523583739 # Exclusive Xsec
Error_3j = sqrt(Error_exc**2 - (Rel_Error_2j*xsec_exc)**2)
rel_error = Error_3j / xsec_exc
dphi = rec['true_dphi_jj_higgs_no_overlap']
scores = rec['classifier']
idx_2j = ((pi - dphi) < 0.2) & (dphi >= 0)
idx_3j = ((pi - dphi) >= 0.2) & (dphi >= 0)
# get normalization factor
dphi_2j = weights[idx_2j].sum()
dphi_3j = weights[idx_3j].sum()
weight_up = np.ones(len(weights))
weight_dn = np.ones(len(weights))
weight_up[idx_2j] -= (dphi_3j / dphi_2j) * rel_error
weight_dn[idx_2j] += (dphi_3j / dphi_2j) * rel_error
weight_up[idx_3j] += rel_error
weight_dn[idx_3j] -= rel_error
weight_up *= weights
weight_dn *= weights
up_hist = nominal.clone(shallow=True, name=sample_nom.name + '_QCDscale_ggH3in_UP')
up_hist.Reset()
dn_hist = nominal.clone(shallow=True, name=sample_nom.name + '_QCDscale_ggH3in_DOWN')
dn_hist.Reset()
fill_hist(up_hist, scores, weight_up)
fill_hist(dn_hist, scores, weight_dn)
if uniform:
up_hist = uniform_hist(up_hist)
dn_hist = uniform_hist(dn_hist)
shape = histfactory.HistoSys('QCDscale_ggH3in',
low=dn_hist,
high=up_hist)
norm, shape = histfactory.split_norm_shape(shape, sample_nom)
sample.AddHistoSys(shape)
for more information.
Author: Evan K. Friis, UW Madison
'''
from datacommon import square, cube, quad, picobarns, \
br_w_leptons, br_z_leptons, query_cli, femtobarns
from data8TeV import datadefs as datadefs52
from string import Template
try:
from yellowhiggs import xs, br, xsbr
br(130.,'WW')
except:
#print "warning: yellowhiggs error"
#define / override functions to avoid crashes
def br(*args, **kwargs):
return -99
def xs(*args, **kwargs):
return -99, (-99, 99)
def xsbr(*args, **kwargs):
return -99, (-99, 99)
# Figure this out later.
data_name_map = {}
datadefs = {
for more information.
Author: Evan K. Friis, UW Madison
'''
from datacommon import square, cube, quad, picobarns, \
br_w_leptons, br_z_leptons, query_cli, femtobarns
from data8TeV import datadefs as datadefs52
from string import Template
try:
from yellowhiggs import xs, br, xsbr
br(130.,'WW')
except:
#print "warning: yellowhiggs error"
#define / override functions to avoid crashes
def br(*args, **kwargs):
return -99
def xs(*args, **kwargs):
return -99, (-99, 99)
def xsbr(*args, **kwargs):
return -99, (-99, 99)
# Figure this out later.
data_name_map = {}
datadefs = {
for more information.
Author: Evan K. Friis, UW Madison
'''
from datacommon import square, cube, quad, picobarns, \
br_w_leptons, br_z_leptons, query_cli, femtobarns
from data8TeV import datadefs as datadefs52
from string import Template
try:
from yellowhiggs import xs, br, xsbr
br(130., 'WW')
except:
#print "warning: yellowhiggs error"
#define / override functions to avoid crashes
def br(*args, **kwargs):
return -99
def xs(*args, **kwargs):
return -99, (-99, 99)
def xsbr(*args, **kwargs):
return -99, (-99, 99)
# Figure this out later.
data_name_map = {}
def histfactory(self, sample, category, systematics=False):
if not systematics:
return
if len(self.modes) != 1:
raise TypeError(
'histfactory sample only valid for single production mode')
if len(self.masses) != 1:
raise TypeError(
'histfactory sample only valid for single mass point')
mode = self.modes[0]
if mode in ('Z', 'W'):
_qcd_scale_mode = 'VH'
else:
_qcd_scale_mode = self.MODES_WORKSPACE[mode]
# QCD_SCALE
for qcd_scale_term, qcd_scale_mode, qcd_scale_category, values in self.QCD_SCALE:
if qcd_scale_mode == _qcd_scale_mode and qcd_scale_category.lower() in category.name.lower():
high, low = map(float, values.split('/'))
sample.AddOverallSys(qcd_scale_term, low, high)
# GEN_QMASS
for qmass_term, qmass_mode, qmass_category, values in self.GEN_QMASS:
if qmass_mode == _qcd_scale_mode and qmass_category.lower() in category.name.lower():
high, low = map(float, values.split('/'))
sample.AddOverallSys(qmass_term, low, high)
# BR_tautau
_, (br_up, br_down) = yellowhiggs.br(
self.mass, 'tautau', error_type='factor')
sample.AddOverallSys('ATLAS_BR_tautau', br_down, br_up)
# <NormFactor Name="mu_BR_tautau" Val="1" Low="0" High="200" />
sample.AddNormFactor('mu_BR_tautau', 1., 0., 200., True)
if self.year == 2011:
energy = 7
elif self.year == 2012:
energy = 8
else:
raise ValueError(
"collision energy is unknown for year {0:d}".format(self.year))
#mu_XS[energy]_[mode]
#_, (xs_up, xs_down) = yellowhiggs.xs(
# energy, self.mass, self.MODES_DICT[self.mode][0],
# error_type='factor')
#sample.AddOverallSys(
# 'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
# xs_down, xs_up)
sample.AddNormFactor(
'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
1., 0., 200., True)
# https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/HSG4Uncertainties
# underlying event uncertainty in the VBF category
if 'vbf' in category.name.lower():
if mode == 'gg':
sample.AddOverallSys('ATLAS_UE_gg', 0.7, 1.3)
elif mode == 'VBF':
sample.AddOverallSys('ATLAS_UE_qq', 0.94, 1.06)
# pdf uncertainty
if mode == 'gg':
if energy == 8:
sample.AddOverallSys('pdf_Higgs_gg', 0.93, 1.08)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_gg', 0.92, 1.08)
else:
if energy == 8:
sample.AddOverallSys('pdf_Higgs_qq', 0.97, 1.03)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_qq', 0.98, 1.03)
for more information.
Author: Evan K. Friis, UW Madison
"""
from datacommon import square, cube, quad, picobarns, br_w_leptons, br_z_leptons, query_cli
from data8TeV import datadefs as datadefs52
from string import Template
try:
from yellowhiggs import xs, br, xsbr
br(130.0, "WW")
except:
# print "warning: yellowhiggs error"
# define / override functions to avoid crashes
def br(*args, **kwargs):
return -99
def xs(*args, **kwargs):
return -99, (-99, 99)
def xsbr(*args, **kwargs):
return -99, (-99, 99)
# Figure this out later.
data_name_map = {}
def histfactory(self,
sample,
category,
systematics=False,
rec=None,
weights=None,
mva=False,
uniform=False,
nominal=None):
if not systematics:
return
if len(self.modes) != 1:
raise TypeError(
'histfactory sample only valid for single production mode')
if len(self.masses) != 1:
raise TypeError(
'histfactory sample only valid for single mass point')
# isolation systematic
sample.AddOverallSys('ATLAS_ANA_HH_{0:d}_Isolation'.format(self.year),
1. - 0.06, 1. + 0.06)
mode = self.modes[0]
if mode in ('Z', 'W'):
_uncert_mode = 'VH'
else:
_uncert_mode = self.MODES_WORKSPACE[mode]
if self.year == 2011:
energy = 7
elif self.year == 2012:
energy = 8
else:
raise ValueError(
"collision energy is unknown for year {0:d}".format(self.year))
# QCD_SCALE
for qcd_scale_term, qcd_scale_mode, qcd_scale_category, values in self.QCD_SCALE:
if qcd_scale_mode == _uncert_mode and qcd_scale_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(qcd_scale_term, low, high)
# UE UNCERTAINTY
for ue_term, ue_mode, ue_category, values in self.UE_UNCERT:
if ue_mode == _uncert_mode and ue_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(ue_term, low, high)
# PDF ACCEPTANCE UNCERTAINTY (OverallSys)
for pdf_term, pdf_mode, pdf_category, values in self.PDF_ACCEPT_NORM_UNCERT:
if pdf_mode == _uncert_mode and pdf_category == category.name:
high, low = map(float, values.split('/'))
sample.AddOverallSys(pdf_term, low, high)
sample_nom = sample.hist
# PDF ACCEPTANCE UNCERTAINTY (HistoSys) ONLY FOR MVA
if mva:
for pdf_term, pdf_mode, pdf_category, hist_names in self.PDF_ACCEPT_SHAPE_UNCERT:
if pdf_mode == _uncert_mode and pdf_category == category.name:
high_name, low_name = hist_names.format(energy).split('/')
high_shape, low_shape = self.PDF_ACCEPT_file[
high_name], self.PDF_ACCEPT_file[low_name]
if len(high_shape) != len(sample.hist):
log.warning("skipping pdf acceptance shape systematic "
"since histograms are not compatible")
continue
high = sample_nom.Clone(shallow=True,
name=sample_nom.name +
'_{0}_UP'.format(pdf_term))
low = sample_nom.Clone(shallow=True,
name=sample_nom.name +
'_{0}_DOWN'.format(pdf_term))
high *= high_shape
low *= low_shape
histsys = histfactory.HistoSys(pdf_term,
low=low,
high=high)
sample.AddHistoSys(histsys)
# BR_tautau
_, (br_up, br_down) = yellowhiggs.br(self.mass,
'tautau',
error_type='factor')
sample.AddOverallSys('ATLAS_BR_tautau', br_down, br_up)
# <NormFactor Name="mu_BR_tautau" Val="1" Low="0" High="200" />
sample.AddNormFactor('mu_BR_tautau', 1., 0., 200., True)
#mu_XS[energy]_[mode]
#_, (xs_up, xs_down) = yellowhiggs.xs(
# energy, self.mass, self.MODES_DICT[self.mode][0],
# error_type='factor')
#sample.AddOverallSys(
# 'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
# xs_down, xs_up)
sample.AddNormFactor(
'mu_XS{0:d}_{1}'.format(energy, self.MODES_WORKSPACE[self.mode]),
1., 0., 200., True)
# https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/HSG4Uncertainties
# pdf uncertainty
if mode == 'gg':
if energy == 8:
sample.AddOverallSys('pdf_Higgs_gg', 0.93, 1.08)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_gg', 0.92, 1.08)
else:
if energy == 8:
sample.AddOverallSys('pdf_Higgs_qq', 0.97, 1.03)
else: # 7 TeV
sample.AddOverallSys('pdf_Higgs_qq', 0.98, 1.03)
# EWK NLO CORRECTION FOR VBF ONLY
if mode == 'VBF':
sample.AddOverallSys('NLO_EW_Higgs', 0.98, 1.02)
# QCDscale_ggH3in HistoSys ONLY FOR MVA
# also see ggH3in script
if mva and mode == 'gg' and category.name == 'vbf':
Rel_Error_2j = 0.215
Error_exc = 0.08613046469238815 # Abs error on the exclusive xsec
xsec_exc = 0.114866523583739 # Exclusive Xsec
Error_3j = sqrt(Error_exc**2 - (Rel_Error_2j * xsec_exc)**2)
rel_error = Error_3j / xsec_exc
dphi = rec['true_dphi_jj_higgs_no_overlap']
scores = rec['classifier']
idx_2j = ((pi - dphi) < 0.2) & (dphi >= 0)
idx_3j = ((pi - dphi) >= 0.2) & (dphi >= 0)
# get normalization factor
dphi_2j = weights[idx_2j].sum()
dphi_3j = weights[idx_3j].sum()
weight_up = np.ones(len(weights))
weight_dn = np.ones(len(weights))
weight_up[idx_2j] -= (dphi_3j / dphi_2j) * rel_error
weight_dn[idx_2j] += (dphi_3j / dphi_2j) * rel_error
weight_up[idx_3j] += rel_error
weight_dn[idx_3j] -= rel_error
weight_up *= weights
weight_dn *= weights
up_hist = nominal.clone(shallow=True,
name=sample_nom.name +
'_QCDscale_ggH3in_UP')
up_hist.Reset()
dn_hist = nominal.clone(shallow=True,
name=sample_nom.name +
'_QCDscale_ggH3in_DOWN')
dn_hist.Reset()
fill_hist(up_hist, scores, weight_up)
fill_hist(dn_hist, scores, weight_dn)
if uniform:
up_hist = uniform_hist(up_hist)
dn_hist = uniform_hist(dn_hist)
shape = histfactory.HistoSys('QCDscale_ggH3in',
low=dn_hist,
high=up_hist)
norm, shape = histfactory.split_norm_shape(shape, sample_nom)
sample.AddHistoSys(shape)
You can query the information in this file at the command line.
Run
python data8TeV.py --help
for more information.
Author: Evan K. Friis, UW Madison
'''
from datacommon import square, cube, quad, picobarns, br_w_leptons, br_z_leptons, query_cli
try:
from yellowhiggs import xs, br, xsbr
br(130.,'WW')
except:
#print "warning: yellowhiggs error"
#define / override functions to avoid crashes
def br(*args, **kwargs):
return -99
def xs(*args, **kwargs):
return -99, (-99, 99)
def xsbr(*args, **kwargs):
return -99, (-99, 99)
# Figure this out later.
data_name_map = {}
datadefs = {
'WJetsToLNu_PtW-100_TuneZ2star_8TeV-madgraph' : {
