def main():
config = XSectionConfig(13)
# method = 'RooUnfoldSvd'
method = 'RooUnfoldBayes'
file_for_unfolding = File(config.unfolding_central, 'read')
for channel in ['electron', 'muon', 'combined']:
for variable in bin_edges.keys():
tau_value = get_tau_value(config, channel, variable)
h_truth, h_measured, h_response, h_fakes = get_unfold_histogram_tuple(
inputfile=file_for_unfolding,
variable=variable,
channel=channel,
met_type=config.met_type,
centre_of_mass=config.centre_of_mass_energy,
ttbar_xsection=config.ttbar_xsection,
luminosity=config.luminosity,
load_fakes=False,
visiblePS=False,
)
unfolding = Unfolding(
h_truth, h_measured, h_response, h_fakes,
method=method, k_value=-1, tau=tau_value)
unfolded_data = unfolding.closureTest()
plot_closure(h_truth, unfolded_data, variable, channel,
config.centre_of_mass_energy, method)
def main():
config = XSectionConfig(13)
# method = 'RooUnfoldSvd'
method = 'RooUnfoldBayes'
file_for_unfolding = File(config.unfolding_central, 'read')
for channel in ['electron', 'muon', 'combined']:
for variable in bin_edges.keys():
tau_value = get_tau_value(config, channel, variable)
h_truth, h_measured, h_response, h_fakes = get_unfold_histogram_tuple(
inputfile=file_for_unfolding,
variable=variable,
channel=channel,
met_type=config.met_type,
centre_of_mass=config.centre_of_mass_energy,
ttbar_xsection=config.ttbar_xsection,
luminosity=config.luminosity,
load_fakes=False,
visiblePS=False,
)
unfolding = Unfolding(h_truth,
h_measured,
h_response,
h_fakes,
method=method,
k_value=-1,
tau=tau_value)
unfolded_data = unfolding.closureTest()
plot_closure(h_truth, unfolded_data, variable, channel,
config.centre_of_mass_energy, method)
'y-title': 'Events/(0.2)'
},
'muon_absolute_eta': {
'min': 0,
'max': 2.6,
'rebin': 2,
'x-title': '$\left|\eta(\mu)\\right|$',
'y-title': 'Events/(0.2)'
},
}
b_tag_bin = '2orMoreBtags'
b_tag_bin_ctl = '0orMoreBtag'
category = 'central'
variables = bin_edges.keys()
save_as = ['pdf']
def main():
global measurement_config, histogram_files
global electron_fit_variables, muon_fit_variables, fit_variable_properties
global b_tag_bin, category, histogram_files, variables
global b_tag_bin_ctl
title_template = '$%.1f$ fb$^{-1}$(%d TeV)'
e_title = title_template % (measurement_config.new_luminosity / 1000.,
measurement_config.centre_of_mass_energy)
met_type = 'patType1CorrectedPFMet'
for variable in variables:
import json
from config import XSectionConfig
from config.variable_binning import bin_edges, bin_edges_vis
from tools.file_utilities import make_folder_if_not_exists
com = 13
fitVars = "M3_angle_bl"
config = XSectionConfig( com )
make_folder_if_not_exists('config/unfolding/FullPS/')
make_folder_if_not_exists('config/unfolding/VisiblePS/')
for channel in config.analysis_types.keys():
for variable in bin_edges.keys():
histogramTemplate = "unfolding_%s_analyser_%s_channel" % ( variable, channel )
outputJson = {
"output_folder": "plots/%sTeV/unfolding_tests/FullPS" % com,
"output_format": ["png", "pdf"],
"centre-of-mass energy" : com,
"channel": "%s" % channel,
"variable": "%s" % variable,
"phaseSpace" : "FullPS",
"truth" : {
"file" : "%s" % config.unfolding_central,
# "histogram": "%s/truth" % ( histogramTemplate ),
},
"gen_vs_reco" : {
"file" : "%s" % config.unfolding_central,
# "histogram": "%s/response_without_fakes" % ( histogramTemplate ),
muon_fit_variables = copy( common_fit_variables )
muon_fit_variables.append( 'muon_absolute_eta' )
fit_variable_properties = {
'M3': {'min':0, 'max':1000, 'rebin':5, 'x-title': 'M3 [GeV]', 'y-title': 'Events/25 GeV'},
'M_bl': {'min':0, 'max':400, 'rebin':2, 'x-title': 'M(b,l) [GeV]', 'y-title': 'Events/10 GeV'},
'angle_bl': {'min':0, 'max':3.5, 'rebin':2, 'x-title': 'angle(b,l)', 'y-title': 'Events/(0.2)'},
'electron_absolute_eta': {'min':0, 'max':2.6, 'rebin':2, 'x-title': '$\left|\eta(e)\\right|$', 'y-title': 'Events/(0.2)'},
'muon_absolute_eta': {'min':0, 'max':2.6, 'rebin':2, 'x-title': '$\left|\eta(\mu)\\right|$', 'y-title': 'Events/(0.2)'},
}
b_tag_bin = '2orMoreBtags'
b_tag_bin_ctl = '0orMoreBtag'
category = 'central'
variables = bin_edges.keys()
save_as = ['pdf']
def main():
global measurement_config, histogram_files
global electron_fit_variables, muon_fit_variables, fit_variable_properties
global b_tag_bin, category, histogram_files, variables
global b_tag_bin_ctl
title_template = '$%.1f$ fb$^{-1}$(%d TeV)'
e_title = title_template % ( measurement_config.new_luminosity / 1000., measurement_config.centre_of_mass_energy )
met_type = 'patType1CorrectedPFMet'
for variable in variables:
variable_bins = variable_bins_ROOT[variable]
histogram_template = get_histogram_template( variable )
def main():
'''
Step 1: Get the 2D histogram for every sample (channel and/or centre of mass energy)
Step 2: Change the size of the first bin until it fulfils the minimal criteria
Step 3: Check if it is true for all other histograms. If not back to step 2
Step 4: Repeat step 2 & 3 until no mo bins can be created
'''
parser = OptionParser()
parser.add_option( '-v', dest = "visiblePhaseSpace", action = "store_true",
help = "Consider visible phase space or not" )
parser.add_option( '-c', dest = "combined", action = "store_true",
help = "Combine channels" )
( options, _ ) = parser.parse_args()
p_min = 0.6
s_min = 0.6
# we also want the statistical error to be larger than 5%
# this translates (error -= 1/sqrt(N)) to (1/0.05)^2 = 400
n_min = 200
n_min_lepton = 500
# n_min = 200 # N = 200 -> 7.1 % stat error
bin_choices = {}
variables = bin_edges.keys()
for variable in variables:
print('--- Doing variable',variable)
variableToUse = variable
if 'Rap' in variable:
variableToUse = 'abs_%s' % variable
histogram_information = get_histograms( variableToUse, options )
if variable == 'HT':
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min, minimum_bin_width[variable], x_min=100. )
elif variable == 'ST':
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min, minimum_bin_width[variable], x_min=123. )
elif variable == 'NJets':
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min, minimum_bin_width[variable], x_min=3.5 )
elif variable == 'lepton_pt':
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min_lepton, minimum_bin_width[variable], x_min=23. )
elif variable == 'abs_lepton_eta':
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min_lepton, minimum_bin_width[variable] )
else:
best_binning, histogram_information = get_best_binning( histogram_information , p_min, s_min, n_min, minimum_bin_width[variable], )
if 'Rap' in variable:
for b in list(best_binning):
if b != 0.0:
best_binning.append(-1.0*b)
best_binning.sort()
# Make last bin smaller if huge
# Won't change final results
if len(best_binning) >= 4:
lastBinWidth = best_binning[-1] - best_binning[-2]
penultimateBinWidth = best_binning[-2] - best_binning[-3]
if lastBinWidth / penultimateBinWidth > 5:
newLastBinWidth = penultimateBinWidth * 5
best_binning[-1] = best_binning[-2] + newLastBinWidth
if variable == 'abs_lepton_eta':
best_binning = [ round(i,2) for i in best_binning ]
elif variable != 'NJets' :
best_binning = [ round(i) for i in best_binning ]
bin_choices[variable] = best_binning
print('The best binning for', variable, 'is:')
print('bin edges =', best_binning)
print('N_bins =', len( best_binning ) - 1)
print('The corresponding purities and stabilities are:')
for info in histogram_information:
# print_latex_table(info, variable, best_binning)
outputInfo = {}
outputInfo['p_i'] = info['p_i']
outputInfo['s_i'] = info['s_i']
outputInfo['N'] = info['N']
outputJsonFile = 'unfolding/13TeV/binningInfo_%s_%s_FullPS.txt' % ( variable, info['channel'] )
if options.visiblePhaseSpace:
outputJsonFile = 'unfolding/13TeV/binningInfo_%s_%s_VisiblePS.txt' % ( variable, info['channel'] )
write_data_to_JSON( outputInfo, outputJsonFile )
for key in outputInfo:
print (key,outputInfo[key])
print('-' * 120)
print('=' * 120)
print('For config/variable_binning.py')
print('=' * 120)
for variable in bin_choices:
print('\''+variable+'\' : '+str(bin_choices[variable])+',')
