def create_fit_data( path, variables, fit_variables, mc_samples, COMEnergies, channels ):
'''
Creates the fit data in path + fit_check_data.txt in the JSON format.
The resulting dictionary is of the form
{centre-of-mass-energy: {
channel : {
variable : {
variable_bin : {
fit_variable : {
templates : { sample : []},
initial_values : { sample : []}
}
}
}
}
}
}
'''
# first step is to read the data
raw_data = {}
# the folder structure is
# path/fit_variable/centre-of-mass-energy/variable/fit_results/central/*
for fit_variable in fit_variables:
raw_data[fit_variable] = {}
for COMEnergy in COMEnergies:
raw_data[fit_variable][COMEnergy] = {}
for variable in variables:
raw_data[fit_variable][COMEnergy][variable] = {}
for channel in channels:
raw_data[fit_variable][COMEnergy][variable][channel] = {}
data_path = path + '/' + fit_variable + '/' + str( COMEnergy ) + 'TeV'
templates = read_fit_templates( data_path, variable,
channel = channel )
initial_values = read_initial_normalisation( data_path,
variable,
channel = channel )
raw_data[fit_variable][COMEnergy][variable][channel]['templates'] = templates
raw_data[fit_variable][COMEnergy][variable][channel]['initial_values'] = initial_values
# put it into the new structure
fit_data = {}
for COMEnergy in COMEnergies:
fit_data[COMEnergy] = {}
for channel in channels:
fit_data[COMEnergy][channel] = {}
for variable in variables:
fit_data[COMEnergy][channel][variable] = {}
for v_bin in variable_bins_ROOT[variable]:
fit_data[COMEnergy][channel][variable][v_bin] = {}
for fit_variable in fit_variables:
fit_data[COMEnergy][channel][variable][v_bin][fit_variable] = {}
fit_data[COMEnergy][channel][variable][v_bin][fit_variable]['templates'] = raw_data[fit_variable][COMEnergy][variable][channel]['templates']
fit_data[COMEnergy][channel][variable][v_bin][fit_variable]['initial_values'] = raw_data[fit_variable][COMEnergy][variable][channel]['initial_values']
write_data_to_JSON( fit_data, path + '/fit_check_data.txt', indent = False )
def create_fit_data(path, variables, fit_variables, mc_samples, COMEnergies,
channels):
'''
Creates the fit data in path + fit_check_data.txt in the JSON format.
The resulting dictionary is of the form
{centre-of-mass-energy: {
channel : {
variable : {
variable_bin : {
fit_variable : {
templates : { sample : []},
initial_values : { sample : []}
}
}
}
}
}
}
'''
# first step is to read the data
raw_data = {}
# the folder structure is
# path/fit_variable/centre-of-mass-energy/variable/fit_results/central/*
for fit_variable in fit_variables:
raw_data[fit_variable] = {}
for COMEnergy in COMEnergies:
raw_data[fit_variable][COMEnergy] = {}
for variable in variables:
raw_data[fit_variable][COMEnergy][variable] = {}
for channel in channels:
raw_data[fit_variable][COMEnergy][variable][channel] = {}
data_path = path + '/' + fit_variable + '/' + str(
COMEnergy) + 'TeV'
templates = read_fit_templates(data_path,
variable,
channel=channel)
initial_values = read_initial_normalisation(
data_path, variable, channel=channel)
raw_data[fit_variable][COMEnergy][variable][channel][
'templates'] = templates
raw_data[fit_variable][COMEnergy][variable][channel][
'initial_values'] = initial_values
# put it into the new structure
fit_data = {}
for COMEnergy in COMEnergies:
fit_data[COMEnergy] = {}
for channel in channels:
fit_data[COMEnergy][channel] = {}
for variable in variables:
fit_data[COMEnergy][channel][variable] = {}
for v_bin in variable_bins_ROOT[variable]:
fit_data[COMEnergy][channel][variable][v_bin] = {}
for fit_variable in fit_variables:
fit_data[COMEnergy][channel][variable][v_bin][
fit_variable] = {}
fit_data[COMEnergy][channel][variable][v_bin][
fit_variable]['templates'] = raw_data[
fit_variable][COMEnergy][variable][channel][
'templates']
fit_data[COMEnergy][channel][variable][v_bin][
fit_variable]['initial_values'] = raw_data[
fit_variable][COMEnergy][variable][channel][
'initial_values']
write_data_to_JSON(fit_data, path + '/fit_check_data.txt', indent=False)
variables = [ 'MET', 'HT', 'ST', 'WPT', 'MT' ]
for test in closure_tests:
if test != 'qcd_only' : continue;
for variable in variables:
fit_results_ = read_normalisation( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/',
variable,
'central',
'electron',
'patType1CorrectedPFMet' )
fit_templates_ = read_fit_templates( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/',
variable,
'central',
'electron',
'patType1CorrectedPFMet' )
initial_values_ = read_initial_normalisation( 'data/closure_test/'+test+'/absolute_eta_M3_angle_bl/8TeV/',
variable,
'central',
'electron',
'patType1CorrectedPFMet' )
for whichBin in range (0,len(fit_results_['TTJet'])):
for fitVariable in fit_variable_properties:
fitTemplates = fit_templates_[fitVariable]
histograms = {}
for template in fitTemplates: