def create_toy_mc(input_file, sample, output_folder, n_toy, centre_of_mass, ttbar_xsection):
from tools.file_utilities import make_folder_if_not_exists
from tools.toy_mc import generate_toy_MC_from_distribution, generate_toy_MC_from_2Ddistribution
from tools.Unfolding import get_unfold_histogram_tuple
make_folder_if_not_exists(output_folder)
input_file_hists = File(input_file)
output_file_name = get_output_file_name(output_folder, sample, n_toy, centre_of_mass)
variable_bins = bin_edges_vis.copy()
with root_open(output_file_name, 'recreate') as f_out:
for channel in ['combined']:
for variable in variable_bins:
output_dir = f_out.mkdir(channel + '/' + variable, recurse=True)
cd = output_dir.cd
mkdir = output_dir.mkdir
h_truth, h_measured, h_response, _ = get_unfold_histogram_tuple(input_file_hists,
variable,
channel,
centre_of_mass = centre_of_mass,
ttbar_xsection = ttbar_xsection,
visiblePS = True,
load_fakes=False)
cd()
mkdir('Original')
cd ('Original')
h_truth.Write('truth')
h_measured.Write('measured')
h_response.Write('response')
for i in range(1, n_toy+1):
toy_id = 'toy_{0}'.format(i)
mkdir(toy_id)
cd(toy_id)
# create histograms
# add tuples (truth, measured, response) of histograms
truth = generate_toy_MC_from_distribution(h_truth)
measured = generate_toy_MC_from_distribution(h_measured)
response = generate_toy_MC_from_2Ddistribution(h_response)
truth.SetName('truth')
measured.SetName('measured')
response.SetName('response')
truth.Write()
measured.Write()
response.Write()
def main():
set_root_defaults()
# prevent directory ownership of ROOT histograms (python does the garbage collection)
TH1F.AddDirectory( False )
parser = OptionParser()
parser.add_option( "-n", "--n_toy_mc",
dest = "n_toy_mc", default = 300,
help = "number of toy MC to create", type = int )
parser.add_option( "-o", "--output",
dest = "output_folder", default = 'data/toy_mc/',
help = "output folder for toy MC" )
parser.add_option( "-v", "--variable", dest = "variable", default = 'MET',
help = "set the variable to analyse (MET, HT, ST, MT, WPT)" )
parser.add_option( "-m", "--metType", dest = "metType", default = 'type1',
help = "set MET type for analysis of MET, ST or MT" )
parser.add_option( "-c", "--centre-of-mass-energy", dest = "CoM", default = 8,
help = "set the centre of mass energy for analysis. Default = 8 [TeV]", type = int )
parser.add_option( '-V', '--verbose', dest = "verbose", action = "store_true",
help = "Print the event number, reco and gen variable value" )
( options, _ ) = parser.parse_args()
measurement_config = XSectionConfig( options.CoM )
centre_of_mass = options.CoM
ttbar_xsection = measurement_config.ttbar_xsection
variable = options.variable
met_type = measurement_config.translate_options[options.metType]
n_toy_mc = options.n_toy_mc
make_folder_if_not_exists( options.output_folder )
# get histograms
input_file_hists = File( measurement_config.unfolding_madgraph )
# define output file
out_file_template = '%s/toy_mc_%s_N_%d_%dTeV.root'
out_file_name = out_file_template % (options.output_folder, variable, n_toy_mc, centre_of_mass)
output = File( out_file_name, 'recreate' )
for channel in ['electron', 'muon']:
# first get the weights
h_truth, h_measured, h_response, _ = get_unfold_histogram_tuple( input_file_hists,
variable,
channel,
met_type,
centre_of_mass,
ttbar_xsection,
load_fakes = False )
# create directories
directory = output.mkdir( channel )
mkdir = directory.mkdir
cd = directory.cd
cd()
# generate toy MC
for i in range( 1, n_toy_mc + 1 ):
mkdir( 'toy_%d' % i )
cd( 'toy_%d' % i )
# create histograms
# add tuples (truth, measured, response) of histograms
truth = generate_toy_MC_from_distribution(h_truth)
measured = generate_toy_MC_from_distribution(h_measured)
response = generate_toy_MC_from_2Ddistribution(h_response)
truth.SetName('truth')
measured.SetName('measured')
response.SetName('response')
truth.Write()
measured.Write()
response.Write()
output.Write()
output.Close()
