#}}}
# 2018{{{
if "2018" in args.years:
for baby in babies_2018:
for little_baby in little_babies(baby):
command_list.append(
'./ttH%sLooper "%s" "RunII" "%s" "%s" "%s" "%s" "%s" "%s" "%s" "%s"'
% (args.channel, args.selection, args.tag, args.bdt,
args.bkg_options, little_baby, "2018", "_" + str(idx),
syst, args.l1_prefire))
idx += 1
#}}}
#}}}
print "------------------------------------------------------------"
nPar = 12
parallel_utils.submit_jobs(command_list, nPar)
print "------------------------------------------------------------"
# histograms, hadd, cleanup{{{
print "after parallel_utils.submit_jobs..."
if args.babymaker:
histos = glob.glob("MVABaby_ttH%s_%s_*.root" % (args.channel, args.tag))
else:
histos = glob.glob("%s_%s_histogramsRunII_*.root" %
(args.selection, args.tag))
good_histos = []
for hist in histos:
size = os.stat(hist).st_size * (1. / (1024))
if size >= 1.:
good_histos.append(hist)
print("good hist: %s, size (kb): %d" % (hist, os.stat(hist).st_size *
(1. / (1024))))
#parallel_utils.run('python plot_wrapper.py --input_file "../%s" --plot_type "std_2017" --plot_labels "FCNC Hadronic|Loose MVA Presel." --signals "TT_FCNC_hut|ST_FCNC_hut" --backgrounds "DiPhoton|QCD_GammaJets_imputed|TTGG|TTGJets|TTJets|VG"' % ("ttHHadronic_RunII_MVA_Presel_%s_histogramsRunII.root" % (args.tag + "_impute_hut_BDT_FCNC")))
#parallel_utils.run('python plot_wrapper.py --input_file "../%s" --plot_type "std_2017" --plot_labels "FCNC Hadronic|Loose MVA Presel." --signals "TT_FCNC_hct|ST_FCNC_hct" --backgrounds "DiPhoton|QCD_GammaJets_imputed|TTGG|TTGJets|TTJets|VG"' % ("ttHHadronic_RunII_MVA_Presel_%s_histogramsRunII.root" % (args.tag + "_impute_hct_BDT_FCNC")))
#os.chdir("../")
#}}}
>>>>>>> dd68e36d52dc32a9ea20698a1283183443a6d3e7
do_mvas = False
if do_mvas:
os.chdir("../MVAs/")
command_list = []
command_list.append('python prep.py --input "../Loopers/MVABaby_ttHLeptonic_%s_FCNC.root" --channel "Leptonic" --fcnc_hut --tag "_hut"' % (args.tag))
command_list.append('python prep.py --input "../Loopers/MVABaby_ttHHadronic_%s_FCNC.root" --channel "Hadronic" --fcnc_hut --tag "_hut"' % (args.tag + "_impute"))
command_list.append('python prep.py --input "../Loopers/MVABaby_ttHLeptonic_%s_FCNC.root" --channel "Leptonic" --fcnc_hct --tag "_hct"' % (args.tag))
command_list.append('python prep.py --input "../Loopers/MVABaby_ttHHadronic_%s_FCNC.root" --channel "Hadronic" --fcnc_hct --tag "_hct"' % (args.tag + "_impute"))
parallel_utils.submit_jobs(command_list, 4)
# MVA Training
parallel_utils.run('python train.py --input "ttHLeptonic_%s_FCNC_features_hut.hdf5" --channel "Leptonic" --tag "%s" --ext ""' % (args.tag, args.tag + "_hut"))
parallel_utils.run('python train.py --input "ttHHadronic_%s_FCNC_features_hut.hdf5" --channel "Hadronic" --tag "%s" --ext ""' % (args.tag + "_impute", args.tag + "_impute_hut"))
parallel_utils.run('python train.py --input "ttHLeptonic_%s_FCNC_features_hct.hdf5" --channel "Leptonic" --tag "%s" --ext ""' % (args.tag, args.tag + "_hct"))
parallel_utils.run('python train.py --input "ttHHadronic_%s_FCNC_features_hct.hdf5" --channel "Hadronic" --tag "%s" --ext ""' % (args.tag + "_impute", args.tag + "_impute_hct"))
do_dnns = False
if do_dnns:
os.chdir("../MVAs/")
command_list = []
#command_list.append('python prep_dnn.py --input "../Loopers/MVABaby_ttHLeptonic_%s_FCNC.root" --channel "Leptonic" --fcnc --z_score --signal "FCNC_hut" --backgrounds "ttH" --tag "hut_FCNC_vs_SMHiggs"' % (args.tag))
#command_list.append('python prep.py --input "../Loopers/MVABaby_ttHLeptonic_%s_FCNC.root" --channel "Leptonic" --fcnc_hut --FCNC_vs_SMHiggs --tag "_hut_FCNC_vs_SMHiggs"' % (args.tag))
command_list.append(
'python prep.py --input "../Loopers/MVABaby_ttHHadronic_%s_impute_FCNC.root" --channel "Hadronic" --signal "tt_fcnc_%s,st_fcnc_%s" --bkg "%s" --features "%s" --tag "addTopTaggers_%s"'
% (args.tag, coupling.lower(), coupling.lower(), non_resonant_bkg +
"," + sm_higgs, training_features_all, coupling.lower()))
# Add top taggers non-resonant
command_list.append(
'python prep.py --input "../Loopers/MVABaby_ttHHadronic_%s_impute_FCNC.root" --channel "Hadronic" --signal "tt_fcnc_%s,st_fcnc_%s" --bkg "%s" --features "%s" --tag "addTopTaggers_nonres_%s"'
% (args.tag, coupling.lower(), coupling.lower(), non_resonant_bkg,
training_features_all, coupling.lower()))
# Add top taggers sm higgs
command_list.append(
'python prep.py --input "../Loopers/MVABaby_ttHHadronic_%s_impute_FCNC.root" --channel "Hadronic" --signal "tt_fcnc_%s,st_fcnc_%s" --bkg "%s" --features "%s" --tag "addTopTaggers_smhiggs_%s"'
% (args.tag, coupling.lower(), coupling.lower(), sm_higgs,
training_features_all, coupling.lower()))
parallel_utils.submit_jobs(command_list, 6)
do_mvas = True
if do_mvas:
os.chdir("../MVAs/")
#os.system("source ~/ttH/MVAs/setup.sh")
command_list = []
for coupling in ["Hut", "Hct"]:
# Baseline
command_list.append(
'python train_bdt.py --input "ttHHadronic_%s_scale_diphoton_FCNC_features_baseline_%s.hdf5" --channel "Hadronic" --tag "baseline_%s_%s"'
% (args.tag, coupling.lower(), args.tag, coupling.lower()))
# Non-resonant
command_list.append(
nPar = 1
command_list = []
for dir in dirs:
if args.data_only:
if "DoubleEG" not in dir:
continue
if args.no_signal:
if "ttHJetToGG" in dir or "ttHToGG" in dir:
continue
files = glob.glob(dir + "/merged_ntuple*.root")
name = dir.split("/")[-1]
if not os.path.isdir(destination + name):
os.system("mkdir %s" % destination + name)
command = "addHistos %s %s %d %d" % (destination + name + "/merged_ntuple",
dir + "/merged_ntuple", len(files),
nPar)
print(command)
command_list.append(command)
#print("addHistos %s %s %d %d" % (destination + name + "/merged_ntuple", dir + "/merged_ntuple", len(files), nPar))
#os.system("addHistos %s %s %d %d" % (destination + name + "/merged_ntuple", dir + "/merged_ntuple", len(files), nPar))
parallel_utils.submit_jobs(command_list, 8, False)
#for dir in dirs:
# Delete intermediate files
#name = dir.split("/")[-1]
#os.system("rm %s" % destination + name + "/merged_ntuple_*.root")
import parallel_utils
scan_list = [
'./ttHHadronicLooper "ttHHadronic_data_sideband_0b_train" "2017" "" "" "binned_NJets"',
'./ttHHadronicLooper "ttHHadronic_data_sideband_0b_test" "2017" "" "" "binned_NJets"',
'./ttHHadronicLooper "ttHHadronic_data_sideband_phoID_train" "2017" "" "" "binned_NJets"',
'./ttHHadronicLooper "ttHHadronic_data_sideband_phoID_test" "2017" "" "" "binned_NJets"',
]
parallel_utils.submit_jobs(scan_list, 8)
print("[merge_skims.py] Merging skims from the following directories: ")
for dir in directories:
print(dir)
command_list = []
for dir in directories:
files = glob.glob(dir + "/*.root")
target_dir = dir.replace(args.input_dir, args.output_dir)
if not os.path.exists(target_dir):
os.system("mkdir %s" % target_dir)
file_size_map = {}
total_size = 0
for file in files:
size = get_size(file)
file_size_map[file] = size
total_size += size
file_map = split_files(files, file_size_map, args.target_size)
if args.debug > 0:
print(
"[merge_skims.py] Merging %d files of total size %.2f GB from directory %s into %d files in directory %s."
% (len(files), size, dir, len(file_map.keys()), target_dir))
command_list += merge_files(file_map, args.output_dir)
parallel_utils.submit_jobs(command_list, args.nCores)
import os, sys
import parallel_utils
from utils import *
command_list = []
labels = label_map.keys()
for label in labels:
command = "python prep_data.py --label %s > log_%s.txt" % (label, label)
command_list.append(command)
parallel_utils.submit_jobs(command_list, len(labels))
