return output
def postprocess(self, accumulator):
return accumulator
if __name__ == '__main__':
from Tools.config_helpers import redirector_ucsd
from Tools.nano_mapping import make_fileset
from processors.default_accumulators import desired_output
year = 2018
fileset = make_fileset(['Data'],
year,
redirector=redirector_ucsd,
small=False)
exe_args = {
'workers': 8,
'function_args': {
'flatten': False
},
"schema": NanoAODSchema,
"skipbadfiles": True,
}
exe = processor.futures_executor
output = processor.run_uproot_job(
fileset,
"Events",
for sample in fileset:
meta[sample] = meta_output[sample]
good_files = []
skipped_files = []
for rootfile in fileset[sample]:
if meta_output[rootfile]:
good_files.append(rootfile)
else:
skipped_files.append(rootfile)
meta[sample]['good_files'] = good_files
meta[sample]['n_good'] = len(good_files)
meta[sample]['bad_files'] = skipped_files
meta[sample]['n_bad'] = len(skipped_files)
meta[sample]['xsec'] = samples[sample]['xsec']
return meta
if __name__ == '__main__':
from Tools.config_helpers import redirector_ucsd, redirector_fnal
from Tools.nano_mapping import make_fileset, nano_mapping
fileset = make_fileset(['QCD'], redirector=redirector_ucsd, small=False)
meta = get_sample_meta(fileset)
import pandas as pd
df = pd.DataFrame(meta)
print(df.transpose())
import uproot
from Tools.helpers import get_samples
from Tools.config_helpers import redirector_ucsd, redirector_fnal
from Tools.nano_mapping import make_fileset, nano_mapping
samples = get_samples()
fileset = make_fileset(['QCD'],
samples,
redirector=redirector_ucsd,
small=False,
year='UL2018')
good = []
bad = []
for sample in list(fileset.keys()):
for f_in in fileset[sample]:
print(f_in)
try:
tree = uproot.open(f_in)["Events"]
good.append(f_in)
except OSError:
print("XRootD Error")
bad.append(f_in)
import uproot
from Tools.helpers import get_samples
from Tools.config_helpers import redirector_ucsd, redirector_fnal
from Tools.nano_mapping import make_fileset, nano_mapping
samples = get_samples(f_in='samples_QCD.yaml')
fileset = make_fileset(['QCD'], samples, redirector=redirector_ucsd, small=False)
print(fileset)
<<<<<<< HEAD
good = []
bad = []
#breakpoint()
for n in range(len(list(fileset.keys()))):
for f_in in fileset[list(fileset.keys())[n]]:
=======
fileset = make_fileset(['TTW'], samples, redirector=redirector_ucsd, small=False)
good = []
bad = []
for sample in list(fileset.keys()):
for f_in in fileset[sample]:
>>>>>>> 6987d93c61482b8369a70afe8a3071d806185974
print (f_in)
try:
tree = uproot.open(f_in)["Events"]
good.append(f_in)
# load the config and the cache
cfg = loadConfig()
cacheName = 'nano_analysis'
cache = dir_archive(os.path.join(os.path.expandvars(cfg['caches']['base']),
cacheName),
serialized=True)
histograms = sorted(list(desired_output.keys()))
year = 2018
samples = get_samples()
fileset = make_fileset(['QCD'],
samples,
redirector=redirector_ucsd,
small=True)
meta = get_sample_meta(fileset, samples)
add_processes_to_output(fileset, desired_output)
desired_output.update({
"single_mu_fakeable":
hist.Hist("Counts", dataset_axis, pt_axis, eta_axis),
"single_mu":
hist.Hist("Counts", dataset_axis, pt_axis, eta_axis)
})
exe_args = {
'workers': 16,
import uproot
from Tools.helpers import get_samples
from Tools.config_helpers import redirector_ucsd, redirector_fnal
from Tools.nano_mapping import make_fileset, nano_mapping
samples = get_samples()
fileset = make_fileset(['top'],
samples,
redirector=redirector_ucsd,
small=False)
good = []
bad = []
for f_in in fileset[list(fileset.keys())[0]]:
print(f_in)
try:
tree = uproot.open(f_in)["Events"]
good.append(f_in)
except OSError:
print("XRootD Error")
bad.append(f_in)
# load the config and the cache
cfg = loadConfig()
cacheName = 'charge_flip_calc'
cache = dir_archive(os.path.join(os.path.expandvars(cfg['caches']['base']),
cacheName),
serialized=True)
histograms = sorted(list(desired_output.keys()))
year = 2018
samples = get_samples()
fileset = make_fileset(['TTW', 'TTZ'],
samples,
redirector=redirector_ucsd,
small=True)
add_processes_to_output(fileset, desired_output)
if local:
exe_args = {
'workers': 16,
'function_args': {
'flatten': False
},
"schema": NanoAODSchema,
}
exe = processor.futures_executor
local = True
# load the config and the cache
cfg = loadConfig()
cacheName = 'charge_flip_check'
cache = dir_archive(os.path.join(os.path.expandvars(cfg['caches']['base']), cacheName), serialized=True)
histograms = sorted(list(desired_output.keys()))
year = 2018
samples = get_samples(2018)
#fileset = make_fileset(['TTW', 'TTZ'], samples, redirector=redirector_ucsd, small=True, n_max=5) # small, max 5 files per sample
#fileset = make_fileset(['DY'], samples, redirector=redirector_ucsd, small=True, n_max=10)
fileset = make_fileset(['top', 'DY',], redirector=redirector_ucsd, small=False)
add_processes_to_output(fileset, desired_output)
#meta = get_sample_meta(fileset, samples)
if local:
exe_args = {
'workers': 16,
'function_args': {'flatten': False},
'schema': NanoAODSchema,
'skipbadfiles': True,
}
exe = processor.futures_executor
cfg = loadConfig()
cacheName = 'nano_analysis'
cache = dir_archive(os.path.join(os.path.expandvars(cfg['caches']['base']),
cacheName),
serialized=True)
histograms = sorted(list(desired_output.keys()))
year = 2018
samples = get_samples()
#fileset = make_fileset(['TTW', 'TTZ'], samples, redirector=redirector_ucsd, small=True, n_max=5) # small, max 5 files per sample
#fileset = make_fileset(['DY'], samples, redirector=redirector_ucsd, small=True, n_max=10)
fileset = make_fileset(['top', 'DY', 'TTZ'],
samples,
redirector=redirector_fnal,
small=True)
add_processes_to_output(fileset, desired_output)
pt_axis_coarse = hist.Bin("pt", r"$p_{T}$ (GeV)",
[15, 40, 60, 80, 100, 200, 300])
eta_axis_coarse = hist.Bin("eta", r"$\eta$", [0, 0.8, 1.479, 2.5])
desired_output.update({
"gen_matched_electron":
hist.Hist("Counts", dataset_axis, pt_axis_coarse, eta_axis_coarse),
"flipped_electron":
hist.Hist("Counts", dataset_axis, pt_axis_coarse, eta_axis_coarse),
})
