def __init__(self, treeName, outputDir, executable_addMEM, samples, era, debug, running_method,
max_files_per_job, mem_integrations_per_job, max_mem_integrations, num_parallel_jobs):
self.treeName = treeName
self.outputDir = outputDir
self.executable_addMEM = executable_addMEM
self.channel = "2lss_1tau"
self.mem_integrations_per_job = mem_integrations_per_job
self.max_files_per_job = max_files_per_job
self.max_mem_integrations = max_mem_integrations
self.samples = samples
self.era = era
self.debug = debug
assert(running_method.lower() in [
"sbatch", "makefile"]), "Invalid running method: %s" % running_method
self.running_method = running_method
self.is_sbatch = False
self.is_makefile = False
if self.running_method.lower() == "sbatch":
self.is_sbatch = True
else:
self.is_makefile = True
self.makefile = os.path.join(
self.outputDir, "Makefile_%s" % self.channel)
self.num_parallel_jobs = num_parallel_jobs
self.workingDir = os.getcwd()
print "Working directory is: " + self.workingDir
create_if_not_exists(self.outputDir)
self.stdout_file = codecs.open(os.path.join(
self.outputDir, "stdout_%s.log" % self.channel), 'w', 'utf-8')
self.stderr_file = codecs.open(os.path.join(
self.outputDir, "stderr_%s.log" % self.channel), 'w', 'utf-8')
self.dirs = {}
self.samples = samples
self.cfgFile_addMEM_original = os.path.join(self.workingDir, "addMEM_2lss_1tau_cfg.py")
self.cfgFiles_addMEM_modified = {}
self.logFiles_addMEM = {}
self.sbatchFile_addMEM = os.path.join(
self.outputDir, "sbatch_addMEM_%s.py" % self.channel)
self.inputFiles = {}
self.outputFiles = {}
self.hadd_records = {}
self.filesToClean = []
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(sample_name)
for dir_type in [ DKEY_CFGS, DKEY_NTUPLES, DKEY_FINAL_NTUPLES, DKEY_LOGS, DKEY_HADD ]:
initDict(self.dirs, [ key_dir, dir_type ])
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, process_name)
self.cvmfs_error_log = {}
def get_scratch_dir(self):
scratch_dir = "/scratch/%s" % getpass.getuser()
if not os.path.exists(scratch_dir):
print "Directory '%s' does not yet exist, creating it !!" % scratch_dir
run_cmd(command_create_scratchDir)
scratch_dir = os.path.join(
scratch_dir,
"tthAnalysis" + "_" + date.today().isoformat()
)
create_if_not_exists(scratch_dir)
return scratch_dir
def get_scratch_dir(self):
scratch_dir = "/scratch/%s" % getpass.getuser()
if not os.path.exists(scratch_dir):
logging.info("Directory '%s' does not yet exist, creating it !!" %
scratch_dir)
run_cmd(command_create_scratchDir)
scratch_dir = os.path.join(
scratch_dir,
"%s_%s" % (self.analysisName, datetime.date.today().isoformat()),
)
create_if_not_exists(scratch_dir)
return scratch_dir
def create(self):
create_if_not_exists(self.hadd_log_dir_path)
if self.running_method.lower() == 'sbatch':
create_if_not_exists(self.hadd_script_dir_path)
createScript_sbatch_hadd(
sbatch_script_file_name=self.hadd_script_path,
input_file_names=list(self.channel_info.keys()),
output_file_name=self.final_output_file,
script_file_name=self.hadd_script_path.replace('.py', '.sh'),
log_file_name=self.
hadd_log_executable_path, # the basename will be replaced anyways?
working_dir=None,
waitForJobs=True,
auxDirName='',
pool_id=uuid.uuid4(),
verbose=False,
max_input_files_per_job=len(self.channel_info),
dry_run=self.dry_run,
use_home=self.use_home,
min_file_size=-1,
)
logging.info("Generated hadd config file: %s" %
self.hadd_script_path)
self.hadd_script_path = 'python %s' % self.hadd_script_path
additional_cmds = ''
else:
self.hadd_script_path = 'hadd -f {} {}'.format(
os.path.basename(self.final_output_file),
' '.join(list(self.channel_info.keys())))
additional_cmds = 'mv {} {}'.format(
os.path.basename(self.final_output_file),
self.final_output_file)
with open(self.makefile_path, 'w') as makefile:
hadd_script_cmd = '{}{}'.format(
'sleep 60\n\t' if self.running_method.lower() == 'makefile'
else '', self.hadd_script_path)
makeFileContents = jinja2.Template(makeFileTemplate).render(
output_file=self.final_output_file,
channel_info=self.channel_info,
hadd_script=hadd_script_cmd,
hadd_wrapper_log=self.hadd_log_wrapper_path,
additional_cmds=additional_cmds,
validate_channels=' '.join(self.channels_to_validate),
output_dir=self.output_dir,
)
makefile.write(makeFileContents)
logging.info("Created the makefile: %s" % self.makefile_path)
def create(self):
"""Creates all necessary config files and runs the Ntuple production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_prodNtuple, process_name))
inputFileList = generateInputFileList(sample_name, sample_info, self.max_files_per_job, self.debug)
for jobId in inputFileList.keys():
key_dir = getKey(sample_name)
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = inputFileList[jobId]
if len(self.inputFiles[key_file]) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (key_file, self.inputFiles[key_file])
continue
##print "sample = '%s', jobId = %i: number of input files = %i" % (sample_name, jobId, len(self.inputFiles[key_file]))
##print self.inputFiles[key_file]
assert(len(self.inputFiles[key_file]) == 1), "There is more than one input file!"
self.cfgFiles_prodNtuple_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "produceNtuple_%s_%s_%i_cfg.py" % \
(self.channel, process_name, jobId))
self.outputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_NTUPLES], "%s_%i.root" % \
(process_name, jobId))
self.logFiles_prodNtuple[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "produceNtuple_%s_%s_%i.log" % \
(self.channel, process_name, jobId))
self.createCfg_prodNtuple(self.inputFiles[key_file], self.outputFiles[key_file], self.era, self.cfgFiles_prodNtuple_modified[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_prodNtuple)
self.createScript_sbatch()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_prodNtuple(lines_makefile)
#self.addToMakefile_clean(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def run(self, clean):
record_software_state(self.sw_ver_file_cfg, self.sw_ver_file_out,
DEPENDENCIES)
target = 'all'
if clean:
if not os.path.isfile(self.makefile_path):
logging.error(
"The makefile %s is missing and therefore it's not possible to clean anything; "
"run sync Ntuple production first!" % self.makefile_path)
sys.exit(1)
target = 'clean'
nof_parallel_jobs = len(self.channel_info)
make_cmd = "make -f %s -j %d %s 2>%s 1>%s" % \
(self.makefile_path, nof_parallel_jobs, target, self.stderr_file_path, self.stdout_file_path)
if self.running_method.lower() == "makefile":
run_dir = re.sub('^/home', '/scratch', self.config_dir)
create_if_not_exists(run_dir)
make_cmd = re.sub('^make', 'make -C {}'.format(run_dir), make_cmd)
logging.info("Running the make command: %s" % make_cmd)
run_cmd(make_cmd)
logging.info("All done")
def create(self):
"""Creates all necessary config files and runs the Ntuple production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
if is_mc and process_name not in self.pileup_histograms:
raise ValueError("Missing PU distribution for %s in file %s" %
(process_name, self.pileup))
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable, process_name))
inputFileList = generateInputFileList(sample_info,
self.max_files_per_job)
key_dir = getKey(sample_name)
subDirs = list(
map(
lambda y: os.path.join(self.dirs[key_dir][DKEY_NTUPLES],
'%04d' % y),
set(map(lambda x: x // 1000, inputFileList.keys()))))
for subDir in subDirs:
create_if_not_exists(subDir)
for jobId in inputFileList.keys():
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = inputFileList[jobId]
if len(self.inputFiles[key_file]) == 0:
logging.warning(
"ntupleFiles['%s'] = %s --> skipping job !!" %
(key_file, self.inputFiles[key_file]))
continue
self.cfgFiles_prodNtuple_modified[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"produceNtuple_%s_%i_cfg.py" % (process_name, jobId))
self.outputFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_NTUPLES], "%04d" % (jobId // 1000),
"tree_%i.root" % jobId)
self.logFiles_prodNtuple[key_file] = os.path.join(
self.dirs[key_dir][DKEY_LOGS],
"produceNtuple_%s_%i.log" % (process_name, jobId))
hlt_paths = sample_info["hlt_paths"] if not is_mc else []
hlt_cuts = list(
Triggers(self.era).triggers_flat
) if self.preselection_cuts["applyHLTcut"] else []
jobOptions = {
'inputFiles': self.inputFiles[key_file],
'cfgFile_modified':
self.cfgFiles_prodNtuple_modified[key_file],
'outputFile': self.outputFiles[key_file],
'is_mc': is_mc,
'random_seed': jobId,
'process_name': process_name,
'category_name': sample_info["sample_category"],
'triggers': hlt_paths,
'HLTcuts': hlt_cuts,
}
self.createCfg_prodNtuple(jobOptions)
num_jobs = 0
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable)
num_jobs = self.createScript_sbatch()
logging.info("Generated %i job(s)" % num_jobs)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_prodNtuple(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
(secondary_files, primary_store,
secondary_store) = self.initializeInputFileIds(
sample_name, sample_info)
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info[
"xsection"] * self.lumi / sample_info["nof_events"]
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
for central_or_shift in self.central_or_shifts:
for jobId in range(len(self.inputFileIds[sample_name])):
if central_or_shift != "central" and not is_mc:
continue
inputFiles = generate_input_list(
self.inputFileIds[sample_name][jobId], secondary_files,
primary_store, secondary_store, self.debug)
key_dir = getKey(sample_name)
key_file = getKey(sample_name, central_or_shift, jobId)
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%i.root" % \
(process_name, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % \
(self.channel, process_name, central_or_shift, jobId))
self.createCfg_analyze(
inputFiles, self.histogramFiles[key_file],
sample_category, triggers, self.lepton_selection,
self.hadTau_selection, is_mc, central_or_shift,
lumi_scale, self.cfgFiles_analyze_modified[key_file])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.createScript_sbatch()
logging.info(
"Creating configuration files for executing 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
self.createCfg_prep_dcard(histogramToFit)
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_clean(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
for mode in self.modes:
key_dir = getKey(process_name, mode)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES, DKEY_SYNC ]:
if dir_type == DKEY_SYNC and not self.do_sync:
continue
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel, "_".join([ mode ]), process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, "_".join([ mode ]), process_name)
for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT, DKEY_SYNC ]:
if dir_type == DKEY_SYNC and not self.do_sync:
continue
initDict(self.dirs, [ dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type, self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)
##print "self.dirs = ", self.dirs
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" % sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)
for mode in self.modes:
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
for central_or_shift in self.central_or_shifts:
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
# build config files for executing analysis code
key_dir = getKey(process_name, mode)
key_analyze_job = getKey(process_name, mode, central_or_shift, jobId)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning("No input ntuples for %s --> skipping job !!" % (key_analyze_job))
continue
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, mode, central_or_shift, jobId)),
'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" % \
(process_name, mode, central_or_shift, jobId)),
'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, mode, central_or_shift, jobId)),
'sample_category' : sample_category,
'mode' : mode,
'lepton_selection' : self.lepton_selection,
'hadTau_selection' : self.hadTau_selection,
'SVfit4tau_logM_wMassConstraint_MarkovChain' : self.SVfit4tau_logM_wMassConstraint_MarkovChain,
'SVfit4tau_logM_woMassConstraint_MarkovChain' : self.SVfit4tau_logM_woMassConstraint_MarkovChain,
'SVfit4tau_logM_wMassConstraint_VAMP' : self.SVfit4tau_logM_wMassConstraint_VAMP,
'use_HIP_mitigation_mediumMuonId' : False,
'is_mc' : is_mc,
'central_or_shift' : central_or_shift,
'lumi_scale' : 1.,
'apply_genWeight' : sample_info["genWeight"] if (is_mc and "genWeight" in sample_info) else False,
}
self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job])
# initialize input and output file names for hadd_stage1
key_hadd_stage1 = getKey(process_name, mode)
if not key_hadd_stage1 in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s_%s.root" % \
(self.channel, process_name, mode))
# initialize input and output file names for hadd_stage2
key_hadd_stage2 = getKey()
if not key_hadd_stage2 in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2] = []
self.inputFiles_hadd_stage2[key_hadd_stage2].append(self.outputFile_hadd_stage1[key_hadd_stage1])
self.outputFile_hadd_stage2[key_hadd_stage2] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage2_%s.root" % \
(self.channel))
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(process_name)
for dir_type in [
DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES, DKEY_SYNC
]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT, DKEY_SYNC
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_info, self.max_files_per_job)
for apply_jetSmearing in self.apply_jetSmearing_options:
jetSmearingLabel = None
if apply_jetSmearing:
jetSmearingLabel = "jetSmearingEnabled"
else:
jetSmearingLabel = "jetSmearingDisabled"
for apply_metSmearing in self.apply_metSmearing_options:
metSmearingLabel = None
if apply_metSmearing:
metSmearingLabel = "metSmearingEnabled"
else:
metSmearingLabel = "metSmearingDisabled"
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
isSignal = True if process_name.find(
"signal") != -1 else False
logging.info(
"Creating configuration files to run '%s' for sample %s"
% (self.executable_analyze, process_name))
sample_category = sample_info["sample_category"]
inputFileList = inputFileLists[sample_name]
numJobsPerFile = None
if sample_info[
"process_name_specific"] == "signal_ggf_nonresonant_node_sm_hh_2b2v":
numJobsPerFile = 500
elif sample_info[
"process_name_specific"] == "signal_ggf_nonresonant_cHHH1_hh_2b2v":
numJobsPerFile = 100
elif sample_info[
"process_name_specific"] == "TTJets_DiLept":
numJobsPerFile = 50
elif sample_info[
"process_name_specific"] == "TTJets_DiLept_ext1":
numJobsPerFile = 50
elif sample_info["process_name_specific"] == "TTTo2L2Nu":
numJobsPerFile = 10
else:
raise ValueError("Invalid sample: %s" %
sample_info["process_name_specific"])
numJobs = numJobsPerFile * len(inputFileList.keys())
for jobId in range(1, numJobs + 1):
ntupleId = ((jobId - 1) / numJobsPerFile) + 1
maxSelEvents = 500
skipSelEvents = maxSelEvents * (
(jobId - 1) % numJobsPerFile)
# build config files for executing analysis code
key_dir = getKey(process_name)
key_analyze_job = getKey(process_name,
jetSmearingLabel,
metSmearingLabel, jobId)
ntupleFiles = inputFileList[ntupleId]
if len(ntupleFiles) == 0:
logging.warning(
"No input ntuples for %s --> skipping job !!" %
(key_analyze_job))
continue
cfgFile_modified_path = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"analyze_%s_%s_%s_%s_%i_cfg.py" %
(self.channel, process_name, jetSmearingLabel,
metSmearingLabel, jobId))
histogramFile_path = os.path.join(
self.dirs[key_dir][DKEY_HIST],
"analyze_%s_%s_%s_%s_%i.root" %
(self.channel, process_name, jetSmearingLabel,
metSmearingLabel, jobId))
logFile_path = os.path.join(
self.dirs[key_dir][DKEY_LOGS],
"analyze_%s_%s_%s_%s_%i.log" %
(self.channel, process_name, jetSmearingLabel,
metSmearingLabel, jobId))
rleOutputFile_path = os.path.join(self.dirs[key_dir][DKEY_RLES], "rle_%s_%s_%s_%s_%i.txt" % (self.channel, process_name, jetSmearingLabel, metSmearingLabel, jobId)) \
if self.select_rle_output else ""
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles': ntupleFiles,
'cfgFile_modified': cfgFile_modified_path,
'histogramFile': histogramFile_path,
'logFile': logFile_path,
'selEventsFileName_output': rleOutputFile_path,
'apply_jetSmearing': apply_jetSmearing,
'apply_metSmearing': apply_metSmearing,
'maxSelEvents': maxSelEvents,
'skipSelEvents': skipSelEvents
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job],
sample_info)
# initialize input and output file names for hadd_stage1
key_hadd_stage1 = getKey(process_name,
jetSmearingLabel,
metSmearingLabel)
if not key_hadd_stage1 in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(
self.jobOptions_analyze[key_analyze_job]
['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s_%s_%s.root" % \
(self.channel, process_name, jetSmearingLabel, metSmearingLabel))
# add output files of hadd_stage1 to list of input files for hadd_stage2
key_hadd_stage1 = getKey(process_name, jetSmearingLabel,
metSmearingLabel)
key_hadd_stage2 = getKey("")
if not key_hadd_stage2 in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2] = []
self.inputFiles_hadd_stage2[key_hadd_stage2].append(
self.outputFile_hadd_stage1[key_hadd_stage1])
self.outputFile_hadd_stage2[
key_hadd_stage2] = os.path.join(
self.dirs[DKEY_HIST],
"histograms_harvested_stage2_%s.root" %
self.channel)
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.targets.extend(self.outputFile_hadd_stage2.values())
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
( secondary_files, primary_store, secondary_store ) = self.initializeInputFileIds(sample_name, sample_info)
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"]
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (is_mc and self.era == "2016" and sample_info["reHLT"]) or not is_mc
for hadTau_selection in self.hadTau_selections:
for hadTau_frWeight in [ "enabled", "disabled" ]:
if hadTau_frWeight == "enabled" and not hadTau_selection.startswith("Fakeable"):
continue
hadTau_selection_and_frWeight = get_hadTau_selection_and_frWeight(hadTau_selection, hadTau_frWeight)
for hadTau_genMatch in self.hadTau_genMatches:
for hadTau_charge_selection in self.hadTau_charge_selections:
for central_or_shift in self.central_or_shifts:
for jobId in range(len(self.inputFileIds[sample_name])):
if hadTau_genMatch != "all" and not is_mc:
continue
if hadTau_genMatch == "all" and is_mc:
continue
if central_or_shift != "central" and not (hadTau_selection.startswith("Tight") and hadTau_charge_selection == "OS"):
continue
if central_or_shift != "central" and not is_mc:
continue
if hadTau_selection == "Fakeable_mcClosure" and not hadTau_frWeight == "enabled":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttH") and sample_category != "signal":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttW") and sample_category != "TTW":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttZ") and sample_category != "TTZ":
continue
sample_category_and_genMatch = sample_category + hadTau_genMatch
key_dir = getKey(sample_name, hadTau_selection, hadTau_frWeight, hadTau_charge_selection)
key_file = getKey(sample_name, hadTau_selection, hadTau_frWeight, hadTau_genMatch, hadTau_charge_selection, central_or_shift, jobId)
self.ntupleFiles[key_file] = generate_input_list(self.inputFileIds[sample_name][jobId], secondary_files, primary_store, secondary_store, self.debug)
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, hadTau_selection_and_frWeight, hadTau_genMatch, hadTau_charge_selection, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%s_%s_%i.root" % \
(process_name, hadTau_selection_and_frWeight, hadTau_genMatch, hadTau_charge_selection, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, hadTau_selection_and_frWeight, hadTau_genMatch, hadTau_charge_selection, central_or_shift, jobId))
self.createCfg_analyze(self.ntupleFiles[key_file], self.histogramFiles[key_file], sample_category, self.era, triggers,
hadTau_selection, hadTau_genMatch, self.apply_hadTauGenMatching, hadTau_frWeight, hadTau_charge_selection,
is_mc, central_or_shift, lumi_scale, apply_trigger_bits, self.cfgFiles_analyze_modified[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
logging.info("Creating configuration files for executing 'addBackgrounds'")
process_names = []
process_names.extend(self.nonfake_backgrounds)
process_names.extend([ "signal", "ttH_htt", "ttH_hww", "ttH_hzz" ])
# sum non-fake contributions for each MC sample separately
# input processes: TT2t0e0m0j, TT1t1e0m0j, TT1t0e1m0j", TT0t2e0m0j, TT0t1e1m0j, TT0t0e2m0j; TTW2t0e0m0j,...
# output processes: TT; ...
for process_name in process_names:
for hadTau_selection in self.hadTau_selections:
for hadTau_frWeight in self.hadTau_frWeights:
if hadTau_frWeight == "enabled" and not hadTau_selection.startswith("Fakeable"):
continue
hadTau_selection_and_frWeight = get_hadTau_selection_and_frWeight(hadTau_selection, hadTau_frWeight)
for hadTau_charge_selection in self.hadTau_charge_selections:
key = getKey(process_name, hadTau_selection, hadTau_frWeight, hadTau_charge_selection)
self.histogramFile_addBackgrounds[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgrounds_%s_%s_%s_%s.root" % \
(self.channel, process_name, hadTau_selection_and_frWeight, hadTau_charge_selection))
self.cfgFile_addBackgrounds_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgrounds_%s_%s_%s_%s_cfg.py" % \
(self.channel, process_name, hadTau_selection_and_frWeight, hadTau_charge_selection))
histogramDir = getHistogramDir(hadTau_selection, hadTau_frWeight, hadTau_charge_selection)
processes_input = [ "%s%s" % (process_name, genMatch) for genMatch in self.hadTau_genMatches_nonfakes ]
self.process_output_addBackgrounds[key] = process_name
self.createCfg_addBackgrounds(self.histogramFile_hadd_stage1, self.histogramFile_addBackgrounds[key], self.cfgFile_addBackgrounds_modified[key],
[ histogramDir ], processes_input, self.process_output_addBackgrounds[key])
# sum fake contributions for the total of all MC sample
# input processes: TT1t0e0m1j, TT0t1e0m1j, TT0t0e1m1j, TT0t0e0m2j; TTW1t0e0m1j,...
# output process: fakes_mc
for hadTau_selection in self.hadTau_selections:
for hadTau_frWeight in self.hadTau_frWeights:
if hadTau_frWeight == "enabled" and not hadTau_selection.startswith("Fakeable"):
continue
hadTau_selection_and_frWeight = get_hadTau_selection_and_frWeight(hadTau_selection, hadTau_frWeight)
for hadTau_charge_selection in self.hadTau_charge_selections:
key = getKey(hadTau_selection, hadTau_frWeight, hadTau_charge_selection)
self.histogramFile_addBackgrounds[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgrounds_%s_fakes_mc_%s_%s.root" % \
(self.channel, hadTau_selection_and_frWeight, hadTau_charge_selection))
self.cfgFile_addBackgrounds_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgrounds_%s_fakes_mc_%s_%s_cfg.py" % \
(self.channel, hadTau_selection_and_frWeight, hadTau_charge_selection))
histogramDir = getHistogramDir(hadTau_selection, hadTau_frWeight, hadTau_charge_selection)
processes_input = []
for process_name in self.nonfake_backgrounds:
for genMatch in self.hadTau_genMatches_fakes:
processes_input.append("%s%s" % (process_name, genMatch))
self.process_output_addBackgrounds[key] = "fakes_mc"
self.createCfg_addBackgrounds(self.histogramFile_hadd_stage1, self.histogramFile_addBackgrounds[key], self.cfgFile_addBackgrounds_modified[key],
[ histogramDir ], processes_input, self.process_output_addBackgrounds[key])
logging.info("Creating configuration files for executing 'addBackgroundFakes'")
for hadTau_charge_selection in self.hadTau_charge_selections:
key = getKey("fakes_data", charge_selection)
self.histogramFile_addFakes[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgroundJetToTauFakes_%s_%s.root" % \
(self.channel, hadTau_charge_selection))
self.cfgFile_addFakes_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgroundJetToTauFakes_%s_%s_cfg.py" % \
(self.channel, hadTau_charge_selection))
category_signal = "0l_2tau_%s_Tight" % hadTau_charge_selection
category_sideband = "0l_2tau_%s_Fakeable_wFakeRateWeights" % hadTau_charge_selection
self.createCfg_addFakes(self.histogramFile_hadd_stage1_5, self.histogramFile_addFakes[key], self.cfgFile_addFakes_modified[key],
category_signal, category_sideband)
logging.info("Creating configuration files for executing 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
self.createCfg_prep_dcard(histogramToFit)
logging.info("Creating configuration files for executing 'makePlots'")
self.createCfg_makePlots()
if "SS" in self.hadTau_charge_selections:
self.createCfg_makePlots(self.histogramDir_prep_dcard_SS, "SS")
if "Fakeable_mcClosure" in self.hadTau_selections:
self.createCfg_makePlots_mcClosure()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.addToMakefile_make_plots_mcClosure(lines_makefile)
self.addToMakefile_clean(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def __init__(self,
configDir,
outputDir,
executable_prodNtuple,
cfgFile_prodNtuple,
samples,
max_files_per_job,
era,
preselection_cuts,
leptonSelection,
hadTauSelection,
debug,
running_method,
version,
num_parallel_jobs,
pool_id=''):
self.configDir = configDir
self.outputDir = outputDir
self.executable_prodNtuple = executable_prodNtuple
self.max_num_jobs = 200000
self.samples = samples
self.max_files_per_job = max_files_per_job
self.era = era
self.preselection_cuts = preselection_cuts
self.leptonSelection = leptonSelection
self.hadTauSelection = hadTauSelection
self.debug = debug
assert (running_method.lower()
in ["sbatch",
"makefile"]), "Invalid running method: %s" % running_method
self.running_method = running_method
self.is_sbatch = False
self.is_makefile = False
if self.running_method.lower() == "sbatch":
self.is_sbatch = True
else:
self.is_makefile = True
self.makefile = os.path.join(self.configDir, "Makefile_prodNtuple")
self.num_parallel_jobs = num_parallel_jobs
self.pool_id = pool_id if pool_id else uuid.uuid4()
self.workingDir = os.getcwd()
print "Working directory is: " + self.workingDir
self.version = version
create_if_not_exists(self.configDir)
create_if_not_exists(self.outputDir)
self.stdout_file = codecs.open(
os.path.join(self.configDir, "stdout_prodNtuple.log"), 'w',
'utf-8')
self.stderr_file = codecs.open(
os.path.join(self.configDir, "stderr_prodNtuple.log"), 'w',
'utf-8')
self.dirs = {}
self.samples = samples
self.cfgFile_prodNtuple_original = os.path.join(
self.workingDir, cfgFile_prodNtuple)
self.cfgFiles_prodNtuple_modified = {}
self.logFiles_prodNtuple = {}
self.sbatchFile_prodNtuple = os.path.join(self.configDir,
"sbatch_prodNtuple.py")
self.inputFiles = {}
self.outputFiles = {}
self.filesToClean = []
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(sample_name)
for dir_type in [DKEY_CFGS, DKEY_NTUPLES, DKEY_LOGS]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, process_name)
for dir_type in [DKEY_CFGS, DKEY_LOGS]:
initDict(self.dirs, [dir_type])
if dir_type in [DKEY_CFGS, DKEY_NTUPLES, DKEY_LOGS]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type)
##print "self.dirs = ", self.dirs
self.cvmfs_error_log = {}
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
for charge_selection in self.charge_selections:
key_dir = getKey(process_name, charge_selection)
for dir_type in [DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel,
"_".join([charge_selection]), process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel,
"_".join([charge_selection]), process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
##print "self.dirs = ", self.dirs
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_name, sample_info, self.max_files_per_job, self.debug)
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info[
"xsection"] * self.lumi / sample_info["nof_events"]
apply_genWeight = sample_info["apply_genWeight"] if (
is_mc and "apply_genWeight" in sample_info.keys()) else False
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (
is_mc and
(self.era == "2015" or
(self.era == "2016" and sample_info["reHLT"]))) or not is_mc
for charge_selection in self.charge_selections:
for central_or_shift in self.central_or_shifts:
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttH"
) and sample_category != "signal":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttW"
) and sample_category != "TTW":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttZ"
) and sample_category != "TTZ":
continue
# build config files for executing analysis code
key_dir = getKey(process_name, charge_selection)
key_analyze_job = getKey(process_name,
charge_selection,
central_or_shift, jobId)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (
key_job, ntupleFiles)
continue
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, charge_selection, central_or_shift, jobId)),
'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" % \
(process_name, charge_selection, central_or_shift, jobId)),
'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, charge_selection, central_or_shift, jobId)),
'sample_category' : sample_category,
'triggers' : sample_info["triggers"],
'charge_selection' : charge_selection,
'jet_minPt' : self.jet_minPt,
'jet_maxPt' : self.jet_maxPt,
'jet_minAbsEta' : self.jet_minAbsEta,
'jet_maxAbsEta' : self.jet_maxAbsEta,
'hadTau_selection_denominator' : self.hadTau_selection_denominator,
'hadTau_selections_numerator' : self.hadTau_selections_numerator,
'absEtaBins' : self.absEtaBins,
##'use_HIP_mitigation_mediumMuonId' : sample_info["use_HIP_mitigation_mediumMuonId"],
'use_HIP_mitigation_mediumMuonId' : True,
'is_mc' : is_mc,
'central_or_shift' : central_or_shift,
'lumi_scale' : 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"],
'apply_genWeight' : sample_info["genWeight"] if (is_mc and "genWeight" in sample_info.keys()) else False,
'apply_trigger_bits' : (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc,
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job])
# initialize input and output file names for hadd_stage1
key_hadd_stage1 = getKey(process_name,
charge_selection)
if not key_hadd_stage1 in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(
self.jobOptions_analyze[key_analyze_job]
['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s_%s.root" % \
(self.channel, process_name, charge_selection))
# initialize input and output file names for hadd_stage2
key_hadd_stage1 = getKey(process_name, charge_selection)
key_hadd_stage2 = getKey(charge_selection)
if not key_hadd_stage2 in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2] = []
self.inputFiles_hadd_stage2[key_hadd_stage2].append(
self.outputFile_hadd_stage1[key_hadd_stage1])
self.outputFile_hadd_stage2[key_hadd_stage2] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage2_%s_%s.root" % \
(self.channel, charge_selection))
logging.info(
"Creating configuration files for executing 'comp_jetToTauFakeRate'"
)
for charge_selection in self.charge_selections:
key_comp_jetToTauFakeRate_job = getKey(charge_selection)
key_hadd_stage2 = getKey(charge_selection)
self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job] = {
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"comp_jetToTauFakeRate_%s_cfg.py" % charge_selection),
'outputFile':
os.path.join(
self.dirs[DKEY_HIST],
"comp_jetToTauFakeRate_%s.root" % charge_selection),
'logFile':
os.path.join(
self.dirs[DKEY_LOGS],
"comp_jetToTauFakeRate_%s.log" % charge_selection),
'looseRegion':
"jetToTauFakeRate_%s/denominator/" % charge_selection,
'tightRegion':
"jetToTauFakeRate_%s/numerator/" % charge_selection,
'absEtaBins':
self.absEtaBins,
'ptBins':
self.ptBins
}
self.createCfg_comp_jetToTauFakeRate(
self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job])
self.targets.append(self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job]['outputFile'])
logging.info("Creating configuration files to run 'makePlots'")
for charge_selection in self.charge_selections:
key_makePlots_job = getKey(charge_selection)
key_hadd_stage2 = getKey(charge_selection)
self.jobOptions_make_plots[key_makePlots_job] = {
'executable':
self.executable_make_plots,
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(self.dirs[DKEY_CFGS],
"makePlots_%s_cfg.py" % self.channel),
'outputFile':
os.path.join(self.dirs[DKEY_PLOT],
"makePlots_%s.png" % self.channel),
'histogramDir':
"jetToTauFakeRate_%s" % charge_selection,
'label':
None,
'make_plots_backgrounds': ["TT", "TTW", "TTZ", "EWK", "Rares"],
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
self.cfgFile_make_plots = self.cfgFile_make_plots_denominator
for absEtaBin in ["absEtaLt1_5", "absEta1_5to9_9"]:
key_makePlots_job = getKey(charge_selection, absEtaBin,
"denominator")
key_hadd_stage2 = getKey(charge_selection)
self.jobOptions_make_plots[key_makePlots_job] = {
'executable':
self.executable_make_plots,
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"makePlots_%s_%s_denominator_%s_cfg.py" %
(self.channel, charge_selection, absEtaBin)),
'outputFile':
os.path.join(
self.dirs[DKEY_PLOT],
"makePlots_%s_%s_denominator_%s.png" %
(self.channel, charge_selection, absEtaBin)),
'histogramDir':
"jetToTauFakeRate_%s/denominator/%s" %
(charge_selection, absEtaBin),
'label':
None,
'make_plots_backgrounds':
["TT", "TTW", "TTZ", "EWK", "Rares"],
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
for hadTau_selection_numerator in self.hadTau_selections_numerator:
key_makePlots_job = getKey(charge_selection, absEtaBin,
"numerator",
hadTau_selection_numerator)
key_hadd_stage2 = getKey(charge_selection)
self.jobOptions_make_plots[key_makePlots_job] = {
'executable':
self.executable_make_plots,
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"makePlots_%s_%s_numerator_%s_%s_cfg.py" %
(self.channel, charge_selection,
hadTau_selection_numerator, absEtaBin)),
'outputFile':
os.path.join(
self.dirs[DKEY_PLOT],
"makePlots_%s_%s_numerator_%s_%s.png" %
(self.channel, charge_selection,
hadTau_selection_numerator, absEtaBin)),
'histogramDir':
"jetToTauFakeRate_%s/numerator/%s/%s" %
(charge_selection, hadTau_selection_numerator,
absEtaBin),
'label':
None,
'make_plots_backgrounds':
["TT", "TTW", "TTZ", "EWK", "Rares"],
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_comp_jetToTauFakeRate)
self.sbatchFile_comp_jetToTauFakeRate = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_comp_jetToTauFakeRate.py")
self.createScript_sbatch(self.executable_comp_jetToTauFakeRate,
self.sbatchFile_comp_jetToTauFakeRate,
self.jobOptions_comp_jetToTauFakeRate)
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_comp_jetToTauFakeRate(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the PU profile production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info['use_it']:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
if not is_mc:
continue
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable, process_name))
inputFileList_map = generateInputFileList(sample_info, 1)
key_dir = getKey(process_name)
key_file = getKey(process_name)
self.inputFiles[key_file] = list(
itertools.chain(*inputFileList_map.values()))
if len(self.inputFiles[key_file]) == 0:
logging.warning("'%s' = %s --> skipping job !!" %
(key_file, self.inputFiles[key_file]))
continue
outputFile = os.path.join(self.dirs[key_dir][DKEY_RESULTS],
"%s.txt" % process_name)
self.outputFiles[key_file] = outputFile
if os.path.isfile(outputFile):
logging.info('File {} already exists --> skipping job'.format(
outputFile))
continue
self.cfgFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"refGenWeight_%s_cfg.txt" % (process_name))
self.logFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_LOGS],
"refGenWeight_%s.log" % (process_name))
self.scriptFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"refGenWeight_%s_cfg.sh" % (process_name))
self.plotFiles[key_file] = ' '.join([
os.path.join(self.dirs[key_dir][DKEY_PLOTS],
"refGenWeight_%s.%s" % (process_name, extension))
for extension in ['pdf', 'png']
])
self.jobOptions_sbatch[key_file] = {
'inputFiles':
self.inputFiles[key_file],
'cfgFile_path':
self.cfgFiles[key_file],
'cmdParams':
"-i {} -o {} -p {} -v".format(
self.cfgFiles[key_file],
self.outputFiles[key_file],
self.plotFiles[key_file],
),
'outputFile':
self.outputFiles[key_file],
'logFile':
self.logFiles[key_file],
'scriptFile':
self.scriptFiles[key_file],
}
self.createCfg(self.jobOptions_sbatch[key_file])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable)
self.num_jobs['refGenWeight'] += self.createScript_sbatch(
self.executable, self.sbatchFile, self.jobOptions_sbatch)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile(lines_makefile)
self.addToMakefile_final(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the MEM -- either locally or on the batch system
"""
statistics = {}
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
if not os.path.exists(sample_info['local_paths'][0]['path']):
logging.warning("Skipping sample {sample_name}".format(sample_name = sample_name))
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_addMEM, process_name))
inputFileList = generateInputFileList(sample_name, sample_info, self.max_files_per_job, self.debug)
# typically, the analysis ends here and starts looping b/c the smallest unit of work processes at least one file
# we need, however, to split the file into event ranges in such a way that each job performs
# mem_integrations_per_job MEM integrations
# so what we are going to do is to open each set of files in inputFileList, read the variable
# requestMEM_2lss_1tau and try to gather the event ranges such that each event range
# performs up to mem_integrations_per_job integrations per job
memEvtRangeDict = self.memJobList(inputFileList)
for jobId in memEvtRangeDict.keys():
key_dir = getKey(sample_name)
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = memEvtRangeDict[jobId]['input_fileset']
# there should always be a job
assert(self.inputFiles[key_file] > 0), "More than one input file: %s ?? !!" % \
', '.join(self.inputFiles[key_file])
#TODO: is this assertion really needed? in principle, no ...
assert(len(self.inputFiles[key_file]) == 1), "There is more than one input file!"
self.cfgFiles_addMEM_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "addMEM_%s_%s_%i_cfg.py" % \
(self.channel, process_name, jobId))
self.outputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_NTUPLES], "%s_%i.root" % \
(process_name, jobId))
self.logFiles_addMEM[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "addMEM_%s_%s_%i.log" % \
(self.channel, process_name, jobId))
self.createCfg_addMEM(
self.inputFiles[key_file],
memEvtRangeDict[jobId]['event_range'][0],
memEvtRangeDict[jobId]['event_range'][1],
self.outputFiles[key_file],
self.era,
self.cfgFiles_addMEM_modified[key_file],
)
# associate the output file with the fileset_id
fileset_id = memEvtRangeDict[jobId]['fileset_id']
hadd_output = os.path.join(
self.dirs[key_dir][DKEY_FINAL_NTUPLES], '%s_%i.root' % ('tree', fileset_id)
)
if hadd_output not in self.hadd_records:
self.hadd_records[hadd_output] = {}
self.hadd_records[hadd_output]['output_files'] = []
self.hadd_records[hadd_output]['fileset_id'] = fileset_id
self.hadd_records[hadd_output]['output_files'].append(self.outputFiles[key_file])
#self.filesToClean.append(self.outputFiles[key_file])
# let's sum the number of integration per sample
nofEntriesMap = {}
for v in memEvtRangeDict.values():
if v['fileset_id'] not in nofEntriesMap:
nofEntriesMap[v['fileset_id']] = v['nof_entries']
statistics[process_name] = {
'nof_int' : sum([entry['nof_int'] for entry in memEvtRangeDict.values()]),
'nof_entries' : sum(nofEntriesMap.values()),
'nof_jobs' : len(memEvtRangeDict),
'nof_events_pass' : sum([entry['nof_events_pass'] for entry in memEvtRangeDict.values()]),
'nof_int_pass' : sum([entry['nof_int_pass'] for entry in memEvtRangeDict.values()]),
}
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_addMEM)
self.createScript_sbatch()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_addMEM(lines_makefile)
self.addToMakefile_hadd(lines_makefile)
self.createMakefile(lines_makefile)
ws_len = max([len(kk) + 1 for kk in statistics.keys()])
total_nof_integrations_sum = sum(x['nof_int'] for x in statistics.values())
total_nof_entires = sum(x['nof_entries'] for x in statistics.values())
total_nof_integrations_avg = float(total_nof_integrations_sum) / total_nof_entires
total_nof_jobs = sum(x['nof_jobs'] for x in statistics.values())
total_nof_pass = sum(x['nof_events_pass'] for x in statistics.values())
total_nof_int_pass_avg = float(sum(x['nof_int_pass'] for x in statistics.values())) / total_nof_pass
for k, v in statistics.iteritems():
print('%s%s: %d (%d entries; %d jobs; %.2f int/evt; %d (%.2f%%) evt pass; %.2f int/evt pass)' %
(k, ' ' * (ws_len - len(k)), v['nof_int'], v['nof_entries'], v['nof_jobs'],
float(v['nof_int']) / v['nof_entries'], v['nof_events_pass'],
(100 * float(v['nof_events_pass']) / v['nof_entries']), float(v['nof_int_pass']) / v['nof_events_pass']))
print('%s%s: %d (%d entries; %d jobs; %.2f int/evt; %d evt pass; %.2f int/evt pass)' %
('total', ' ' * (ws_len - len('total')), total_nof_integrations_sum, total_nof_entires, total_nof_jobs,
total_nof_integrations_avg, total_nof_pass, total_nof_int_pass_avg))
if total_nof_integrations_sum > self.max_mem_integrations:
logging.error("Will not start the jobs (max nof integrations exceeded)!")
return False
else:
logging.info("Done")
return True
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
logging.info("Building dictionaries for sample %s..." % process_name)
for lepton_selection in self.lepton_selections:
central_or_shift_extensions = ["", "hadd", "addBackgrounds"]
central_or_shifts_extended = central_or_shift_extensions + self.central_or_shifts
for central_or_shift_or_dummy in central_or_shifts_extended:
process_name_extended = [ process_name, "hadd" ]
for process_name_or_dummy in process_name_extended:
if central_or_shift_or_dummy in [ "hadd", "addBackgrounds" ] and process_name_or_dummy in [ "hadd" ]:
continue
if central_or_shift_or_dummy != "central" and central_or_shift_or_dummy not in central_or_shift_extensions:
if not is_mc:
continue
if not self.accept_central_or_shift(central_or_shift_or_dummy, sample_info):
continue
key_dir = getKey(process_name_or_dummy, lepton_selection, central_or_shift_or_dummy)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES ]:
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel,
"_".join([ lepton_selection ]), process_name_or_dummy, central_or_shift_or_dummy)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,
"_".join([ lepton_selection ]), process_name_or_dummy)
for subdirectory in [ "prepareDatacards" ]:
key_dir = getKey(subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel, subdirectory)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT, DKEY_COMBINE_OUTPUT ]:
initDict(self.dirs, [ dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT, DKEY_COMBINE_OUTPUT ]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type, self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" % numDirectories)
numDirectories_created = 0;
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100*numDirectories_created >= frac*numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" % sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)
for lepton_selection in self.lepton_selections:
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
inputFileList = inputFileLists[sample_name]
for central_or_shift in self.central_or_shifts:
if central_or_shift != "central" and not is_mc:
continue
# build config files for executing analysis code
key_analyze_dir = getKey(process_name, lepton_selection, central_or_shift)
for jobId in inputFileList.keys():
analyze_job_tuple = (process_name, lepton_selection, central_or_shift, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning("No input ntuples for %s --> skipping job !!" % (key_analyze_job))
continue
cfgFile_modified_path = os.path.join(self.dirs[key_analyze_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % analyze_job_tuple)
rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], "rle_%s_%s_%s_%i.txt" % analyze_job_tuple) \
if self.select_rle_output else ""
histogramFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_HIST], "analyze_%s_%s_%s_%i.root" % analyze_job_tuple)
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : cfgFile_modified_path,
'histogramFile' : histogramFile_path,
'logFile' : logFile_path,
'selEventsFileName_output' : rleOutputFile_path,
'leptonSelection' : lepton_selection,
'applyFakeRateWeights' : "disabled",
'central_or_shift' : central_or_shift,
}
self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job], sample_info)
# initialize input and output file names for hadd_stage1
key_hadd_stage1_dir = getKey(process_name, lepton_selection)
hadd_stage1_job_tuple = (process_name, lepton_selection)
key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)
if not key_hadd_stage1_job in self.inputFiles_hadd_stage1.keys():
self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []
self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1_job] = os.path.join(self.dirs[key_hadd_stage1_dir][DKEY_HIST],
"hadd_stage1_%s_%s.root" % hadd_stage1_job_tuple)
# initialize input and output file names for hadd_stage2
key_hadd_stage1_job = getKey(process_name, lepton_selection)
key_hadd_stage2_dir = getKey("hadd", lepton_selection)
key_hadd_stage2_job = getKey(lepton_selection)
if not key_hadd_stage2_job in self.inputFiles_hadd_stage2.keys():
self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.outputFile_hadd_stage1[key_hadd_stage1_job])
self.outputFile_hadd_stage2[key_hadd_stage2_job] = os.path.join(self.dirs[key_hadd_stage2_dir][DKEY_HIST],
"hadd_stage2_%s.root" % lepton_selection)
logging.info("Creating configuration files to run 'prepareDatacards'")
processesToCopy = []
for process in self.prep_dcard_processesToCopy:
processesToCopy.append(process)
self.prep_dcard_processesToCopy = processesToCopy
processesToCopy = []
for process in self.prep_dcard_signals:
processesToCopy.append(process)
self.prep_dcard_signals = processesToCopy
for histogramToFit in self.histograms_to_fit:
key_hadd_stage2_job = getKey("Tight")
key_prep_dcard_dir = getKey("prepareDatacards")
prep_dcard_job_tuple = (self.channel, histogramToFit)
key_prep_dcard_job = getKey(histogramToFit)
datacardFile = os.path.join(self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_%s_%s.root" % prep_dcard_job_tuple)
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_CFGS], "prepareDatacards_%s_%s_cfg.py" % prep_dcard_job_tuple),
'datacardFile' : datacardFile,
'histogramDir' : self.histogramDir_prep_dcard,
'histogramToFit' : histogramToFit,
'label' : None
}
self.createCfg_prep_dcard(self.jobOptions_prep_dcard[key_prep_dcard_job])
jobOptions_makefile = copy.deepcopy(self.jobOptions_postFit)
jobOptions_makefile['fit_result'] = os.path.join(
self.dirs[DKEY_COMBINE_OUTPUT], 'fit_{}'.format(histogramToFit), jobOptions_makefile['target']
)
jobOptions_makefile['hadd_stage2'] = self.outputFile_hadd_stage2[key_hadd_stage2_job]
jobOptions_makefile['prepare_datacard'] = datacardFile
jobOptions_makefile['data_datacard'] = os.path.join(
self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_data_%s_%s.root" % prep_dcard_job_tuple
)
jobOptions_makefile['pseudodata_datacard'] = os.path.join(
self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_pseudodata_%s_%s.root" % prep_dcard_job_tuple
)
jobOptions_makefile['makefile'] = os.path.join(
self.dirs[DKEY_COMBINE_OUTPUT], 'Makefile_{}'.format(histogramToFit)
)
jobOptions_makefile['stdout'] = os.path.join(
self.dirs[DKEY_COMBINE_OUTPUT], 'stdout_{}.log'.format(histogramToFit)
)
self.createCfg_postFit(jobOptions_makefile)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile, make_dependency = "phony_hadd_stage1")
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_postFit(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"]
apply_genWeight = sample_info["apply_genWeight"] if (is_mc and "apply_genWeight" in sample_info.keys()) else False
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc
for lepton_and_hadTau_selection in self.lepton_and_hadTau_selections:
lepton_selection = lepton_and_hadTau_selection
hadTau_selection = lepton_and_hadTau_selection
if self.applyFakeRateWeights == "2lepton":
hadTau_selection = "Tight"
hadTau_selection = "|".join([ hadTau_selection, self.hadTau_selection_part2 ])
for lepton_and_hadTau_frWeight in self.lepton_and_hadTau_frWeights:
if lepton_and_hadTau_frWeight == "enabled" and not lepton_and_hadTau_selection.startswith("Fakeable"):
continue
if lepton_and_hadTau_selection == "Fakeable_mcClosure" and not lepton_and_hadTau_frWeight == "enabled":
continue
lepton_and_hadTau_selection_and_frWeight = get_lepton_and_hadTau_selection_and_frWeight(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight)
for lepton_charge_selection in self.lepton_charge_selections:
for central_or_shift in self.central_or_shifts:
inputFileList = generateInputFileList(sample_name, sample_info, self.max_files_per_job, self.debug)
for jobId in inputFileList.keys():
if central_or_shift != "central" and not (lepton_and_hadTau_selection.startswith("Tight") and lepton_charge_selection == "SS"):
continue
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttH") and sample_category != "signal":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttW") and sample_category != "TTW":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttZ") and sample_category != "TTZ":
continue
key_dir = getKey(sample_name, lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
key_file = getKey(sample_name, lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection, central_or_shift, jobId)
self.ntupleFiles[key_file] = inputFileList[jobId]
if len(self.ntupleFiles[key_file]) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (key_file, self.ntupleFiles[key_file])
continue
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%s_%i.root" % \
(process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection, central_or_shift, jobId))
self.rleOutputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_RLES], "rle_%s_%s_%s_%s_%s_%i.txt" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection, central_or_shift, jobId)) if self.select_rle_output else ""
applyFakeRateWeights = self.applyFakeRateWeights
if lepton_and_hadTau_frWeight == "disabled":
applyFakeRateWeights = "disabled"
self.createCfg_analyze(self.ntupleFiles[key_file], self.histogramFiles[key_file], sample_category, self.era, triggers,
lepton_selection, self.apply_leptonGenMatching, lepton_charge_selection, hadTau_selection, self.apply_hadTauGenMatching,
applyFakeRateWeights, is_mc, central_or_shift, lumi_scale, apply_genWeight, apply_trigger_bits, self.cfgFiles_analyze_modified[key_file],
self.rleOutputFiles[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
for key in self.histogramFiles.keys():
self.inputFiles_hadd_stage1.append(self.histogramFiles[key])
logging.info("Creating configuration files for executing 'addBackgrounds'")
process_names = []
process_names.extend(self.nonfake_backgrounds)
process_names.extend([ "signal", "ttH_htt", "ttH_hww", "ttH_hzz" ])
# sum non-fake contributions for each MC sample separately
# input processes: TT2l0j,...
# output processes: TT; ...
for process_name in process_names:
for lepton_and_hadTau_selection in self.lepton_and_hadTau_selections:
for lepton_and_hadTau_frWeight in self.lepton_and_hadTau_frWeights:
if lepton_and_hadTau_frWeight == "enabled" and not lepton_and_hadTau_selection.startswith("Fakeable"):
continue
if lepton_and_hadTau_selection == "Fakeable_mcClosure" and not lepton_and_hadTau_frWeight == "enabled":
continue
lepton_and_hadTau_selection_and_frWeight = get_lepton_and_hadTau_selection_and_frWeight(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight)
for lepton_charge_selection in self.lepton_charge_selections:
key = getKey(process_name, lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
self.histogramFile_addBackgrounds[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgrounds_%s_%s_%s_%s.root" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
self.cfgFile_addBackgrounds_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgrounds_%s_%s_%s_%s_cfg.py" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
histogramDir = getHistogramDir(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
processes_input = [ "%s%s" % (process_name, genMatch) for genMatch in self.lepton_and_hadTau_genMatches_nonfakes ]
# CV: treat fakes in ttH signal events as "signal", not as "background"
##if process_name in [ "signal", "ttH_htt", "ttH_hww", "ttH_hzz" ]:
## processes_input.extend([ "%s%s" % (process_name, genMatch) for genMatch in self.lepton_and_hadTau_genMatches_fakes ])
self.process_output_addBackgrounds[key] = process_name
self.createCfg_addBackgrounds(self.histogramFile_hadd_stage1, self.histogramFile_addBackgrounds[key], self.cfgFile_addBackgrounds_modified[key],
[ histogramDir ], processes_input, self.process_output_addBackgrounds[key])
# sum fake contributions for each MC sample separately
# input processes: TT1l1j,TT0l2j,...
# output processes: fakes_TT; ...
for process_name in process_names:
for lepton_and_hadTau_selection in self.lepton_and_hadTau_selections:
for lepton_and_hadTau_frWeight in self.lepton_and_hadTau_frWeights:
if lepton_and_hadTau_frWeight == "enabled" and not lepton_and_hadTau_selection.startswith("Fakeable"):
continue
if lepton_and_hadTau_selection == "Fakeable_mcClosure" and not lepton_and_hadTau_frWeight == "enabled":
continue
lepton_and_hadTau_selection_and_frWeight = get_lepton_and_hadTau_selection_and_frWeight(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight)
for lepton_charge_selection in self.lepton_charge_selections:
key = getKey("fakes_%s" % process_name, lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
self.histogramFile_addBackgrounds[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgrounds_%s_fakes_%s_%s_%s.root" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
self.cfgFile_addBackgrounds_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgrounds_%s_fakes_%s_%s_%s_cfg.py" % \
(self.channel, process_name, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
histogramDir = getHistogramDir(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
processes_input = [ "%s%s" % (process_name, genMatch) for genMatch in self.lepton_and_hadTau_genMatches_fakes ]
self.process_output_addBackgrounds[key] = "fakes_%s" % process_name
self.createCfg_addBackgrounds(self.histogramFile_hadd_stage1, self.histogramFile_addBackgrounds[key], self.cfgFile_addBackgrounds_modified[key],
[ histogramDir ], processes_input, self.process_output_addBackgrounds[key])
# sum fake contributions for the total of all MC samples
# input processes: TT1l1j,TT0l2j,...
# output process: fakes_mc
for lepton_and_hadTau_selection in self.lepton_and_hadTau_selections:
for lepton_and_hadTau_frWeight in self.lepton_and_hadTau_frWeights:
if lepton_and_hadTau_frWeight == "enabled" and not lepton_and_hadTau_selection.startswith("Fakeable"):
continue
if lepton_and_hadTau_selection == "Fakeable_mcClosure" and not lepton_and_hadTau_frWeight == "enabled":
continue
lepton_and_hadTau_selection_and_frWeight = get_lepton_and_hadTau_selection_and_frWeight(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight)
for lepton_charge_selection in self.lepton_charge_selections:
key = getKey(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
self.histogramFile_addBackgrounds[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgrounds_%s_fakes_mc_%s_%s.root" % \
(self.channel, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
self.cfgFile_addBackgrounds_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgrounds_%s_fakes_mc_%s_%s_cfg.py" % \
(self.channel, lepton_and_hadTau_selection_and_frWeight, lepton_charge_selection))
histogramDir = getHistogramDir(lepton_and_hadTau_selection, lepton_and_hadTau_frWeight, lepton_charge_selection)
processes_input = []
for process_name in self.nonfake_backgrounds:
for genMatch in self.lepton_and_hadTau_genMatches_fakes:
processes_input.append("%s%s" % (process_name, genMatch))
self.process_output_addBackgrounds[key] = "fakes_mc"
self.createCfg_addBackgrounds(self.histogramFile_hadd_stage1, self.histogramFile_addBackgrounds[key], self.cfgFile_addBackgrounds_modified[key],
[ histogramDir ], processes_input, self.process_output_addBackgrounds[key])
logging.info("Creating configuration files for executing 'addBackgroundLeptonFakes'")
for lepton_charge_selection in self.lepton_charge_selections:
key = getKey("fakes_data", lepton_charge_selection)
self.histogramFile_addFakes[key] = os.path.join(self.outputDir, DKEY_HIST, "addBackgroundLeptonFakes_%s_%s.root" % \
(self.channel, lepton_charge_selection))
self.cfgFile_addFakes_modified[key] = os.path.join(self.outputDir, DKEY_CFGS, "addBackgroundLeptonFakes_%s_%s_cfg.py" % \
(self.channel, lepton_charge_selection))
category_signal = "2lss_1tau_%s_Tight" % lepton_charge_selection
category_sideband = "2lss_1tau_%s_Fakeable_wFakeRateWeights" % lepton_charge_selection
self.createCfg_addFakes(self.histogramFile_hadd_stage1_5, self.histogramFile_addFakes[key], self.cfgFile_addFakes_modified[key],
category_signal, category_sideband)
logging.info("Creating configuration files for executing 'addBackgroundLeptonFlips'")
self.createCfg_addFlips(self.histogramFile_hadd_stage1_5, self.histogramFile_addFlips, self.cfgFile_addFlips_modified)
logging.info("Creating configuration files for executing 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
self.createCfg_prep_dcard(histogramToFit)
logging.info("Creating configuration files for executing 'makePlots'")
self.createCfg_makePlots()
if "OS" in self.lepton_charge_selections:
make_plots_backgrounds = self.make_plots_backgrounds
if "flips_data" in make_plots_backgrounds:
make_plots_backgrounds.remove("flips_data")
self.createCfg_makePlots(self.histogramDir_prep_dcard_OS, "OS", make_plots_backgrounds)
if "Fakeable_mcClosure" in self.lepton_and_hadTau_selections:
self.createCfg_makePlots_mcClosure()
self.inputFiles_hadd_stage2 = [ self.histogramFile_hadd_stage1_5 ] + self.histogramFile_addFakes.values() + [ self.histogramFile_addFlips ]
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.addToMakefile_make_plots_mcClosure(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
central_or_shifts_extended = [""]
central_or_shifts_extended.extend(self.central_or_shifts)
central_or_shifts_extended.extend(
["hadd", "copyHistograms", "addBackgrounds"])
for central_or_shift_or_dummy in central_or_shifts_extended:
process_name_extended = [process_name, "hadd"]
for process_name_or_dummy in process_name_extended:
if process_name_or_dummy in [
"hadd"
] and central_or_shift_or_dummy != "":
continue
if central_or_shift_or_dummy in [
"hadd", "copyHistograms", "addBackgrounds"
] and process_name_or_dummy in ["hadd"]:
continue
key_dir = getKey(process_name_or_dummy,
central_or_shift_or_dummy)
for dir_type in [
DKEY_CFGS, DKEY_LOGS, DKEY_RLES, DKEY_SYNC
]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel,
process_name_or_dummy,
central_or_shift_or_dummy)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel,
process_name_or_dummy,
central_or_shift_or_dummy)
for subdirectory in [
"addBackgrounds", "addBackgroundLeptonFakes",
"prepareDatacards", "addSystFakeRates", "makePlots"
]:
key_dir = getKey(subdirectory)
for dir_type in [
DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_ROOT, DKEY_DCRD,
DKEY_PLOT
]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, subdirectory)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, subdirectory)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_SYNC, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_HADD_RT]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" %
numDirectories)
numDirectories_created = 0
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100 * numDirectories_created >= frac * numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_info, self.max_files_per_job)
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
for central_or_shift in self.central_or_shifts:
logging.info(" ... for systematic uncertainty %s" %
central_or_shift)
key_analyze_dir = getKey(process_name, central_or_shift)
analyze_job_tuple = (process_name, central_or_shift, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
print("Warning: no ntupleFiles --> skipping job !!")
continue
syncOutput = os.path.join(
self.dirs[key_analyze_dir][DKEY_SYNC],
'%s_%s.root' % (self.channel, central_or_shift))
syncOutputTree = self.output_tree if central_or_shift == "central" else os.path.join(
central_or_shift, self.output_tree)
self.inputFiles_sync['sync'].append(syncOutput)
cfgFile_modified_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_CFGS],
"analyze_%s_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_LOGS],
"analyze_%s_%s_%i.log" % analyze_job_tuple)
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles':
ntupleFiles,
'cfgFile_modified':
cfgFile_modified_path,
'histogramFile':
'',
'logFile':
logFile_path,
'syncTree':
syncOutputTree,
'syncOutput':
syncOutput,
'syncRLE':
self.rle_select if self.rle_select
and '%s' not in self.rle_select else '',
'useNonNominal':
self.use_nonnominal,
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job], sample_info)
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_syncNtuple(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_syncNtuple(lines_makefile)
outputFile_sync_path = os.path.join(self.outputDir, DKEY_SYNC,
'%s.root' % self.channel)
self.outputFile_sync['sync'] = outputFile_sync_path
self.addToMakefile_hadd_sync(lines_makefile)
self.targets.extend(self.phoniesToAdd)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the PU profile production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info['use_it']:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
if not is_mc:
continue
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable, process_name))
inputFileList = generateInputFileList(sample_info,
self.max_files_per_job)
key_dir = getKey(process_name)
outputFile = os.path.join(self.dirs[key_dir][DKEY_HISTO],
"%s.root" % process_name)
self.outputFiles[process_name] = {
'inputFiles': [],
'outputFile': outputFile,
}
if os.path.isfile(outputFile) and tools_is_file_ok(
outputFile, min_file_size=2000):
logging.info('File {} already exists --> skipping job'.format(
outputFile))
continue
for jobId in inputFileList.keys():
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = inputFileList[jobId]
if len(self.inputFiles[key_file]) == 0:
logging.warning("'%s' = %s --> skipping job !!" %
(key_file, self.inputFiles[key_file]))
continue
self.cfgFiles_projection[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"project_%s_%i_cfg.txt" % (process_name, jobId))
self.outputFiles_tmp[key_file] = os.path.join(
self.dirs[key_dir][DKEY_HISTO_TMP],
"histogram_%i.root" % jobId)
self.logFiles_projection[key_file] = os.path.join(
self.dirs[key_dir][DKEY_LOGS],
"project_%s_%i.log" % (process_name, jobId))
self.scriptFiles_projection[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"project_%s_%i_cfg.sh" % (process_name, jobId))
projection_module = self.projection_module
if projection_module == "count":
projection_module = "countHistogramAll"
if sample_name.startswith('/TTTo'):
projection_module += "CompTopRwgt"
elif sample_info['sample_category'].startswith('ttH'):
projection_module += "CompHTXS"
elif isSplitByNlheJet(process_name):
projection_module += "SplitByLHENjet"
elif isSplitByNlheHT(process_name):
projection_module += "SplitByLHEHT"
elif isSplitByNlheJetHT(process_name, sample_name):
projection_module += "SplitByLHENjetHT"
self.jobOptions_sbatch[key_file] = {
'histName': process_name,
'inputFiles': self.inputFiles[key_file],
'cfgFile_path': self.cfgFiles_projection[key_file],
'outputFile': self.outputFiles_tmp[key_file],
'logFile': self.logFiles_projection[key_file],
'scriptFile': self.scriptFiles_projection[key_file],
'projection_module': projection_module,
}
if self.projection_module != 'puHist':
self.jobOptions_sbatch[key_file][
'ref_genWeight'] = self.ref_genWeights[process_name]
if process_name not in self.ref_genWeights:
raise RuntimeError(
"Unable to find reference LHE weight for process %s"
% process_name)
self.createCfg_project(self.jobOptions_sbatch[key_file])
self.outputFiles[process_name]['inputFiles'].append(
self.outputFiles_tmp[key_file])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable)
self.num_jobs['project'] += self.createScript_sbatch(
self.executable, self.sbatchFile_projection,
self.jobOptions_sbatch)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_project(lines_makefile)
self.addToMakefile_hadd(lines_makefile)
if self.plot:
self.addToMakefile_plot(lines_makefile)
self.addToMakefile_finalHadd(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def submitJob(self, inputFiles, executable, cfgFile, outputFilePath, outputFiles, logFile=None, skipIfOutputFileExists=False):
"""Waits for all sbatch jobs submitted by this instance of sbatchManager to finish processing
"""
# raise if logfile missing
if not logFile:
if not self.logFileDir:
raise ValueError(
"Please call 'setLogFileDir' before calling 'submitJob' !!")
logFile = os.path.join(self.logFileDir, os.path.basename(
script_file).replace(".sh", ".log"))
# if any of the output files exists, returns (Margus: BUG? Because only
# that file should be skipped, not all?)
if skipIfOutputFileExists:
for outputFile in outputFiles:
if os.path.exists(os.path.join(outputFilePath, outputFile)):
print "output file = '%s' exists --> skipping !!" % os.path.join(outputFilePath, outputFile)
return
if not self.workingDir:
raise ValueError(
"Please call 'setWorkingDir' before calling 'submitJob' !!")
# create scratch dir
scratchDir = "/scratch/%s" % getpass.getuser()
if not os.path.exists(scratchDir):
print "Directory '%s' does not yet exist, creating it !!" % scratchDir
run_cmd(command_create_scratchDir)
scratchDir = os.path.join(
scratchDir, "tthAnalysis" + "_" + date.today().isoformat())
create_if_not_exists(scratchDir)
# create script for executing jobs
script_file = cfgFile.replace(".py", ".sh")
script_file = script_file.replace("_cfg", "")
wrapper_log_file = logFile.replace('.log', '_wrapper.log')
executable_log_file = logFile.replace('.log', '_executable.log')
command = "%s --partition=%s --output=%s %s" % (
self.command_submit, self.queue, wrapper_log_file, script_file)
script = jinja2.Template(job_template).render(
working_dir = self.workingDir,
scratch_dir = scratchDir,
exec_name = executable,
cfg_file = cfgFile,
inputFiles = " ".join(inputFiles),
outputDir = outputFilePath,
outputFiles = " ".join(outputFiles),
wrapper_log_file = wrapper_log_file,
executable_log_file = executable_log_file,
RUNNING_COMMAND = command
)
print "writing sbatch script file = '%s'" % script_file
with codecs.open(script_file, "w", "utf-8") as f:
f.write(script)
print "<submitJob>: command = %s" % command
run_cmd_output = run_cmd(command)
print "run_cmd_output: %s" % run_cmd_output
ret_val = run_cmd_output.split()[-1]
print "ret_val: %s" % ret_val
job_id = ret_val.split()[-1]
# print " jobId = %s" % jobId
self.jobIds.append(job_id)
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"]
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc
for lepton_selection in self.lepton_selections:
for central_or_shift in self.central_or_shifts:
inputFileList = generateInputFileList(sample_name, sample_info, self.max_files_per_job, self.debug)
for jobId in inputFileList.keys():
if central_or_shift != "central" and not (lepton_selection == "Tight"):
continue
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttH") and sample_category != "signal":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttW") and sample_category != "TTW":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttZ") and sample_category != "TTZ":
continue
key_dir = getKey(sample_name, lepton_selection)
key_file = getKey(sample_name, lepton_selection, central_or_shift, jobId)
self.ntupleFiles[key_file] = inputFileList[jobId]
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, lepton_selection, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" % \
(process_name, lepton_selection, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, lepton_selection, central_or_shift, jobId))
self.rleOutputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_RLES], "rle_%s_%s_%s_%s_%i.txt" % \
(self.channel, process_name, lepton_selection, central_or_shift, jobId)) if self.select_rle_output else ""
self.createCfg_analyze(self.ntupleFiles[key_file], self.histogramFiles[key_file], sample_category, self.era, triggers,
lepton_selection,
is_mc, central_or_shift, lumi_scale, apply_trigger_bits, self.cfgFiles_analyze_modified[key_file], self.rleOutputFiles[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
print self.sbatchFile_analyze
#logging.info("Creating configuration files for executing 'addBackgroundLeptonFakes'")
#self.createCfg_addFakes(self.histogramFile_hadd_stage1, self.histogramFile_addFakes, self.cfgFile_addFakes_modified)
#logging.info("Creating configuration files for executing 'addBackgroundLeptonFlips'")
#self.createCfg_addFlips(self.histogramFile_hadd_stage1, self.histogramFile_addFlips, self.cfgFile_addFlips_modified)
logging.info("Creating configuration files for executing 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
self.createCfg_prep_dcard(histogramToFit)
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
( secondary_files, primary_store, secondary_store ) = self.initializeInputFileIds(sample_name, sample_info)
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"]
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
for central_or_shift in self.central_or_shifts:
for jobId in range(len(self.inputFileIds[sample_name])):
if central_or_shift != "central" and not is_mc:
continue
inputFiles = generate_input_list(self.inputFileIds[sample_name][jobId], secondary_files, primary_store, secondary_store, self.debug)
key_dir = getKey(sample_name)
key_file = getKey(sample_name, central_or_shift, jobId)
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%i.root" % \
(process_name, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % \
(self.channel, process_name, central_or_shift, jobId))
self.createCfg_analyze(inputFiles, self.histogramFiles[key_file], sample_category, triggers,
self.lepton_selection, self.hadTau_selection,
is_mc, central_or_shift, lumi_scale, self.cfgFiles_analyze_modified[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
logging.info("Creating configuration files for executing 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
self.createCfg_prep_dcard(histogramToFit)
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_clean(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in ["additional_signal_overlap", "background_data_estimate"]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (
self.executable_analyze, process_name))
(secondary_files, primary_store, secondary_store) = self.initializeInputFileIds(
sample_name, sample_info)
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info[
"xsection"] * self.lumi / sample_info["nof_events"]
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
for lepton_selection in self.lepton_selections:
key_dir = getKey(sample_name, lepton_selection)
for central_or_shift in self.central_or_shifts:
if self.select_root_output:
rootOutputSingleFile = os.path.join(self.dirs[key_dir][DKEY_ROOT], "out_%s_%s_%s_%s.root" %
(self.channel, process_name, lepton_selection, central_or_shift))
self.rootOutputAux[rootOutputSingleFile] = os.path.join(self.dirs[key_dir][DKEY_ROOT], "out_%s_%s_%s_%s_*.root" %
(self.channel, process_name, lepton_selection, central_or_shift))
for jobId in range(len(self.inputFileIds[sample_name])):
if central_or_shift != "central" and not is_mc:
continue
key_dir = getKey(sample_name, lepton_selection)
key_file = getKey(sample_name, lepton_selection, central_or_shift, jobId)
inputFiles = generate_input_list(self.inputFileIds[sample_name][jobId], secondary_files, primary_store, secondary_store, self.debug)
self.ntupleFiles[key_file] = inputFiles
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" %
(self.channel, process_name, lepton_selection, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" %
(process_name, lepton_selection, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" %
(self.channel, process_name, lepton_selection, central_or_shift, jobId))
self.rleOutputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_RLES], "rle_%s_%s_%s_%s_%i.txt" %
(self.channel, process_name, lepton_selection, central_or_shift, jobId)) if self.select_rle_output else ""
self.rootOutputFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_ROOT], "out_%s_%s_%s_%s_%i.root" %
(self.channel, process_name, lepton_selection, central_or_shift, jobId)) if self.select_root_output else ""
self.createCfg_analyze(inputFiles,
self.histogramFiles[key_file],
sample_category,
self.era,
triggers,
lepton_selection,
is_mc,
central_or_shift,
lumi_scale,
self.cfgFiles_analyze_modified[key_file],
self.rleOutputFiles[key_file],
self.rootOutputFiles[key_file]
)
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
# # TODO hackfix (Margus)
self.datacardFiles['this_value_is_useless_and_not_used_but_somehow_it_is_important_should_be_fixed'] = 'hadd_stage1'
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(process_name)
for dir_type in [DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, "",
process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, "",
process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_HADD_RT]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
##print "self.dirs = ", self.dirs
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_name, sample_info, self.max_files_per_job, self.debug)
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
is_signal = (sample_category == "signal")
for central_or_shift in self.central_or_shifts:
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttH"
) and sample_category != "signal":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttW"
) and sample_category != "TTW":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttZ"
) and sample_category != "TTZ":
continue
# build config files for executing analysis code
key_dir = getKey(process_name)
key_analyze_job = getKey(process_name, central_or_shift,
jobId)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (
key_job, ntupleFiles)
continue
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, central_or_shift, jobId)),
'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%i.root" % \
(process_name, central_or_shift, jobId)),
'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % \
(self.channel, process_name, central_or_shift, jobId)),
'rleOutputFile' : os.path.join(self.dirs[key_dir][DKEY_RLES], "rle_%s_%s_%s_%i.txt" % \
(self.channel, process_name, central_or_shift, jobId)) if self.select_rle_output else "",
'sample_category' : sample_category,
'triggers' : sample_info["triggers"],
'hadTau_selection' : self.hadTau_selection_part2,
##'use_HIP_mitigation_mediumMuonId' : sample_info["use_HIP_mitigation_mediumMuonId"],
'use_HIP_mitigation_mediumMuonId' : True,
'is_mc' : is_mc,
'central_or_shift' : central_or_shift,
'lumi_scale' : 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"],
'apply_genWeight' : sample_info["genWeight"] if (is_mc and "genWeight" in sample_info.keys()) else False,
'apply_trigger_bits' : (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job])
# initialize input and output file names for hadd_stage1
key_hadd_stage1 = getKey(process_name)
if not key_hadd_stage1 in self.inputFiles_hadd_stage1.keys(
):
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(
self.jobOptions_analyze[key_analyze_job]
['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s.root" % \
(self.channel, process_name))
# initialize input and output file names for hadd_stage2
key_hadd_stage1 = getKey(process_name)
key_hadd_stage2 = getKey("all")
if not key_hadd_stage2 in self.inputFiles_hadd_stage2.keys():
self.inputFiles_hadd_stage2[key_hadd_stage2] = []
self.inputFiles_hadd_stage2[key_hadd_stage2].append(
self.outputFile_hadd_stage1[key_hadd_stage1])
self.outputFile_hadd_stage2[key_hadd_stage2] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage2_%s.root" % \
(self.channel))
logging.info("Creating configuration files to run 'prepareDatacards'")
for evtSelection in self.evtSelections:
for histogramToFit in self.histograms_to_fit:
key_prep_dcard_job = getKey(evtSelection, histogramToFit)
key_hadd_stage2 = getKey("all")
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"prepareDatacards_%s_%s_%s_cfg.py" %
(self.channel, evtSelection, histogramToFit)),
'datacardFile':
os.path.join(
self.dirs[DKEY_DCRD],
"prepareDatacards_%s_%s_%s.root" %
(self.channel, evtSelection, histogramToFit)),
'histogramDir':
"_".join([self.histogramDir_prep_dcard, evtSelection]),
'histogramToFit':
histogramToFit,
'label':
None
}
self.createCfg_prep_dcard(
self.jobOptions_prep_dcard[key_prep_dcard_job])
logging.info("Creating configuration files to run 'makePlots'")
for evtSelection in self.evtSelections:
key_makePlots_job = getKey(evtSelection)
key_hadd_stage2 = getKey("all")
self.jobOptions_make_plots[key_makePlots_job] = {
'executable':
self.executable_make_plots,
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"makePlots_%s_%s_cfg.py" % (self.channel, evtSelection)),
'outputFile':
os.path.join(
self.dirs[DKEY_PLOT],
"makePlots_%s_%s.png" % (self.channel, evtSelection)),
'histogramDir':
"_".join([self.histogramDir_prep_dcard, evtSelection]),
'label':
evtSelection,
'make_plots_backgrounds':
self.make_plots_backgrounds
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def __init__(self,
treeName,
outputDir,
cfgDir,
executable_addMEM,
samples,
era,
debug,
running_method,
max_files_per_job,
mem_integrations_per_job,
max_mem_integrations,
num_parallel_jobs,
leptonSelection,
hadTauSelection,
isForBDTtraining,
channel,
pool_id=''):
self.treeName = treeName
self.outputDir = outputDir
self.cfgDir = cfgDir
self.executable_addMEM = executable_addMEM
self.mem_integrations_per_job = mem_integrations_per_job
self.max_files_per_job = max_files_per_job
self.max_mem_integrations = max_mem_integrations
self.samples = samples
self.era = era
self.debug = debug
self.channel = channel
self.leptonSelection = leptonSelection
self.hadTauSelection = hadTauSelection
self.hadTauDefinition = self.hadTauSelection.split('|')[0]
self.hadTauWorkingPoint = self.hadTauSelection.split('|')[1]
self.maxPermutations_branchName = "maxPermutations_addMEM_%s_lep%s_tau%s_%s" % (
self.channel,
self.leptonSelection,
self.hadTauDefinition,
self.hadTauWorkingPoint,
)
self.isForBDTtraining = isForBDTtraining
if running_method.lower() not in ["sbatch", "makefile"]:
raise ValueError("Invalid running method: %s" % running_method)
self.running_method = running_method
self.is_sbatch = False
self.is_makefile = False
if self.running_method.lower() == "sbatch":
self.is_sbatch = True
else:
self.is_makefile = True
self.makefile = os.path.join(self.cfgDir, "Makefile_%s" % self.channel)
self.num_parallel_jobs = num_parallel_jobs
self.pool_id = pool_id if pool_id else uuid.uuid4()
self.workingDir = os.getcwd()
logging.info("Working directory is: {workingDir}".format(
workingDir=self.workingDir))
for dirPath in [self.outputDir, self.cfgDir]:
create_if_not_exists(dirPath)
self.stdout_file = codecs.open(
os.path.join(self.cfgDir, "stdout_%s.log" % self.channel), 'w',
'utf-8')
self.stderr_file = codecs.open(
os.path.join(self.cfgDir, "stderr_%s.log" % self.channel), 'w',
'utf-8')
self.dirs = {}
self.samples = samples
self.cfgFiles_addMEM_modified = {}
self.shFiles_addMEM_modified = {}
self.logFiles_addMEM = {}
self.sbatchFile_addMEM = os.path.join(
self.cfgDir, "sbatch_addMEM_%s.py" % self.channel)
self.inputFiles = {}
self.outputFiles = {}
self.hadd_records = {}
self.filesToClean = []
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or \
sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(sample_name)
for dir_type in [DKEY_NTUPLES, DKEY_FINAL_NTUPLES]:
initDict(self.dirs, [key_dir, dir_type])
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, process_name)
for dir_type in [DKEY_CFGS, DKEY_LOGS, DKEY_HADD, DKEY_HADD_RT]:
initDict(self.dirs, [key_dir, dir_type])
self.dirs[key_dir][dir_type] = os.path.join(
self.cfgDir, dir_type, self.channel, process_name)
self.cvmfs_error_log = {}
def create(self):
"""Creates all necessary config files and runs the PU profile production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info['use_it']:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
if not is_mc:
continue
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable, process_name))
inputFileList = generateInputFileList(sample_info,
self.max_files_per_job)
key_dir = getKey(process_name)
outputFile = os.path.join(self.dirs[key_dir][DKEY_HISTO],
"%s.root" % process_name)
if os.path.isfile(outputFile) and tools_is_file_ok(
outputFile, min_file_size=2000):
logging.info('File {} already exists --> skipping job'.format(
outputFile))
continue
self.outputFiles[process_name] = {
'inputFiles': [],
'outputFile': outputFile
}
for jobId in inputFileList.keys():
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = inputFileList[jobId]
if len(self.inputFiles[key_file]) == 0:
logging.warning(
"ntupleFiles['%s'] = %s --> skipping job !!" %
(key_file, self.inputFiles[key_file]))
continue
self.cfgFiles_puProfile[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"puProfile_%s_%i_cfg.txt" % (process_name, jobId))
self.outputFiles_tmp[key_file] = os.path.join(
self.dirs[key_dir][DKEY_HISTO_TMP],
"histogram_%i.root" % jobId)
self.logFiles_puProfile[key_file] = os.path.join(
self.dirs[key_dir][DKEY_LOGS],
"puProfile_%s_%i.log" % (process_name, jobId))
self.scriptFiles_puProfile[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"puProfile_%s_%i_cfg.sh" % (process_name, jobId))
self.jobOptions_sbatch[key_file] = {
'histName': process_name,
'inputFiles': self.inputFiles[key_file],
'cfgFile_path': self.cfgFiles_puProfile[key_file],
'outputFile': self.outputFiles_tmp[key_file],
'logFile': self.logFiles_puProfile[key_file],
'scriptFile': self.scriptFiles_puProfile[key_file],
}
self.createCfg_puProfile(self.jobOptions_sbatch[key_file])
self.outputFiles[process_name]['inputFiles'].append(
self.outputFiles_tmp[key_file])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable)
self.num_jobs['puProfile'] += self.createScript_sbatch(
self.executable, self.sbatchFile_puProfile,
self.jobOptions_sbatch)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_puProfile(lines_makefile)
self.addToMakefile_hadd(lines_makefile)
self.addToMakefile_plot(lines_makefile)
self.addToMakefile_finalHadd(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the MEM -- either locally or on the batch system
"""
statistics = {}
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
# read the file in, sample-by-sample
# build the dictionary recursively
# add rle file also to generated cfg files
# print integrations per job as well!
# consider more than 1 file per jobs -- the jobs are splitted by MEM integration anyways
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or \
sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
if not os.path.exists(sample_info['local_paths'][0]['path']):
logging.warning("Skipping sample {sample_name}".format(
sample_name=sample_name))
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_addMEM, process_name))
is_mc = (sample_info["type"] == "mc")
inputFileList = generateInputFileList(sample_name, sample_info,
self.max_files_per_job,
self.debug)
# typically, the analysis ends here and starts looping b/c the smallest unit of work processes
# at least one file; we need, however, to split the file into event ranges in such a way that
# each job performs mem_integrations_per_job MEM integrations
# so what we are going to do is to open each set of files in inputFileList, read the variable
# requestMEM_*l_*tau and try to gather the event ranges such that each event range
# performs up to mem_integrations_per_job integrations per job
memEvtRangeDict = self.memJobList(inputFileList)
for jobId in memEvtRangeDict.keys():
key_dir = getKey(sample_name)
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = memEvtRangeDict[jobId][
'input_fileset']
# there should always be a job
assert(self.inputFiles[key_file] > 0), "More than one input file: %s ?? !!" % \
', '.join(self.inputFiles[key_file])
#assert(len(self.inputFiles[key_file]) == 1), "There is more than one input file!"
self.cfgFiles_addMEM_modified[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS], "addMEM_%s_%s_%i_cfg.py" %
(self.channel, process_name, jobId))
self.shFiles_addMEM_modified[key_file] = os.path.join(
self.dirs[key_dir][DKEY_CFGS],
"addMEM_%s_%s_%i.sh" % (self.channel, process_name, jobId))
self.outputFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_NTUPLES],
"%s_%i.root" % (process_name, jobId))
self.logFiles_addMEM[key_file] = os.path.join(
self.dirs[key_dir][DKEY_LOGS], "addMEM_%s_%s_%i.log" %
(self.channel, process_name, jobId))
self.createCfg_addMEM(
self.inputFiles[key_file],
memEvtRangeDict[jobId]['event_range'][0],
memEvtRangeDict[jobId]['event_range'][1],
self.outputFiles[key_file],
self.era,
is_mc,
self.cfgFiles_addMEM_modified[key_file],
)
# associate the output file with the fileset_id
#UDPATE: ONE OUTPUT FILE PER SAMPLE!
fileset_id = memEvtRangeDict[jobId]['fileset_id']
hadd_output_dir = os.path.join(
self.dirs[key_dir][DKEY_FINAL_NTUPLES],
str('%04d' % fileset_id // 1000))
if not os.path.exists(hadd_output_dir):
os.makedirs(hadd_output_dir)
hadd_output = os.path.join(
hadd_output_dir,
'%s_%i.root' % ('tree', fileset_id) # UDPATE: ADDED
#hadd_output_dir, "tree.root" # UDPATE: REMOVED
)
if hadd_output not in self.hadd_records:
self.hadd_records[hadd_output] = {}
self.hadd_records[hadd_output]['output_files'] = []
self.hadd_records[hadd_output]['fileset_id'] = fileset_id
self.hadd_records[hadd_output]['output_files'].append(
self.outputFiles[key_file])
self.hadd_records[hadd_output]['process_name'] = process_name
#self.filesToClean.append(self.outputFiles[key_file])
# let's sum the number of integration per sample
nofEntriesMap = {}
for v in memEvtRangeDict.values():
if v['fileset_id'] not in nofEntriesMap:
nofEntriesMap[v['fileset_id']] = {
'nof_entries': v['nof_entries'],
}
statistics[process_name] = {
'nof_int':
sum([entry['nof_int'] for entry in memEvtRangeDict.values()]),
'nof_entries':
sum([entry['nof_entries']
for entry in nofEntriesMap.values()]),
'nof_events_pass':
sum([
entry['nof_events_pass']
for entry in memEvtRangeDict.values()
]),
'nof_int_pass':
sum([
entry['nof_int_pass']
for entry in memEvtRangeDict.values()
]),
'nof_zero':
sum([entry['nof_zero'] for entry in memEvtRangeDict.values()]),
'nof_jobs':
len(memEvtRangeDict),
}
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_addMEM)
self.createScript_sbatch()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_addMEM(lines_makefile)
self.addToMakefile_hadd(lines_makefile)
self.createMakefile(lines_makefile)
ws_len = max([len(kk) + 1 for kk in statistics.keys()])
total_nof_integrations_sum = sum(x['nof_int']
for x in statistics.values())
total_nof_entires = sum(x['nof_entries'] for x in statistics.values())
total_nof_zero_int = sum(x['nof_zero'] for x in statistics.values())
total_nof_jobs = sum(x['nof_jobs'] for x in statistics.values())
total_nof_pass = sum(x['nof_events_pass'] for x in statistics.values())
total_nof_int_pass_avg = float(
sum(x['nof_int_pass']
for x in statistics.values())) / total_nof_pass
total_nof_integrations_avg = float(
total_nof_integrations_sum) / total_nof_entires
total_nof_int_per_job = float(
total_nof_integrations_sum) / total_nof_jobs
for k, v in statistics.iteritems():
if v['nof_entries'] == 0:
int_per_event = 0.
evt_pass = 0.
else:
int_per_event = float(v['nof_int']) / v['nof_entries']
evt_pass = (100 * float(v['nof_events_pass']) /
v['nof_entries'])
if v['nof_events_pass'] == 0:
nof_int_pass = 0.
else:
nof_int_pass = float(v['nof_int_pass']) / v['nof_events_pass']
print(
'%s%s: %d (%d entries; %d jobs; %.2f int/evt; %d (%.2f%%) evt pass; %.2f int/evt pass; %d evt 0int)'
% (
k,
' ' * (ws_len - len(k)),
v['nof_int'],
v['nof_entries'],
v['nof_jobs'],
int_per_event,
v['nof_events_pass'],
evt_pass,
nof_int_pass,
v['nof_zero'],
))
print(
'%s%s: %d (%d entries; %d jobs; %.2f int/evt; %d evt pass; %.2f int/evt pass; '
'%.2f int/job pass; %d evt 0int)' % (
'total',
' ' * (ws_len - len('total')),
total_nof_integrations_sum,
total_nof_entires,
total_nof_jobs,
total_nof_integrations_avg,
total_nof_pass,
total_nof_int_pass_avg,
total_nof_int_per_job,
total_nof_zero_int,
))
if self.max_mem_integrations > 0 and total_nof_integrations_sum > self.max_mem_integrations:
logging.error(
"Will not start the jobs (max nof integrations exceeded)!")
return False
else:
logging.info("Done")
return True
def create(self):
"""Creates all necessary config files and runs the Ntuple production -- either locally or on the batch system
"""
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
is_mc = (sample_info["type"] == "mc")
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_prodNtuple, process_name))
inputFileList = generateInputFileList(sample_name, sample_info,
self.max_files_per_job,
self.debug)
key_dir = getKey(sample_name)
subDirs = list(
map(
lambda y: os.path.join(self.dirs[key_dir][DKEY_NTUPLES],
'%04d' % y),
set(map(lambda x: x // 1000, inputFileList.keys()))))
for subDir in subDirs:
create_if_not_exists(subDir)
for jobId in inputFileList.keys():
key_file = getKey(sample_name, jobId)
self.inputFiles[key_file] = inputFileList[jobId]
if len(self.inputFiles[key_file]) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (
key_file, self.inputFiles[key_file])
continue
self.cfgFiles_prodNtuple_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "produceNtuple_%s_%i_cfg.py" % \
(process_name, jobId))
self.outputFiles[key_file] = os.path.join(
self.dirs[key_dir][DKEY_NTUPLES], "%04d" % (jobId // 1000),
"tree_%i.root" % jobId)
self.logFiles_prodNtuple[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "produceNtuple_%s_%i.log" % \
(process_name, jobId))
jobOptions = {
'inputFiles': self.inputFiles[key_file],
'cfgFile_modified':
self.cfgFiles_prodNtuple_modified[key_file],
'outputFile': self.outputFiles[key_file],
##'use_HIP_mitigation_mediumMuonId' : sample_info["use_HIP_mitigation_mediumMuonId"],
'use_HIP_mitigation_mediumMuonId': True,
'is_mc': is_mc,
'random_seed': jobId
}
self.createCfg_prodNtuple(jobOptions)
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_prodNtuple)
self.createScript_sbatch()
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_prodNtuple(lines_makefile)
#self.addToMakefile_clean(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
process_name = sample_info["process_name_specific"]
logging.info("Building dictionaries for sample %s..." % process_name)
for lepton_selection in self.lepton_selections:
for lepton_frWeight in self.lepton_frWeights:
if lepton_frWeight == "enabled" and not lepton_selection.startswith("Fakeable"):
continue
if lepton_frWeight == "disabled" and not lepton_selection in ["Tight", "forBDTtraining"]:
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_selection, lepton_frWeight)
for leptonChargeSelection in self.leptonChargeSelections:
central_or_shift_extensions = ["", "hadd", "addBackgrounds"]
central_or_shift_dedicated = self.central_or_shifts if self.runTHweights(sample_info) else self.central_or_shifts_external
central_or_shifts_extended = central_or_shift_extensions + central_or_shift_dedicated
for central_or_shift_or_dummy in central_or_shifts_extended:
process_name_extended = [ process_name, "hadd" ]
for process_name_or_dummy in process_name_extended:
if central_or_shift_or_dummy in [ "hadd", "addBackgrounds" ] and process_name_or_dummy in [ "hadd" ]:
continue
if central_or_shift_or_dummy not in central_or_shift_extensions and not self.accept_systematics(
central_or_shift_or_dummy, is_mc, lepton_selection, leptonChargeSelection, sample_info
):
continue
key_dir = getKey(process_name_or_dummy, lepton_selection_and_frWeight, leptonChargeSelection, central_or_shift_or_dummy)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES, DKEY_SYNC ]:
if dir_type == DKEY_SYNC and not self.do_sync:
continue
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel,
"_".join([ lepton_selection_and_frWeight, leptonChargeSelection ]), process_name_or_dummy, central_or_shift_or_dummy)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,
"_".join([ lepton_selection_and_frWeight, leptonChargeSelection ]), process_name_or_dummy)
for subdirectory in [ "addBackgrounds", "addBackgroundLeptonFakes", "prepareDatacards", "addSystFakeRates", "makePlots" ]:
key_dir = getKey(subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel, subdirectory)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT, DKEY_SYNC ]:
if dir_type == DKEY_SYNC and not self.do_sync:
continue
initDict(self.dirs, [ dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type, self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" % numDirectories)
numDirectories_created = 0;
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100*numDirectories_created >= frac*numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" % sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)
for lepton_selection in self.lepton_selections:
hadTau_selection = "Tight"
hadTau_selection = "|".join([hadTau_selection, self.hadTau_selection_part2])
electron_selection = lepton_selection
muon_selection = lepton_selection
if lepton_selection == "forBDTtraining":
electron_selection = "Loose"
muon_selection = "Loose"
elif lepton_selection == "Fakeable_mcClosure_e":
electron_selection = "Fakeable"
muon_selection = "Tight"
elif lepton_selection == "Fakeable_mcClosure_m":
electron_selection = "Tight"
muon_selection = "Fakeable"
if "forBDTtraining" in lepton_selection:
electron_selection = "Loose"
muon_selection = "Loose"
elif lepton_selection == "Fakeable_mcClosure_e":
electron_selection = "Fakeable"
muon_selection = "Tight"
elif lepton_selection == "Fakeable_mcClosure_m":
electron_selection = "Tight"
muon_selection = "Fakeable"
for lepton_frWeight in self.lepton_frWeights:
if lepton_frWeight == "enabled" and not lepton_selection.startswith("Fakeable"):
continue
if lepton_frWeight == "disabled" and not lepton_selection in [ "Tight", "forBDTtraining" ]:
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_selection, lepton_frWeight)
for leptonChargeSelection in self.leptonChargeSelections:
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
inputFileList = inputFileLists[sample_name]
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
use_th_weights = self.runTHweights(sample_info)
central_or_shift_dedicated = self.central_or_shifts if use_th_weights else self.central_or_shifts_external
for central_or_shift in central_or_shift_dedicated:
if not self.accept_systematics(
central_or_shift, is_mc, lepton_selection, leptonChargeSelection, sample_info
):
continue
central_or_shifts_local = []
if central_or_shift == "central" and not use_th_weights:
for central_or_shift_local in self.central_or_shifts_internal:
if self.accept_systematics(
central_or_shift_local, is_mc, lepton_selection, leptonChargeSelection, sample_info
):
central_or_shifts_local.append(central_or_shift_local)
logging.info(" ... for '%s' and systematic uncertainty option '%s'" % (lepton_selection_and_frWeight, central_or_shift))
# build config files for executing analysis code
key_analyze_dir = getKey(process_name, lepton_selection_and_frWeight, leptonChargeSelection, central_or_shift)
for jobId in inputFileList.keys():
analyze_job_tuple = (process_name, lepton_selection_and_frWeight, leptonChargeSelection, central_or_shift, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning("No input ntuples for %s --> skipping job !!" % (key_analyze_job))
continue
cfgFile_modified_path = os.path.join(self.dirs[key_analyze_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % analyze_job_tuple)
rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], "rle_%s_%s_%s_%s_%i.txt" % analyze_job_tuple) \
if self.select_rle_output else ""
histogramFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_HIST], "analyze_%s_%s_%s_%s_%i.root" % analyze_job_tuple)
applyFakeRateWeights = self.applyFakeRateWeights \
if self.isBDTtraining or lepton_selection.find("Tight") == -1 \
else "disabled"
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : cfgFile_modified_path,
'histogramFile' : histogramFile_path,
'logFile' : logFile_path,
'selEventsFileName_output' : rleOutputFile_path,
'electronSelection' : electron_selection,
'muonSelection' : muon_selection,
'apply_leptonGenMatching' : self.apply_leptonGenMatching,
'leptonChargeSelection' : leptonChargeSelection,
'applyFakeRateWeights' : applyFakeRateWeights,
'hadTauSelection' : hadTau_selection,
'central_or_shift' : central_or_shift,
'central_or_shifts_local' : central_or_shifts_local,
'fillGenEvtHistograms' : True,
'selectBDT' : self.isBDTtraining,
'apply_hlt_filter' : self.hlt_filter,
'selectBDT' : self.isBDTtraining,
}
self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job], sample_info, lepton_selection)
# initialize input and output file names for hadd_stage1
key_hadd_stage1_dir = getKey(process_name, lepton_selection_and_frWeight, leptonChargeSelection)
hadd_stage1_job_tuple = (process_name, lepton_selection_and_frWeight, leptonChargeSelection)
key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)
if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []
self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1_job] = os.path.join(self.dirs[key_hadd_stage1_dir][DKEY_HIST],
"hadd_stage1_%s_%s_%s.root" % hadd_stage1_job_tuple)
if self.isBDTtraining:
continue
# add output files of hadd_stage1 to list of input files for hadd_stage1_5
key_hadd_stage1_job = getKey(process_name, lepton_selection_and_frWeight, leptonChargeSelection)
key_hadd_stage1_5_dir = getKey("hadd", lepton_selection_and_frWeight, leptonChargeSelection)
hadd_stage1_5_job_tuple = (lepton_selection_and_frWeight, leptonChargeSelection)
key_hadd_stage1_5_job = getKey(*hadd_stage1_5_job_tuple)
if not key_hadd_stage1_5_job in self.inputFiles_hadd_stage1_5:
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job] = []
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job].append(self.outputFile_hadd_stage1[key_hadd_stage1_job])
self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job] = os.path.join(self.dirs[key_hadd_stage1_5_dir][DKEY_HIST],
"hadd_stage1_5_%s_%s.root" % hadd_stage1_5_job_tuple)
if self.isBDTtraining:
continue
# sum fake background contributions for the total of all MC sample
# input processes: TT_fake, TTW_fake, TTWW_fake, ...
# output process: fakes_mc
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight, leptonChargeSelection)
key_addBackgrounds_dir = getKey("addBackgrounds")
addBackgrounds_job_fakes_tuple = ("fakes_mc", lepton_selection_and_frWeight, leptonChargeSelection)
key_addBackgrounds_job_fakes = getKey(*addBackgrounds_job_fakes_tuple)
sample_categories = []
sample_categories.extend(self.nonfake_backgrounds)
processes_input = []
for sample_category in sample_categories:
processes_input.append("%s_fake" % sample_category)
self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_%s_cfg.py" % addBackgrounds_job_fakes_tuple),
'outputFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s_%s.root" % addBackgrounds_job_fakes_tuple),
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], "addBackgrounds_%s_%s_%s.log" % addBackgrounds_job_fakes_tuple),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight, leptonChargeSelection) ],
'processes_input' : processes_input,
'process_output' : "fakes_mc"
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes])
# sum conversion background contributions for the total of all MC sample
# input processes: TT_Convs, TTW_Convs, TTWW_Convs, ...
# output process: Convs
addBackgrounds_job_Convs_tuple = ("Convs", lepton_selection_and_frWeight, leptonChargeSelection)
key_addBackgrounds_job_Convs = getKey(*addBackgrounds_job_Convs_tuple)
sample_categories = []
sample_categories.extend(self.nonfake_backgrounds)
processes_input = []
for sample_category in self.convs_backgrounds:
processes_input.append("%s_Convs" % sample_category)
self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_Convs] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_%s_cfg.py" % addBackgrounds_job_Convs_tuple),
'outputFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s_%s.root" % addBackgrounds_job_Convs_tuple),
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], "addBackgrounds_%s_%s_%s.log" % addBackgrounds_job_Convs_tuple),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight, leptonChargeSelection) ],
'processes_input' : processes_input,
'process_output' : "Convs"
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_Convs])
# sum signal contributions from HH->4tau ("tttt"), HH->2W2tau ("wwtt"), and HH->4W ("wwww"),
# separately for "nonfake" and "fake" contributions
genMatch_categories = [ "nonfake", "fake" ]
for genMatch_category in genMatch_categories:
for signal_base, signal_input in self.signal_io.items():
addBackgrounds_job_signal_tuple = (lepton_selection_and_frWeight, leptonChargeSelection, signal_base, genMatch_category)
key_addBackgrounds_job_signal = getKey(*addBackgrounds_job_signal_tuple)
if key_addBackgrounds_job_signal in self.jobOptions_addBackgrounds_sum.keys():
continue
processes_input = signal_input
process_output = signal_base
if genMatch_category == "fake":
processes_input = [ process_input + "_fake" for process_input in processes_input ]
process_output += "_fake"
self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_signal] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_%s_%s_cfg.py" % addBackgrounds_job_signal_tuple),
'outputFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s_%s_%s.root" % addBackgrounds_job_signal_tuple),
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], "addBackgrounds_%s_%s_%s_%s.log" % addBackgrounds_job_signal_tuple),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight, leptonChargeSelection) ],
'processes_input' : processes_input,
'process_output' : process_output
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_signal])
key_hadd_stage2_job = getKey(lepton_selection_and_frWeight, leptonChargeSelection)
if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []
if lepton_selection == "Tight":
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_signal]['outputFile'])
# initialize input and output file names for hadd_stage2
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight, leptonChargeSelection)
key_hadd_stage2_dir = getKey("hadd", lepton_selection_and_frWeight, leptonChargeSelection)
hadd_stage2_job_tuple = (lepton_selection_and_frWeight, leptonChargeSelection)
key_hadd_stage2_job = getKey(*hadd_stage2_job_tuple)
if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []
if lepton_selection == "Tight":
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes]['outputFile'])
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_Convs]['outputFile'])
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job])
self.outputFile_hadd_stage2[key_hadd_stage2_job] = os.path.join(self.dirs[key_hadd_stage2_dir][DKEY_HIST],
"hadd_stage2_%s_%s.root" % hadd_stage2_job_tuple)
if self.isBDTtraining:
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.targets.extend(self.phoniesToAdd)
self.addToMakefile_validate(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
logging.info("Creating configuration files to run 'addBackgroundFakes'")
for leptonChargeSelection in self.leptonChargeSelections:
key_hadd_stage1_5_job = getKey(get_lepton_selection_and_frWeight("Fakeable", "enabled"), leptonChargeSelection)
key_addFakes_dir = getKey("addBackgroundLeptonFakes")
key_addFakes_job = getKey("data_fakes", leptonChargeSelection)
category_sideband = "hh_4l_%s_Fakeable_wFakeRateWeights" % leptonChargeSelection
self.jobOptions_addFakes[key_addFakes_job] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addFakes_dir][DKEY_CFGS], "addBackgroundLeptonFakes_%s_cfg.py" % leptonChargeSelection),
'outputFile' : os.path.join(self.dirs[key_addFakes_dir][DKEY_HIST], "addBackgroundLeptonFakes_%s.root" % leptonChargeSelection),
'logFile' : os.path.join(self.dirs[key_addFakes_dir][DKEY_LOGS], "addBackgroundLeptonFakes_%s.log" % leptonChargeSelection),
'category_signal' : "hh_4l_%s_Tight" % leptonChargeSelection,
'category_sideband' : category_sideband
}
self.createCfg_addFakes(self.jobOptions_addFakes[key_addFakes_job])
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), leptonChargeSelection)
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addFakes[key_addFakes_job]['outputFile'])
logging.info("Creating configuration files to run 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
key_prep_dcard_dir = getKey("prepareDatacards")
if "OS" in self.leptonChargeSelections:
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), "OS")
prep_dcard_job_tuple = (self.channel, "OS", histogramToFit)
key_prep_dcard_job = getKey("OS", histogramToFit)
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_CFGS], "prepareDatacards_%s_%s_%s_cfg.py" % prep_dcard_job_tuple),
'datacardFile' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_%s_%s_%s.root" % prep_dcard_job_tuple),
'histogramDir' : self.histogramDir_prep_dcard,
'histogramToFit' : histogramToFit,
'label' : '4l',
}
self.createCfg_prep_dcard(self.jobOptions_prep_dcard[key_prep_dcard_job])
if "SS" in self.leptonChargeSelections:
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), "SS")
prep_dcard_job_tuple = (self.channel, "SS", histogramToFit)
key_prep_dcard_job = getKey("SS", histogramToFit)
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_CFGS], "prepareDatacards_%s_%s_%s_cfg.py" % prep_dcard_job_tuple),
'datacardFile' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_%s_%s_%s.root" % prep_dcard_job_tuple),
'histogramDir' : self.histogramDir_prep_dcard_SS,
'histogramToFit' : histogramToFit,
'label' : '4l SS',
}
self.createCfg_prep_dcard(self.jobOptions_prep_dcard[key_prep_dcard_job])
# add shape templates for the following systematic uncertainties:
# - 'CMS_ttHl_Clos_norm_e'
# - 'CMS_ttHl_Clos_shape_e'
# - 'CMS_ttHl_Clos_norm_m'
# - 'CMS_ttHl_Clos_shape_m'
for leptonChargeSelection in self.leptonChargeSelections:
key_prep_dcard_job = getKey(leptonChargeSelection, histogramToFit)
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), leptonChargeSelection)
key_add_syst_fakerate_dir = getKey("addSystFakeRates")
add_syst_fakerate_job_tuple = (self.channel, leptonChargeSelection, histogramToFit)
key_add_syst_fakerate_job = getKey(leptonChargeSelection, histogramToFit)
self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job] = {
'inputFile' : self.jobOptions_prep_dcard[key_prep_dcard_job]['datacardFile'],
'cfgFile_modified' : os.path.join(self.dirs[key_add_syst_fakerate_dir][DKEY_CFGS], "addSystFakeRates_%s_%s_%s_cfg.py" % add_syst_fakerate_job_tuple),
'outputFile' : os.path.join(self.dirs[key_add_syst_fakerate_dir][DKEY_DCRD], "addSystFakeRates_%s_%s_%s.root" % add_syst_fakerate_job_tuple),
'category' : self.channel,
'histogramToFit' : histogramToFit,
'plots_outputFileName' : os.path.join(self.dirs[DKEY_PLOT], "addSystFakeRates.png")
}
histogramDir_nominal = None
if leptonChargeSelection == "OS":
histogramDir_nominal = self.histogramDir_prep_dcard
elif leptonChargeSelection == "SS":
histogramDir_nominal = self.histogramDir_prep_dcard_SS
else:
raise ValueError("Invalid parameter 'leptonChargeSelection' = %s !!" % leptonChargeSelection)
for lepton_type in [ 'e', 'm' ]:
lepton_mcClosure = "Fakeable_mcClosure_%s" % lepton_type
if lepton_mcClosure not in self.lepton_selections:
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_mcClosure, "enabled")
key_addBackgrounds_job_fakes = getKey("fakes_mc", lepton_selection_and_frWeight, leptonChargeSelection)
histogramDir_mcClosure = self.mcClosure_dir['%s_%s' % (lepton_mcClosure, leptonChargeSelection)]
self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job].update({
'add_Clos_%s' % lepton_type : ("Fakeable_mcClosure_%s" % lepton_type) in self.lepton_selections,
'inputFile_nominal_%s' % lepton_type : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'histogramName_nominal_%s' % lepton_type : "%s/sel/evt/fakes_mc/%s" % (histogramDir_nominal, histogramToFit),
'inputFile_mcClosure_%s' % lepton_type : self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes]['outputFile'],
'histogramName_mcClosure_%s' % lepton_type : "%s/sel/evt/fakes_mc/%s" % (histogramDir_mcClosure, histogramToFit)
})
self.createCfg_add_syst_fakerate(self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job])
logging.info("Creating configuration files to run 'makePlots'")
key_makePlots_dir = getKey("makePlots")
if "OS" in self.leptonChargeSelections:
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), "OS")
key_makePlots_job = getKey("OS")
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_%s_cfg.py" % self.channel),
'outputFile' : os.path.join(self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_%s.png" % self.channel),
'histogramDir' : self.histogramDir_prep_dcard,
'label' : '4l',
'make_plots_backgrounds' : self.make_plots_backgrounds,
}
self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
if "SS" in self.leptonChargeSelections:
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), "SS")
key_makePlots_job = getKey("SS")
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_%s_SS_cfg.py" % self.channel),
'outputFile' : os.path.join(self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_%s_SS.png" % self.channel),
'histogramDir' : self.histogramDir_prep_dcard_SS,
'label' : "4l SS",
'make_plots_backgrounds' : self.make_plots_backgrounds,
}
self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
if "Fakeable_mcClosure" in self.lepton_selections: #TODO
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"), "OS")
key_makePlots_job = getKey("Fakeable_mcClosure", "OS")
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots_mcClosure,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_mcClosure_%s_cfg.py" % self.channel),
'outputFile' : os.path.join(self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_mcClosure_%s.png" % self.channel)
}
self.createCfg_makePlots_mcClosure(self.jobOptions_make_plots[key_makePlots_job])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_addBackgrounds)
self.sbatchFile_addBackgrounds = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addBackgrounds_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addBackgrounds, self.sbatchFile_addBackgrounds, self.jobOptions_addBackgrounds)
self.sbatchFile_addBackgrounds_sum = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addBackgrounds_sum_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addBackgrounds, self.sbatchFile_addBackgrounds_sum, self.jobOptions_addBackgrounds_sum)
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_addFakes)
self.sbatchFile_addFakes = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addFakes_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addFakes, self.sbatchFile_addFakes, self.jobOptions_addFakes)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_add_syst_fakerate(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.addToMakefile_validate(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
'label' : inclusive_sample,
})
for sample_entry in samples.values():
sample_name = sample_entry['process_name_specific']
if sample_name not in valid_samples_to_sum_flat and sample_entry['type'] != 'data':
valid_samples_to_sum.append({
'xs' : sample_entry['xsection'],
'samples' : [ sample_name ],
'nentries' : { sample_name : sample_entry['nof_tree_events'] },
'label' : sample_name,
})
if not os.path.isdir(args.output):
if not args.force:
raise ValueError('Use -f/--force to create output directory %s' % args.output)
create_if_not_exists(args.output)
for valid_samples in valid_samples_to_sum:
input_files = {
sample_name : {
'input' : pattern.format(sample_name = sample_name),
'nentries' : valid_samples['nentries'][sample_name],
} for sample_name in valid_samples['samples']
}
output_files = [
os.path.join(args.output, '%s.%s' % (valid_samples['label'], ext)) for ext in args.extension
]
expected_neff = lumi * valid_samples['xs']
plot(input_files, output_files, valid_samples['label'], expected_neff, args.mode)
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(process_name)
for dir_type in [DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
##print "self.dirs = ", self.dirs
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_name, sample_info, self.max_files_per_job, self.debug)
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
##print "processing sample %s: jobId = %i" % (process_name, jobId)
# build config files for executing analysis code
key_dir = getKey(process_name)
key_analyze_job = getKey(process_name, jobId)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (
key_file, ntupleFiles)
continue
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%i_cfg.py" % \
(self.channel, process_name, jobId)),
'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%i.root" % \
(process_name, jobId)),
'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%i.log" % \
(self.channel, process_name, jobId)),
'sample_category' : sample_category,
'hadTau_selection' : self.hadTau_selection,
'use_HIP_mitigation_mediumMuonId' : True,
'is_mc' : is_mc,
'lumi_scale' : 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"],
'apply_genWeight' : sample_info["genWeight"] if (is_mc and "genWeight" in sample_info) else False,
'selectBDT' : True,
'changeBranchNames' : self.changeBranchNames
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job])
# initialize input and output file names for hadd_stage1
key_hadd_stage1 = getKey(process_name)
if not key_hadd_stage1 in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(
self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s.root" % \
(self.channel, process_name))
self.targets.append(
self.outputFile_hadd_stage1[key_hadd_stage1])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
for lepton_selection in self.lepton_selections:
for lepton_frWeight in self.lepton_frWeights:
if lepton_frWeight == "enabled" and not lepton_selection.startswith("Fakeable"):
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_selection, lepton_frWeight)
central_or_shifts_extended = [ "" ]
central_or_shifts_extended.extend(self.central_or_shifts)
central_or_shifts_extended.extend([ "hadd", "addBackgrounds" ])
for central_or_shift_or_dummy in central_or_shifts_extended:
process_name_extended = [ process_name, "hadd" ]
for process_name_or_dummy in process_name_extended:
key_dir = getKey(process_name_or_dummy, lepton_selection_and_frWeight, central_or_shift_or_dummy)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_ROOT, DKEY_RLES, DKEY_SYNC ]:
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel,
"_".join([ lepton_selection_and_frWeight ]), process_name_or_dummy, central_or_shift_or_dummy)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,
"_".join([ lepton_selection_and_frWeight ]), process_name_or_dummy, central_or_shift_or_dummy)
for subdirectory in [ "addBackgrounds", "addBackgroundLeptonFakes", "prepareDatacards", "addSystFakeRates", "makePlots" ]:
key_dir = getKey(subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_ROOT, DKEY_DCRD, DKEY_PLOT ]:
initDict(self.dirs, [ key_dir, dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_LOGS ]:
self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel, subdirectory)
else:
self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel, subdirectory)
for dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT, DKEY_SYNC ]:
initDict(self.dirs, [ dir_type ])
if dir_type in [ DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT, DKEY_HADD_RT ]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type, self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type, self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" % numDirectories)
numDirectories_created = 0;
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100*numDirectories_created >= frac*numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
logging.info("Checking input files for sample %s" % sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(sample_info, self.max_files_per_job)
mcClosure_regex = re.compile('Fakeable_mcClosure_(?P<type>m|e)_wFakeRateWeights')
for lepton_selection in self.lepton_selections:
electron_selection = lepton_selection
muon_selection = lepton_selection
hadTauVeto_selection = "Tight"
hadTauVeto_selection = "|".join([ hadTauVeto_selection, self.hadTauVeto_selection_part2 ])
if lepton_selection == "Fakeable_mcClosure_e":
electron_selection = "Fakeable"
muon_selection = "Tight"
elif lepton_selection == "Fakeable_mcClosure_m":
electron_selection = "Tight"
muon_selection = "Fakeable"
for lepton_frWeight in self.lepton_frWeights:
if lepton_frWeight == "enabled" and not lepton_selection.startswith("Fakeable"):
continue
if lepton_frWeight == "disabled" and not lepton_selection in [ "Tight" ]:
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_selection, lepton_frWeight)
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
is_signal = (sample_category == "signal")
for central_or_shift in self.central_or_shifts:
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
if central_or_shift != "central":
isFR_shape_shift = (central_or_shift in systematics.FR_all)
if not ((lepton_selection == "Fakeable" and isFR_shape_shift) or lepton_selection == "Tight"):
continue
if not is_mc and not isFR_shape_shift:
continue
if central_or_shift in systematics.LHE().ttH and sample_category != "signal":
continue
if central_or_shift in systematics.LHE().ttW and sample_category != "TTW":
continue
if central_or_shift in systematics.LHE().ttZ and sample_category != "TTZ":
continue
if central_or_shift in systematics.DYMCReweighting and not is_dymc_reweighting(sample_name):
continue
logging.info(" ... for '%s' and systematic uncertainty option '%s'" % (lepton_selection_and_frWeight, central_or_shift))
# build config files for executing analysis code
key_analyze_dir = getKey(process_name, lepton_selection_and_frWeight, central_or_shift)
analyze_job_tuple = (process_name, lepton_selection_and_frWeight, central_or_shift, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning("No input ntuples for %s --> skipping job !!" % (key_analyze_job))
continue
syncOutput = ''
syncTree = ''
syncRequireGenMatching = True
if self.do_sync:
mcClosure_match = mcClosure_regex.match(lepton_selection_and_frWeight)
if lepton_selection_and_frWeight == 'Tight':
syncOutput = os.path.join(self.dirs[key_analyze_dir][DKEY_SYNC], '%s_%s_SR.root' % (self.channel, central_or_shift))
syncTree = 'syncTree_%s_SR' % self.channel
syncRequireGenMatching = True
elif lepton_selection_and_frWeight == 'Fakeable_wFakeRateWeights':
syncOutput = os.path.join(self.dirs[key_analyze_dir][DKEY_SYNC], '%s_%s_Fake.root' % (self.channel, central_or_shift))
syncTree = 'syncTree_%s_Fake' % self.channel
elif mcClosure_match:
mcClosure_type = mcClosure_match.group('type')
syncOutput = os.path.join(self.dirs[key_analyze_dir][DKEY_SYNC], '%s_%s_mcClosure_%s.root' % (self.channel, central_or_shift, mcClosure_type))
syncTree = 'syncTree_%s_mcClosure_%s' % (self.channel, mcClosure_type)
else:
continue
if syncTree and central_or_shift != "central":
syncTree = os.path.join(central_or_shift, syncTree)
syncRLE = ''
if self.do_sync and self.rle_select:
syncRLE = self.rle_select % syncTree
if not os.path.isfile(syncRLE):
logging.warning("Input RLE file for the sync is missing: %s; skipping the job" % syncRLE)
continue
if syncOutput:
self.inputFiles_sync['sync'].append(syncOutput)
cfgFile_modified_path = os.path.join(self.dirs[key_analyze_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % analyze_job_tuple)
rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], "rle_%s_%s_%s_%i.txt" % analyze_job_tuple) \
if self.select_rle_output else ""
histogramFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_HIST], "analyze_%s_%s_%s_%i.root" % analyze_job_tuple)
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
'cfgFile_modified' : cfgFile_modified_path,
'histogramFile' : histogramFile_path,
'logFile' : logFile_path,
'selEventsFileName_output' : rleOutputFile_path,
'electronSelection' : electron_selection,
'muonSelection' : muon_selection,
'apply_leptonGenMatching' : self.apply_leptonGenMatching,
'hadTauSelection_veto' : hadTauVeto_selection,
'applyFakeRateWeights' : self.applyFakeRateWeights if not lepton_selection == "Tight" else "disabled",
'central_or_shift' : central_or_shift,
'syncOutput' : syncOutput,
'syncTree' : syncTree,
'syncRLE' : syncRLE,
'syncRequireGenMatching' : syncRequireGenMatching,
'useNonNominal' : self.use_nonnominal,
'apply_hlt_filter' : self.hlt_filter,
}
self.createCfg_analyze(self.jobOptions_analyze[key_analyze_job], sample_info, lepton_selection)
# initialize input and output file names for hadd_stage1
key_hadd_stage1_dir = getKey(process_name, lepton_selection_and_frWeight)
hadd_stage1_job_tuple = (process_name, lepton_selection_and_frWeight)
key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)
if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []
self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[key_hadd_stage1_job] = os.path.join(self.dirs[key_hadd_stage1_dir][DKEY_HIST],
"hadd_stage1_%s_%s.root" % hadd_stage1_job_tuple)
if self.do_sync: continue
if is_mc:
logging.info("Creating configuration files to run 'addBackgrounds' for sample %s" % process_name)
sample_categories = [ sample_category ]
if is_signal:
sample_categories = [ "signal", "ttH", "ttH_htt", "ttH_hww", "ttH_hzz", "ttH_hmm", "ttH_hzg" ]
for sample_category in sample_categories:
# sum non-fake and fake contributions for each MC sample separately
genMatch_categories = [ "nonfake", "conversions", "fake" ]
for genMatch_category in genMatch_categories:
key_hadd_stage1_job = getKey(process_name, lepton_selection_and_frWeight)
key_addBackgrounds_dir = getKey(process_name, lepton_selection_and_frWeight, "addBackgrounds")
addBackgrounds_job_tuple = None
processes_input = None
process_output = None
if genMatch_category == "nonfake":
# sum non-fake contributions for each MC sample separately
# input processes: TT3l0g0j,...
# output processes: TT; ...
if sample_category in [ "signal" ]:
lepton_genMatches = []
lepton_genMatches.extend(self.lepton_genMatches_nonfakes)
lepton_genMatches.extend(self.lepton_genMatches_conversions)
lepton_genMatches.extend(self.lepton_genMatches_fakes)
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in lepton_genMatches ]
elif sample_category in [ "ttH" ]:
lepton_genMatches = []
lepton_genMatches.extend(self.lepton_genMatches_nonfakes)
lepton_genMatches.extend(self.lepton_genMatches_conversions)
processes_input = []
processes_input.extend([ "%s%s" % ("ttH_htt", genMatch) for genMatch in lepton_genMatches ])
processes_input.extend([ "%s%s" % ("ttH_hww", genMatch) for genMatch in lepton_genMatches ])
processes_input.extend([ "%s%s" % ("ttH_hzz", genMatch) for genMatch in lepton_genMatches ])
processes_input.extend([ "%s%s" % ("ttH_hzg", genMatch) for genMatch in lepton_genMatches ])
processes_input.extend([ "%s%s" % ("ttH_hmm", genMatch) for genMatch in lepton_genMatches ])
else:
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in self.lepton_genMatches_nonfakes ]
process_output = sample_category
addBackgrounds_job_tuple = (process_name, sample_category, lepton_selection_and_frWeight)
elif genMatch_category == "conversions":
# sum fake contributions for each MC sample separately
# input processes: TT2l1g0j, TT1l2g0j, TT0l3g0j; ...
# output processes: TT_conversion; ...
if sample_category in [ "signal" ]:
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in self.lepton_genMatches_conversions ]
elif sample_category in [ "ttH" ]:
processes_input = []
processes_input.extend([ "%s%s" % ("ttH_htt", genMatch) for genMatch in self.lepton_genMatches_conversions ])
processes_input.extend([ "%s%s" % ("ttH_hww", genMatch) for genMatch in self.lepton_genMatches_conversions ])
processes_input.extend([ "%s%s" % ("ttH_hzz", genMatch) for genMatch in self.lepton_genMatches_conversions ])
processes_input.extend([ "%s%s" % ("ttH_hzg", genMatch) for genMatch in self.lepton_genMatches_conversions ])
processes_input.extend([ "%s%s" % ("ttH_hmm", genMatch) for genMatch in self.lepton_genMatches_conversions ])
else:
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in self.lepton_genMatches_conversions ]
process_output = "%s_conversion" % sample_category
addBackgrounds_job_tuple = (process_name, "%s_conversion" % sample_category, lepton_selection_and_frWeight)
elif genMatch_category == "fake":
# sum fake contributions for each MC sample separately
# input processes: TT2l0g1j, TT1l1g1j, TT1l0g2j, TT0l2g1j, TT0l1g2j, TT0l0g3j; ...
# output processes: TT_fake; ...
if sample_category in [ "signal" ]:
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in self.lepton_genMatches_fakes ]
elif sample_category in [ "ttH" ]:
processes_input = []
processes_input.extend([ "%s%s" % ("ttH_htt", genMatch) for genMatch in self.lepton_genMatches_fakes ])
processes_input.extend([ "%s%s" % ("ttH_hww", genMatch) for genMatch in self.lepton_genMatches_fakes ])
processes_input.extend([ "%s%s" % ("ttH_hzz", genMatch) for genMatch in self.lepton_genMatches_fakes ])
processes_input.extend([ "%s%s" % ("ttH_hzg", genMatch) for genMatch in self.lepton_genMatches_fakes ])
processes_input.extend([ "%s%s" % ("ttH_hmm", genMatch) for genMatch in self.lepton_genMatches_fakes ])
else:
processes_input = [ "%s%s" % (sample_category, genMatch) for genMatch in self.lepton_genMatches_fakes ]
process_output = "%s_fake" % sample_category
addBackgrounds_job_tuple = (process_name, "%s_fake" % sample_category, lepton_selection_and_frWeight)
if processes_input:
logging.info(" ...for genMatch option = '%s'" % genMatch_category)
key_addBackgrounds_job = getKey(*addBackgrounds_job_tuple)
cfgFile_modified = os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_%s_cfg.py" % addBackgrounds_job_tuple)
outputFile = os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s_%s.root" % addBackgrounds_job_tuple)
self.jobOptions_addBackgrounds[key_addBackgrounds_job] = {
'inputFile' : self.outputFile_hadd_stage1[key_hadd_stage1_job],
'cfgFile_modified' : cfgFile_modified,
'outputFile' : outputFile,
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], os.path.basename(cfgFile_modified).replace("_cfg.py", ".log")),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight) ],
'processes_input' : processes_input,
'process_output' : process_output
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds[key_addBackgrounds_job])
# initialize input and output file names for hadd_stage1_5
key_hadd_stage1_5_dir = getKey("hadd", lepton_selection_and_frWeight)
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight)
if not key_hadd_stage1_5_job in self.inputFiles_hadd_stage1_5:
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job] = []
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job].append(self.jobOptions_addBackgrounds[key_addBackgrounds_job]['outputFile'])
self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job] = os.path.join(self.dirs[key_hadd_stage1_5_dir][DKEY_HIST],
"hadd_stage1_5_%s.root" % lepton_selection_and_frWeight)
# add output files of hadd_stage1 for data to list of input files for hadd_stage1_5
if not is_mc:
key_hadd_stage1_job = getKey(process_name, lepton_selection_and_frWeight)
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight)
if not key_hadd_stage1_5_job in self.inputFiles_hadd_stage1_5:
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job] = []
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5_job].append(self.outputFile_hadd_stage1[key_hadd_stage1_job])
if self.do_sync: continue
# sum fake background contributions for the total of all MC sample
# input processes: TT2l0g1j, TT1l1g1j, TT1l0g2j, TT0l3j, TT0l3j, TT0l3j, TT0l3j; ...
# output process: fakes_mc
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight)
key_addBackgrounds_dir = getKey("addBackgrounds")
addBackgrounds_job_fakes_tuple = ("fakes_mc", lepton_selection_and_frWeight)
key_addBackgrounds_job_fakes = getKey(*addBackgrounds_job_fakes_tuple)
sample_categories = []
sample_categories.extend(self.nonfake_backgrounds)
sample_categories.extend([ "signal" ])
processes_input = []
for sample_category in sample_categories:
processes_input.append("%s_fake" % sample_category)
self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_cfg.py" % addBackgrounds_job_fakes_tuple),
'outputFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s.root" % addBackgrounds_job_fakes_tuple),
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], "addBackgrounds_%s_%s.log" % addBackgrounds_job_fakes_tuple),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight) ],
'processes_input' : processes_input,
'process_output' : "fakes_mc"
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes])
# sum conversion background contributions for the total of all MC sample
# input processes: TT2l0g1j, TT1l1g1j, TT1l0g2j, TT0l3j, TT0l3j, TT0l3j, TT0l3j; ...
# output process: conversions
addBackgrounds_job_conversions_tuple = ("conversions", lepton_selection_and_frWeight)
key_addBackgrounds_job_conversions = getKey(*addBackgrounds_job_conversions_tuple)
sample_categories = []
sample_categories.extend(self.nonfake_backgrounds)
sample_categories.extend([ "signal" ])
processes_input = []
for sample_category in sample_categories:
processes_input.append("%s_conversion" % sample_category)
self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_conversions] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_CFGS], "addBackgrounds_%s_%s_cfg.py" % addBackgrounds_job_conversions_tuple),
'outputFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_HIST], "addBackgrounds_%s_%s.root" % addBackgrounds_job_conversions_tuple),
'logFile' : os.path.join(self.dirs[key_addBackgrounds_dir][DKEY_LOGS], "addBackgrounds_%s_%s.log" % addBackgrounds_job_conversions_tuple),
'categories' : [ getHistogramDir(lepton_selection, lepton_frWeight) ],
'processes_input' : processes_input,
'process_output' : "conversions"
}
self.createCfg_addBackgrounds(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_conversions])
# initialize input and output file names for hadd_stage2
key_hadd_stage1_5_job = getKey(lepton_selection_and_frWeight)
key_hadd_stage2_dir = getKey("hadd", lepton_selection_and_frWeight)
key_hadd_stage2_job = getKey(lepton_selection_and_frWeight)
if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []
if lepton_selection == "Tight":
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes]['outputFile'])
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_conversions]['outputFile'])
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job])
self.outputFile_hadd_stage2[key_hadd_stage2_job] = os.path.join(self.dirs[key_hadd_stage2_dir][DKEY_HIST],
"hadd_stage2_%s.root" % lepton_selection_and_frWeight)
if self.do_sync:
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_syncNtuple(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_syncNtuple(lines_makefile)
outputFile_sync_path = os.path.join(self.outputDir, DKEY_SYNC, '%s.root' % self.channel)
self.outputFile_sync['sync'] = outputFile_sync_path
self.targets.append(outputFile_sync_path)
self.addToMakefile_hadd_sync(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
logging.info("Creating configuration files to run 'addBackgroundFakes'")
key_hadd_stage1_5_job = getKey(get_lepton_selection_and_frWeight("Fakeable", "enabled"))
key_addFakes_job = getKey("fakes_data")
category_sideband = "ttZctrl_Fakeable_wFakeRateWeights"
self.jobOptions_addFakes[key_addFakes_job] = {
'inputFile' : self.outputFile_hadd_stage1_5[key_hadd_stage1_5_job],
'cfgFile_modified' : os.path.join(self.dirs[DKEY_CFGS], "addBackgroundLeptonFakes_cfg.py"),
'outputFile' : os.path.join(self.dirs[DKEY_HIST], "addBackgroundLeptonFakes.root"),
'logFile' : os.path.join(self.dirs[DKEY_LOGS], "addBackgroundLeptonFakes.log"),
'category_signal' : "ttZctrl_Tight",
'category_sideband' : category_sideband
}
self.createCfg_addFakes(self.jobOptions_addFakes[key_addFakes_job])
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"))
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(self.jobOptions_addFakes[key_addFakes_job]['outputFile'])
logging.info("Creating configuration files to run 'prepareDatacards'")
for histogramToFit in self.histograms_to_fit:
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"))
key_prep_dcard_dir = getKey("prepareDatacards")
prep_dcard_job_tuple = (self.channel, histogramToFit)
key_prep_dcard_job = getKey(histogramToFit)
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_CFGS], "prepareDatacards_%s_%s_cfg.py" % prep_dcard_job_tuple),
'datacardFile' : os.path.join(self.dirs[key_prep_dcard_dir][DKEY_DCRD], "prepareDatacards_%s_%s.root" % prep_dcard_job_tuple),
'histogramDir' : self.histogramDir_prep_dcard,
'histogramToFit' : histogramToFit,
'label' : None
}
self.createCfg_prep_dcard(self.jobOptions_prep_dcard[key_prep_dcard_job])
# add shape templates for the following systematic uncertainties:
# - 'CMS_ttHl_Clos_norm_e'
# - 'CMS_ttHl_Clos_shape_e'
# - 'CMS_ttHl_Clos_norm_m'
# - 'CMS_ttHl_Clos_shape_m'
key_prep_dcard_job = getKey(histogramToFit)
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"))
key_add_syst_fakerate_dir = getKey("addSystFakeRates")
add_syst_fakerate_job_tuple = (self.channel, histogramToFit)
key_add_syst_fakerate_job = getKey(histogramToFit)
self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job] = {
'inputFile' : self.jobOptions_prep_dcard[key_prep_dcard_job]['datacardFile'],
'cfgFile_modified' : os.path.join(self.dirs[key_add_syst_fakerate_dir][DKEY_CFGS], "addSystFakeRates_%s_%s_cfg.py" % add_syst_fakerate_job_tuple),
'outputFile' : os.path.join(self.dirs[key_add_syst_fakerate_dir][DKEY_DCRD], "addSystFakeRates_%s_%s.root" % add_syst_fakerate_job_tuple),
'category' : self.channel,
'histogramToFit' : histogramToFit,
'plots_outputFileName' : os.path.join(self.dirs[DKEY_PLOT], "addSystFakeRates.png")
}
histogramDir_nominal = self.histogramDir_prep_dcard
for lepton_type in [ 'e', 'm' ]:
lepton_mcClosure = "Fakeable_mcClosure_%s" % lepton_type
if lepton_mcClosure not in self.lepton_selections:
continue
lepton_selection_and_frWeight = get_lepton_selection_and_frWeight(lepton_mcClosure, "enabled")
key_addBackgrounds_job_fakes = getKey("fakes_mc", lepton_selection_and_frWeight)
histogramDir_mcClosure = self.mcClosure_dir[lepton_mcClosure]
self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job].update({
'add_Clos_%s' % lepton_type : ("Fakeable_mcClosure_%s" % lepton_type) in self.lepton_selections,
'inputFile_nominal_%s' % lepton_type : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'histogramName_nominal_%s' % lepton_type : "%s/sel/evt/fakes_mc/%s" % (histogramDir_nominal, histogramToFit),
'inputFile_mcClosure_%s' % lepton_type : self.jobOptions_addBackgrounds_sum[key_addBackgrounds_job_fakes]['outputFile'],
'histogramName_mcClosure_%s' % lepton_type : "%s/sel/evt/fakes_mc/%s" % (histogramDir_mcClosure, histogramToFit)
})
self.createCfg_add_syst_fakerate(self.jobOptions_add_syst_fakerate[key_add_syst_fakerate_job])
logging.info("Creating configuration files to run 'makePlots'")
key_hadd_stage2_job = getKey(get_lepton_selection_and_frWeight("Tight", "disabled"))
key_makePlots_dir = getKey("makePlots")
key_makePlots_job = getKey('')
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_%s_cfg.py" % self.channel),
'outputFile' : os.path.join(self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_%s.png" % self.channel),
'histogramDir' : self.histogramDir_prep_dcard,
'label' : "t#bar{t}Z control region",
'make_plots_backgrounds' : self.make_plots_backgrounds
}
self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.sbatchFile_analyze = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.createScript_sbatch_analyze(self.executable_analyze, self.sbatchFile_analyze, self.jobOptions_analyze)
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_addBackgrounds)
self.sbatchFile_addBackgrounds = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addBackgrounds_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addBackgrounds, self.sbatchFile_addBackgrounds, self.jobOptions_addBackgrounds)
self.sbatchFile_addBackgrounds_sum = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addBackgrounds_sum_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addBackgrounds, self.sbatchFile_addBackgrounds_sum, self.jobOptions_addBackgrounds_sum)
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_addFakes)
self.sbatchFile_addFakes = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_addFakes_%s.py" % self.channel)
self.createScript_sbatch(self.executable_addFakes, self.sbatchFile_addFakes, self.jobOptions_addFakes)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
self.addToMakefile_add_syst_fakerate(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
if output_filenames:
if len(basedirs) != len(output_filenames):
raise ValueError(
"The number of output file names (%d) does not coincide w/ the number of "
"input base directories (%d); either drop the list of output filenames or "
"provide the exact same number of output file names as input base directories" % \
(len(output_filenames), len(basedirs))
)
for output_filename in output_filenames:
output_dir = os.path.dirname(output_filename)
if not os.path.isdir(output_dir):
logging.debug('Directory %s does not exist' % output_dir)
if args.force:
create_if_not_exists(output_dir)
else:
raise ValueError(
'Use -f/--force to create the output directory %s' %
output_dir)
for basedir_idx, basedir in enumerate(basedirs):
logging.info('Finding sum of weights for %s' % basedir)
filenames = get_filelist(basedir)
weight_map = collections.OrderedDict()
for filename in filenames:
assert (exists(filename))
neg_weights = collections.OrderedDict()
logging.debug('Processing %s ...' % filename)
events = Events(filename)
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for key in self.dirs.keys():
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [ "additional_signal_overlap", "background_data_estimate" ]:
continue
process_name = sample_info["process_name_specific"]
logging.info("Creating configuration files to run '%s' for sample %s" % (self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"]
apply_genWeight = sample_info["apply_genWeight"] if (is_mc and "apply_genWeight" in sample_info.keys()) else False
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc
for charge_selection in self.charge_selections:
for central_or_shift in self.central_or_shifts:
inputFileList = generateInputFileList(sample_name, sample_info, self.max_files_per_job, self.debug)
for jobId in inputFileList.keys():
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttH") and sample_category != "signal":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttW") and sample_category != "TTW":
continue
if central_or_shift.startswith("CMS_ttHl_thu_shape_ttZ") and sample_category != "TTZ":
continue
key_dir = getKey(sample_name, charge_selection)
key_file = getKey(sample_name, charge_selection, central_or_shift, jobId)
self.ntupleFiles[key_file] = inputFileList[jobId]
self.cfgFiles_analyze_modified[key_file] = os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, charge_selection, central_or_shift, jobId))
self.histogramFiles[key_file] = os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" % \
(process_name, charge_selection, central_or_shift, jobId))
self.logFiles_analyze[key_file] = os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % \
(self.channel, process_name, charge_selection, central_or_shift, jobId))
self.createCfg_analyze(self.ntupleFiles[key_file], self.histogramFiles[key_file], sample_category, self.era, triggers,
charge_selection, self.jet_minPt, self.jet_maxPt, self.jet_minAbsEta, self.jet_maxAbsEta, self.hadTau_selections, self.absEtaBins,
is_mc, central_or_shift, lumi_scale, apply_genWeight, apply_trigger_bits, self.cfgFiles_analyze_modified[key_file])
if self.is_sbatch:
logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_analyze)
self.createScript_sbatch()
logging.info("Creating configuration files for executing 'comp_jetToTauFakeRate'")
for charge_selection in self.charge_selections:
self.histogramFile_comp_jetToTauFakeRate[charge_selection] = os.path.join(
self.outputDir, DKEY_HIST, "comp_jetToTauFakeRate_%s.root" % charge_selection)
self.histogramDir_numerator[charge_selection] = "jetToTauFakeRate_%s/numerator/" % charge_selection
self.histogramDir_denominator[charge_selection] = "jetToTauFakeRate_%s/denominator/" % charge_selection
self.cfgFile_comp_jetToTauFakeRate_modified[charge_selection] = os.path.join(
self.outputDir, DKEY_CFGS, "comp_jetToTauFakeRate_%s_cfg.py" % charge_selection)
self.createCfg_comp_jetToTauFakeRate(self.histogramFile_hadd_stage1, self.histogramFile_comp_jetToTauFakeRate[charge_selection],
self.histogramDir_denominator[charge_selection], self.histogramDir_numerator[charge_selection], self.absEtaBins, self.ptBins,
self.cfgFile_comp_jetToTauFakeRate_modified[charge_selection])
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_comp_jetToTauFakeRate(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done")
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(process_name)
for dir_type in [DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" %
numDirectories)
numDirectories_created = 0
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100 * numDirectories_created >= frac * numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_info, self.max_files_per_job)
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
##print "processing sample %s: jobId = %i" % (process_name, jobId)
# build config files for executing analysis code
key_analyze_dir = getKey(process_name)
analyze_job_tuple = (process_name, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning(
"No input ntuples for %s --> skipping job !!" %
(key_analyze_job))
continue
cfgFile_modified_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_CFGS],
"analyze_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_LOGS],
"analyze_%s_%i.log" % analyze_job_tuple)
histogramFile_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_HIST],
"analyze_%s_%i.root" % analyze_job_tuple)
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles': ntupleFiles,
'cfgFile_modified': cfgFile_modified_path,
'histogramFile': histogramFile_path,
'histogramDir': 'analyze_hadTopTagger',
'logFile': logFile_path,
'hadTauSelection': self.hadTau_selection,
'lumiScale': 1.,
'selectBDT': True,
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job], sample_info)
# initialize input and output file names for hadd_stage1
key_hadd_stage1_dir = getKey(process_name,
lepton_selection_and_frWeight)
key_hadd_stage1_job = getKey(process_name)
if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1_job] = []
self.inputFiles_hadd_stage1[key_hadd_stage1_job].append(
self.jobOptions_analyze[key_analyze_job]['histogramFile'])
self.outputFile_hadd_stage1[
key_hadd_stage1_job] = os.path.join(
self.dirs[key_hadd_stage1_dir][DKEY_HIST],
"hadd_stage1_%s.root" % process_name)
self.targets.append(
self.outputFile_hadd_stage1[key_hadd_stage1_job])
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info("Creating Makefile")
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
# for charge_selection in self.charge_selections: ## NO CHARGE SELECTION NEEDED HERE
# key_dir = getKey(process_name, charge_selection) ## NO CHARGE SELECTION NEEDED HERE
key_dir = getKey(process_name)
for dir_type in [DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
# self.dirs[key_dir][dir_type] = os.path.join(self.configDir, dir_type, self.channel,
# "_".join([ charge_selection ]), process_name) ## NO CHARGE SELECTION NEEDED HERE
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, process_name)
else:
# self.dirs[key_dir][dir_type] = os.path.join(self.outputDir, dir_type, self.channel,
# "_".join([ charge_selection ]), process_name) ## NO CHARGE SELECTION NEEDED HERE
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, process_name)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_HIST, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_HADD_RT
]: ## DKEY_PLOT TO BE ADDED LATER
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
print "self.dirs = ", self.dirs
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
else:
create_if_not_exists(self.dirs[key])
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_name, sample_info, self.max_files_per_job, self.debug)
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"] or sample_info["sample_category"] in [
"additional_signal_overlap", "background_data_estimate"
]:
continue
process_name = sample_info["process_name_specific"]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
lumi_scale = 1. if not (self.use_lumi and is_mc) else sample_info[
"xsection"] * self.lumi / sample_info["nof_events"]
apply_genWeight = sample_info["apply_genWeight"] if (
is_mc and "apply_genWeight" in sample_info.keys()) else False
sample_category = sample_info["sample_category"]
triggers = sample_info["triggers"]
apply_trigger_bits = (
is_mc and
(self.era == "2015" or
(self.era == "2016" and sample_info["reHLT"]))) or not is_mc
# for charge_selection in self.charge_selections: ## NO CHARGE SELECTION NEEDED HERE
for central_or_shift in self.central_or_shifts:
inputFileList = inputFileLists[sample_name]
for jobId in inputFileList.keys():
if central_or_shift != "central" and not is_mc:
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttH"
) and sample_category != "signal":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttW"
) and sample_category != "TTW":
continue
if central_or_shift.startswith(
"CMS_ttHl_thu_shape_ttZ"
) and sample_category != "TTZ":
continue
# build config files for executing analysis code
# key_dir = getKey(process_name, charge_selection) ## NO CHARGE SELECTION NEEDED HERE
key_dir = getKey(process_name)
# key_analyze_job = getKey(process_name, charge_selection, central_or_shift, jobId) ## NO CHARGE SELECTION NEEDED HERE
key_analyze_job = getKey(process_name, central_or_shift,
jobId)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
print "Warning: ntupleFiles['%s'] = %s --> skipping job !!" % (
key_job, ntupleFiles)
continue
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles' : ntupleFiles,
# 'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%s_%i_cfg.py" % \
# (self.channel, process_name, charge_selection, central_or_shift, jobId)), ## NO CHARGE SELECTION NEEDED HERE
# 'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%s_%i.root" % \
# (process_name, charge_selection, central_or_shift, jobId)), ## NO CHARGE SELECTION NEEDED HERE
# 'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%s_%i.log" % \
# (self.channel, process_name, charge_selection, central_or_shift, jobId)), ## NO CHARGE SELECTION NEEDED HERE
'cfgFile_modified' : os.path.join(self.dirs[key_dir][DKEY_CFGS], "analyze_%s_%s_%s_%i_cfg.py" % \
(self.channel, process_name, central_or_shift, jobId)),
'histogramFile' : os.path.join(self.dirs[key_dir][DKEY_HIST], "%s_%s_%i.root" % \
(process_name, central_or_shift, jobId)),
'logFile' : os.path.join(self.dirs[key_dir][DKEY_LOGS], "analyze_%s_%s_%s_%i.log" % \
(self.channel, process_name, central_or_shift, jobId)),
'sample_category' : sample_category,
'triggers' : sample_info["triggers"],
# 'charge_selection' : charge_selection, ## NO CHARGE SELECTION NEEDED HERE
# 'jet_minPt' : self.jet_minPt,
# 'jet_maxPt' : self.jet_maxPt,
# 'jet_minAbsEta' : self.jet_minAbsEta,
# 'jet_maxAbsEta' : self.jet_maxAbsEta,
# 'hadTau_selections' : self.hadTau_selections,
'absEtaBins_e' : self.absEtaBins_e,
'absEtaBins_mu' : self.absEtaBins_mu,
'absPtBins_e' : self.absPtBins_e,
'absPtBins_mu' : self.absPtBins_mu,
##'use_HIP_mitigation_mediumMuonId' : sample_info["use_HIP_mitigation_mediumMuonId"],
'use_HIP_mitigation_mediumMuonId' : True,
'is_mc' : is_mc,
'central_or_shift' : central_or_shift,
'lumi_scale' : 1. if not (self.use_lumi and is_mc) else sample_info["xsection"] * self.lumi / sample_info["nof_events"],
'apply_genWeight' : sample_info["genWeight"] if (is_mc and "genWeight" in sample_info.keys()) else False,
'apply_trigger_bits' : (is_mc and (self.era == "2015" or (self.era == "2016" and sample_info["reHLT"]))) or not is_mc,
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job])
# initialize input and output file names for hadd_stage1
# key_hadd_stage1 = getKey(process_name, charge_selection)
key_hadd_stage1 = getKey(
process_name) ## NO CHARGE SELECTION NEEDED HERE
if not key_hadd_stage1 in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[key_hadd_stage1] = []
self.inputFiles_hadd_stage1[key_hadd_stage1].append(
self.jobOptions_analyze[key_analyze_job]
['histogramFile'])
# self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s_%s.root" % \
# (self.channel, process_name, charge_selection)) ## NO CHARGE SELECTION NEEDED HERE
self.outputFile_hadd_stage1[key_hadd_stage1] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage1_%s_%s.root" % \
(self.channel, process_name))
# initialize input and output file names for hadd_stage1_5
key_hadd_stage1_5 = getKey('')
if not key_hadd_stage1_5 in self.inputFiles_hadd_stage1_5:
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5] = []
for key_hadd_stage1 in self.outputFile_hadd_stage1.keys():
self.inputFiles_hadd_stage1_5[key_hadd_stage1_5].append(
self.outputFile_hadd_stage1[key_hadd_stage1])
self.outputFile_hadd_stage1_5[key_hadd_stage1_5] = os.path.join(
self.dirs[DKEY_HIST], "histograms_harvested_stage1_5.root")
## Creating configuration files to run 'addBackgrounds_LeptonFakeRate' [stage 1.5]
key_addBackgrounds_job = getKey('')
self.jobOptions_addBackgrounds_LeptonFakeRate[
key_addBackgrounds_job] = {
'inputFile':
self.outputFile_hadd_stage1_5[key_hadd_stage1_5],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
os.path.basename(
self.cfgFile_addBackgrounds_LeptonFakeRate)),
'outputFile':
os.path.join(self.dirs[DKEY_HIST],
"addBackground_LeptonFakeRate.root"),
'logFile':
os.path.join(
self.dirs[DKEY_LOGS],
os.path.basename(
self.cfgFile_addBackgrounds_LeptonFakeRate.replace(
"_cfg.py", ".log"))),
}
self.createCfg_addBackgrounds_LeptonFakeRate(
self.
jobOptions_addBackgrounds_LeptonFakeRate[key_addBackgrounds_job])
# initialize input and output file names for hadd_stage2
# key_hadd_stage2 = getKey(charge_selection) ## NO CHARGE SELECTION NEEDED HERE
# if not key_hadd_stage2 in self.inputFiles_hadd_stage2: ## NO CHARGE SELECTION NEEDED HERE
# self.inputFiles_hadd_stage2[key_hadd_stage2] = [] ## NO CHARGE SELECTION NEEDED HERE
# self.inputFiles_hadd_stage2[key_hadd_stage2].append(self.outputFile_hadd_stage1[key_hadd_stage1]) ## NO CHARGE SELECTION NEEDED HERE
# self.outputFile_hadd_stage2[key_hadd_stage2] = os.path.join(self.dirs[DKEY_HIST], "histograms_harvested_stage2_%s_%s.root" % \ ## NO CHARGE SELECTION NEEDED HERE
# (self.channel, charge_selection)) ## NO CHARGE SELECTION NEEDED HERE
key_hadd_stage2 = getKey('')
if not key_hadd_stage2 in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2] = []
for key_hadd_stage1_5 in self.outputFile_hadd_stage1_5.keys():
self.inputFiles_hadd_stage2[key_hadd_stage2].append(
self.outputFile_hadd_stage1_5[key_hadd_stage1_5])
self.inputFiles_hadd_stage2[key_hadd_stage2].append(
self.jobOptions_addBackgrounds_LeptonFakeRate[
key_addBackgrounds_job]['outputFile'])
self.outputFile_hadd_stage2[key_hadd_stage2] = os.path.join(
self.dirs[DKEY_HIST], "histograms_harvested_stage2.root")
if self.prep_dcard:
processesToCopy = []
signals = []
logging.info(
"Creating configuration files to run 'prepareDatacards_LeptonFakeRate'"
)
for process in self.prep_dcard_signals:
signals.append(process)
self.prep_dcard_signals = signals
for process in self.prep_dcard_processesToCopy:
processesToCopy.append(process)
self.prep_dcard_processesToCopy = processesToCopy
for histogramToFit in self.histograms_to_fit:
key_prep_dcard_job = getKey(histogramToFit)
self.jobOptions_prep_dcard[key_prep_dcard_job] = {
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"prepareDatacards_LeptonFakeRate_%s_cfg.py" %
(histogramToFit)),
'datacardFile':
os.path.join(self.dirs[DKEY_DCRD],
"prepareDatacards_%s.root" %
(histogramToFit)),
'histogramDir': (self.histogramDir_prep_dcard),
'histogramToFit':
histogramToFit,
'label':
None
}
# self.createCfg_prep_dcard(self.jobOptions_prep_dcard[key_prep_dcard_job]) ## DEF LINE
self.createCfg_prep_dcard_LeptonFakeRate(
self.jobOptions_prep_dcard[key_prep_dcard_job])
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
# self.createScript_sbatch()
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
self.sbatchFile_addBackgrounds_LeptonFakeRate = os.path.join(
self.dirs[DKEY_SCRIPTS],
"sbatch_addBackgrounds_LeptonFakeRate_%s.py" % self.channel)
self.createScript_sbatch(
self.executable_addBackgrounds_LeptonFakeRate,
self.sbatchFile_addBackgrounds_LeptonFakeRate,
self.jobOptions_addBackgrounds_LeptonFakeRate)
# logging.info("Creating script for submitting '%s' jobs to batch system" % self.executable_comp_jetToTauFakeRate)
# self.sbatchFile_comp_jetToTauFakeRate = os.path.join(self.dirs[DKEY_SCRIPTS], "sbatch_comp_jetToTauFakeRate.py")
# self.createScript_sbatch(self.executable_comp_jetToTauFakeRate, self.sbatchFile_comp_jetToTauFakeRate, self.jobOptions_comp_jetToTauFakeRate)
#### FAKE RATE COMP BLOCK COMMENTED OUT ########################
# logging.info("Creating configuration files for executing 'comp_jetToTauFakeRate'")
# for charge_selection in self.charge_selections:
# key_comp_jetToTauFakeRate_job = getKey(charge_selection)
# key_hadd_stage2 = getKey(charge_selection)
# self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job] = {
# 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2],
# 'cfgFile_modified' : os.path.join(
# self.dirs[DKEY_CFGS], "comp_jetToTauFakeRate_%s_cfg.py" % charge_selection),
# 'outputFile' : os.path.join(
# self.dirs[DKEY_HIST], "comp_jetToTauFakeRate_%s.root" % charge_selection),
# 'looseRegion' : "jetToTauFakeRate_%s/denominator/" % charge_selection,
# 'tightRegion' : "jetToTauFakeRate_%s/numerator/" % charge_selection,
# 'absEtaBins' : self.absEtaBins,
# 'ptBins' : self.ptBins
# }
# self.createCfg_comp_jetToTauFakeRate(self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job])
# self.targets.append(self.jobOptions_comp_jetToTauFakeRate[key_comp_jetToTauFakeRate_job]['outputFile'])
# logging.info("Creating configuration files to run 'makePlots'")
# for charge_selection in self.charge_selections:
# key_makePlots_job = getKey(charge_selection)
# key_hadd_stage2 = getKey(charge_selection)
# self.jobOptions_make_plots[key_makePlots_job] = {
# 'executable' : self.executable_make_plots,
# 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2],
# 'cfgFile_modified' : os.path.join(
# self.dirs[DKEY_CFGS], "makePlots_%s_cfg.py" % self.channel),
# 'outputFile' : os.path.join(
# self.dirs[DKEY_PLOT], "makePlots_%s.png" % self.channel),
# 'histogramDir' : "jetToTauFakeRate_%s" % charge_selection,
# 'label' : None,
# 'make_plots_backgrounds' : [ "TT", "TTW", "TTZ", "EWK", "Rares" ],
# }
# self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
# self.cfgFile_make_plots = self.cfgFile_make_plots_denominator
# for absEtaBin in [ "absEtaLt1_5", "absEta1_5to9_9" ]:
# key_makePlots_job = getKey(charge_selection, absEtaBin, "denominator")
# key_hadd_stage2 = getKey(charge_selection)
# self.jobOptions_make_plots[key_makePlots_job] = {
# 'executable' : self.executable_make_plots,
# 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2],
# 'cfgFile_modified' : os.path.join(
# self.dirs[DKEY_CFGS], "makePlots_%s_%s_denominator_%s_cfg.py" % (self.channel, charge_selection, absEtaBin)),
# 'outputFile' : os.path.join(
# self.dirs[DKEY_PLOT], "makePlots_%s_%s_denominator_%s.png" % (self.channel, charge_selection, absEtaBin)),
# 'histogramDir' : "jetToTauFakeRate_%s/denominator/%s" % (charge_selection, absEtaBin),
# 'label' : None,
# 'make_plots_backgrounds' : [ "TT", "TTW", "TTZ", "EWK", "Rares" ],
# }
# self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
# for hadTau_selection in self.hadTau_selections:
# key_makePlots_job = getKey(charge_selection, absEtaBin, "numerator", hadTau_selection)
# key_hadd_stage2 = getKey(charge_selection)
# self.jobOptions_make_plots[key_makePlots_job] = {
# 'executable' : self.executable_make_plots,
# 'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2],
# 'cfgFile_modified' : os.path.join(
# self.dirs[DKEY_CFGS], "makePlots_%s_%s_numerator_%s_%s_cfg.py" % (self.channel, charge_selection, hadTau_selection, absEtaBin)),
# 'outputFile' : os.path.join(
# self.dirs[DKEY_PLOT], "makePlots_%s_%s_numerator_%s_%s.png" % (self.channel, charge_selection, hadTau_selection, absEtaBin)),
# 'histogramDir' : "jetToTauFakeRate_%s/numerator/%s/%s" % (charge_selection, hadTau_selection, absEtaBin),
# 'label' : None,
# 'make_plots_backgrounds' : [ "TT", "TTW", "TTZ", "EWK", "Rares" ],
# }
# self.createCfg_makePlots(self.jobOptions_make_plots[key_makePlots_job])
#########################################################
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
# self.addToMakefile_hadd_stage1_5(lines_makefile)
self.addToMakefile_backgrounds_from_data(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile)
self.addToMakefile_prep_dcard(lines_makefile)
# self.addToMakefile_comp_jetToTauFakeRate(lines_makefile) ## TO BE IMPLEMENTED LATER
# self.addToMakefile_make_plots(lines_makefile) ## TO BE IMPLEMENTED LATER
self.targets = [
outputFile for outputFile in self.outputFile_hadd_stage2.values()
]
self.createMakefile(lines_makefile)
logging.info("Done")
root_file.Close()
return True
def hadd(input_files, output_file):
cmd_str = 'hadd -f %s %s' % (output_file, ' '.join(input_files))
stdout, stderr = run_cmd(cmd_str, do_not_log=True, return_stderr=True)
if not stdout or stderr:
raise RuntimeError('Error: %s' % stderr)
output_root_dir = os.path.expanduser('~/sandbox/stitch_samples/root_files')
output_plot_dir = os.path.expanduser('~/sandbox/stitch_samples/plots')
for output_dir in [output_root_dir, output_plot_dir]:
create_if_not_exists(output_dir)
for sample_set_to_stich in samples_to_stitch:
binning_keys = filter(lambda key: key != 'inclusive',
sample_set_to_stich.keys())
sample_list = []
for key in sample_set_to_stich:
if key == 'inclusive':
sample_list.extend(sample_set_to_stich[key]['samples'])
else:
for binned_sample in sample_set_to_stich[key]:
sample_list.extend(binned_sample['samples'])
assert (len(sample_list) == len(set(sample_list)))
binning = {}
def __init__(
self,
configDir,
outputDir,
cfgFile_prodNtuple,
samples,
max_files_per_job,
era,
preselection_cuts,
leptonSelection,
hadTauWP,
check_output_files,
running_method,
version,
num_parallel_jobs,
pileup,
golden_json,
dry_run,
isDebug,
gen_matching_by_index,
use_nonnominal,
use_home,
skip_tools_step,
verbose=False,
pool_id='',
):
self.configDir = configDir
self.outputDir = outputDir
self.max_num_jobs = 200000
self.samples = samples
self.max_files_per_job = max_files_per_job
self.era = era
self.preselection_cuts = preselection_cuts
self.leptonSelection = leptonSelection
self.hadTauWP = hadTauWP
self.check_output_files = check_output_files
self.verbose = verbose
self.dry_run = dry_run
self.isDebug = isDebug
self.gen_matching_by_index = gen_matching_by_index
self.use_nonnominal = use_nonnominal
self.use_home = use_home
self.pileup = pileup
self.golden_json = golden_json
if running_method.lower() not in ["sbatch", "makefile"]:
raise ValueError("Invalid running method: %s" % running_method)
if not os.path.isfile(self.pileup):
raise ValueError('No such file: %s' % self.pileup)
self.pileup_histograms = get_pileup_histograms(self.pileup)
if not os.path.isfile(self.golden_json):
raise ValueError('No such file: %s' % self.golden_json)
self.running_method = running_method
self.is_sbatch = self.running_method.lower() == "sbatch"
self.is_makefile = not self.is_sbatch
self.makefile = os.path.join(self.configDir, "Makefile_prodNtuple")
self.num_parallel_jobs = num_parallel_jobs
self.skip_tools_step = skip_tools_step
self.pool_id = pool_id if pool_id else uuid.uuid4()
self.workingDir = os.getcwd()
logging.info("Working directory is: %s" % self.workingDir)
self.template_dir = os.path.join(os.getenv('CMSSW_BASE'), 'src',
'tthAnalysis', 'HiggsToTauTau',
'test', 'templates')
logging.info("Templates directory is: %s" % self.template_dir)
self.version = version
self.samples = samples
create_if_not_exists(self.configDir)
create_if_not_exists(self.outputDir)
self.stdout_file_path = os.path.join(self.configDir,
"stdout_prodNtuple.log")
self.stderr_file_path = os.path.join(self.configDir,
"stderr_prodNtuple.log")
self.sw_ver_file_cfg = os.path.join(self.configDir,
"VERSION_prodNtuple.log")
self.sw_ver_file_out = os.path.join(self.outputDir,
"VERSION_prodNtuple.log")
self.stdout_file_path, self.stderr_file_path, self.sw_ver_file_cfg, self.sw_ver_file_out = get_log_version(
(self.stdout_file_path, self.stderr_file_path,
self.sw_ver_file_cfg, self.sw_ver_file_out))
self.cfgFile_prodNtuple_original = os.path.join(
self.template_dir, cfgFile_prodNtuple)
self.sbatchFile_prodNtuple = os.path.join(self.configDir,
"sbatch_prodNtuple.py")
self.cfgFiles_prodNtuple_modified = {}
self.logFiles_prodNtuple = {}
self.inputFiles = {}
self.outputFiles = {}
self.filesToClean = []
self.dirs = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(sample_name)
for dir_type in [DKEY_CFGS, DKEY_NTUPLES, DKEY_LOGS]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, process_name)
for dir_type in [DKEY_CFGS, DKEY_LOGS]:
initDict(self.dirs, [dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type)
self.cvmfs_error_log = {}
self.executable = "produceNtuple.sh"
def create(self):
"""Creates all necessary config files and runs the complete analysis workfow -- either locally or on the batch system
"""
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
sample_category = sample_info["sample_category"]
is_mc = (sample_info["type"] == "mc")
logging.info("Building dictionaries for sample %s..." %
process_name)
for charge_selection in self.charge_selections:
central_or_shift_extensions = ["", "hadd", "addBackgrounds"]
central_or_shifts_extended = central_or_shift_extensions + self.central_or_shifts
for central_or_shift_or_dummy in central_or_shifts_extended:
process_name_extended = [process_name, "hadd"]
for process_name_or_dummy in process_name_extended:
if central_or_shift_or_dummy in [
"hadd"
] and process_name_or_dummy in ["hadd"]:
continue
if central_or_shift_or_dummy != "central" and central_or_shift_or_dummy not in central_or_shift_extensions:
if not is_mc:
continue
if not self.accept_central_or_shift(
central_or_shift_or_dummy, sample_info):
continue
key_dir = getKey(process_name_or_dummy,
charge_selection,
central_or_shift_or_dummy)
for dir_type in [
DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_RLES
]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel,
"_".join([charge_selection]),
process_name_or_dummy,
central_or_shift_or_dummy)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel,
"_".join([charge_selection]),
process_name_or_dummy)
for subdirectory in ["comp_jetToTauFakeRate", "makePlots"]:
key_dir = getKey(subdirectory)
for dir_type in [
DKEY_CFGS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT
]:
initDict(self.dirs, [key_dir, dir_type])
if dir_type in [DKEY_CFGS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT]:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, self.channel, subdirectory)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, self.channel, subdirectory)
for dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_HIST, DKEY_LOGS, DKEY_DCRD,
DKEY_PLOT, DKEY_HADD_RT
]:
initDict(self.dirs, [dir_type])
if dir_type in [
DKEY_CFGS, DKEY_SCRIPTS, DKEY_LOGS, DKEY_DCRD, DKEY_PLOT,
DKEY_HADD_RT
]:
self.dirs[dir_type] = os.path.join(self.configDir, dir_type,
self.channel)
else:
self.dirs[dir_type] = os.path.join(self.outputDir, dir_type,
self.channel)
numDirectories = 0
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
numDirectories += len(self.dirs[key])
else:
numDirectories += 1
logging.info("Creating directory structure (numDirectories = %i)" %
numDirectories)
numDirectories_created = 0
frac = 1
for key in self.dirs.keys():
if type(self.dirs[key]) == dict:
for dir_type in self.dirs[key].keys():
create_if_not_exists(self.dirs[key][dir_type])
numDirectories_created += len(self.dirs[key])
else:
create_if_not_exists(self.dirs[key])
numDirectories_created = numDirectories_created + 1
while 100 * numDirectories_created >= frac * numDirectories:
logging.info(" %i%% completed" % frac)
frac = frac + 1
logging.info("Done.")
inputFileLists = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
logging.info("Checking input files for sample %s" %
sample_info["process_name_specific"])
inputFileLists[sample_name] = generateInputFileList(
sample_info, self.max_files_per_job)
self.inputFileIds = {}
for sample_name, sample_info in self.samples.items():
if not sample_info["use_it"]:
continue
process_name = sample_info["process_name_specific"]
inputFileList = inputFileLists[sample_name]
logging.info(
"Creating configuration files to run '%s' for sample %s" %
(self.executable_analyze, process_name))
is_mc = (sample_info["type"] == "mc")
sample_category = sample_info["sample_category"]
for charge_selection in self.charge_selections:
for central_or_shift in self.central_or_shifts:
if central_or_shift != "central" and not is_mc:
continue
if not self.accept_central_or_shift(
central_or_shift, sample_info):
continue
# build config files for executing analysis code
key_analyze_dir = getKey(process_name, charge_selection,
central_or_shift)
for jobId in inputFileList.keys():
analyze_job_tuple = (process_name, charge_selection,
central_or_shift, jobId)
key_analyze_job = getKey(*analyze_job_tuple)
ntupleFiles = inputFileList[jobId]
if len(ntupleFiles) == 0:
logging.warning(
"No input ntuples for %s --> skipping job !!" %
(key_analyze_job))
continue
cfgFile_modified_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_CFGS],
"analyze_%s_%s_%s_%i_cfg.py" % analyze_job_tuple)
logFile_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_LOGS],
"analyze_%s_%s_%s_%i.log" % analyze_job_tuple)
histogramFile_path = os.path.join(
self.dirs[key_analyze_dir][DKEY_HIST],
"analyze_%s_%s_%s_%i.root" % analyze_job_tuple)
rleOutputFile_path = os.path.join(self.dirs[key_analyze_dir][DKEY_RLES], "rle_%s_%s_%s_%i.txt" % analyze_job_tuple) \
if self.select_rle_output else ""
self.jobOptions_analyze[key_analyze_job] = {
'ntupleFiles': ntupleFiles,
'cfgFile_modified': cfgFile_modified_path,
'histogramFile': histogramFile_path,
'logFile': logFile_path,
'chargeSelection': charge_selection,
'jet_minPt': self.jet_minPt,
'jet_maxPt': self.jet_maxPt,
'jet_minAbsEta': self.jet_minAbsEta,
'jet_maxAbsEta': self.jet_maxAbsEta,
'hadTau_selection_tight':
self.hadTau_selection_tight,
'hadTauSelection_denominator':
self.hadTau_selection_denominator,
'hadTauSelections_numerator':
self.hadTau_selections_numerator,
'trigMatchingOptions': self.trigMatchingOptions,
'selEventsFileName_output': rleOutputFile_path,
'absEtaBins': self.absEtaBins,
'decayModes': self.decayModes,
'central_or_shift': central_or_shift,
'central_or_shifts_local': [],
'apply_hlt_filter': self.hlt_filter,
}
self.createCfg_analyze(
self.jobOptions_analyze[key_analyze_job],
sample_info)
# initialize input and output file names for hadd_stage1
key_hadd_stage1_dir = getKey(process_name,
charge_selection)
hadd_stage1_job_tuple = (process_name,
charge_selection)
key_hadd_stage1_job = getKey(*hadd_stage1_job_tuple)
if not key_hadd_stage1_job in self.inputFiles_hadd_stage1:
self.inputFiles_hadd_stage1[
key_hadd_stage1_job] = []
self.inputFiles_hadd_stage1[
key_hadd_stage1_job].append(
self.jobOptions_analyze[key_analyze_job]
['histogramFile'])
self.outputFile_hadd_stage1[
key_hadd_stage1_job] = os.path.join(
self.dirs[key_hadd_stage1_dir][DKEY_HIST],
"hadd_stage1_%s_%s.root" %
hadd_stage1_job_tuple)
# initialize input and output file names for hadd_stage2
key_hadd_stage1_job = getKey(process_name, charge_selection)
key_hadd_stage2_dir = getKey("hadd", charge_selection)
key_hadd_stage2_job = getKey(charge_selection)
if not key_hadd_stage2_job in self.inputFiles_hadd_stage2:
self.inputFiles_hadd_stage2[key_hadd_stage2_job] = []
self.inputFiles_hadd_stage2[key_hadd_stage2_job].append(
self.outputFile_hadd_stage1[key_hadd_stage1_job])
self.outputFile_hadd_stage2[
key_hadd_stage2_job] = os.path.join(
self.dirs[key_hadd_stage2_dir][DKEY_HIST],
"hadd_stage2_%s.root" % charge_selection)
logging.info(
"Creating configuration files for executing 'comp_jetToTauFakeRate'"
)
for charge_selection in self.charge_selections:
charge_key = "comp_%s" % charge_selection
self.comp_input_files[charge_key] = []
for trigMatchingOption in self.trigMatchingOptions:
key_hadd_stage2_job = getKey(charge_selection)
key_comp_jetToTauFakeRate_dir = getKey("comp_jetToTauFakeRate")
key_comp_jetToTauFakeRate_job = getKey(charge_selection,
trigMatchingOption)
self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job] = {
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified':
os.path.join(
self.dirs[DKEY_CFGS],
"comp_jetToTauFakeRate_%s_%s_cfg.py" %
(charge_selection, trigMatchingOption)),
'outputFile':
os.path.join(
self.dirs[DKEY_HIST],
"comp_jetToTauFakeRate_%s_%s.root" %
(charge_selection, trigMatchingOption)),
'logFile':
os.path.join(
self.dirs[DKEY_LOGS],
"comp_jetToTauFakeRate_%s_%s.log" %
(charge_selection, trigMatchingOption)),
'looseRegion':
"jetToTauFakeRate_%s_%s/denominator/" %
(charge_selection, trigMatchingOption),
'tightRegion':
"jetToTauFakeRate_%s_%s/numerator/" %
(charge_selection, trigMatchingOption),
'absEtaBins':
self.absEtaBins,
'ptBins':
self.ptBins,
'decayModes':
self.decayModes,
'hadTauSelections':
self.hadTau_selections_numerator,
'trigMatchingOption':
trigMatchingOption,
'plots_outputFileName':
os.path.join(
self.dirs[key_comp_jetToTauFakeRate_dir]
[DKEY_PLOT], "comp_jetToTauFakeRate_%s.png" %
trigMatchingOption)
}
self.createCfg_comp_jetToTauFakeRate(
self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job])
comp_output = self.jobOptions_comp_jetToTauFakeRate[
key_comp_jetToTauFakeRate_job]['outputFile']
self.targets.append(comp_output)
self.comp_input_files[charge_key].append(comp_output)
self.comp_output_files[charge_key] = os.path.join(
self.dirs[DKEY_HIST],
"comp_jetToTauFakeRate_%s.root" % charge_selection)
logging.info("Creating configuration files to run 'makePlots'")
for charge_selection in self.charge_selections:
key_hadd_stage2_job = getKey(charge_selection)
key_makePlots_dir = getKey("makePlots")
key_makePlots_job = getKey(charge_selection)
self.jobOptions_make_plots[key_makePlots_job] = {
'executable':
self.executable_make_plots,
'inputFile':
self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified':
os.path.join(self.dirs[key_makePlots_dir][DKEY_CFGS],
"makePlots_%s_cfg.py" % self.channel),
'outputFile':
os.path.join(self.dirs[key_makePlots_dir][DKEY_PLOT],
"makePlots_%s.png" % self.channel),
'histogramDir':
"jetToTauFakeRate_%s" % charge_selection,
'label':
None,
'make_plots_backgrounds':
self.make_plots_backgrounds
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
for trigMatchingOption in self.trigMatchingOptions:
self.cfgFile_make_plots = self.cfgFile_make_plots_denominator
for absEtaBin in ["absEtaLt1_5", "absEta1_5to9_9"]:
key_hadd_stage2_job = getKey(charge_selection)
key_makePlots_job = getKey(charge_selection,
trigMatchingOption, absEtaBin,
"denominator")
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(
self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_%s_%s_%s_denominator_%s_cfg.py" % \
(self.channel, charge_selection, trigMatchingOption, absEtaBin)),
'outputFile' : os.path.join(
self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_%s_%s_%s_denominator_%s.png" % (self.channel, charge_selection, trigMatchingOption, absEtaBin)),
'histogramDir' : "jetToTauFakeRate_%s_%s/denominator/%s" % (charge_selection, trigMatchingOption, absEtaBin),
'label' : None,
'make_plots_backgrounds' : self.make_plots_backgrounds
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
for hadTau_selection_numerator in self.hadTau_selections_numerator:
key_hadd_stage2_job = getKey(charge_selection)
key_makePlots_job = getKey(charge_selection,
trigMatchingOption,
absEtaBin, "numerator",
hadTau_selection_numerator)
self.jobOptions_make_plots[key_makePlots_job] = {
'executable' : self.executable_make_plots,
'inputFile' : self.outputFile_hadd_stage2[key_hadd_stage2_job],
'cfgFile_modified' : os.path.join(
self.dirs[key_makePlots_dir][DKEY_CFGS], "makePlots_%s_%s_%s_numerator_%s_%s_cfg.py" % \
(self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),
'outputFile' : os.path.join(
self.dirs[key_makePlots_dir][DKEY_PLOT], "makePlots_%s_%s_%s_numerator_%s_%s.png" % \
(self.channel, charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin)),
'histogramDir' : "jetToTauFakeRate_%s_%s/numerator/%s/%s" % (charge_selection, trigMatchingOption, hadTau_selection_numerator, absEtaBin),
'label' : None,
'make_plots_backgrounds' : self.make_plots_backgrounds
}
self.createCfg_makePlots(
self.jobOptions_make_plots[key_makePlots_job])
self.sbatchFile_analyze = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_analyze_%s.py" % self.channel)
self.sbatchFile_comp_jetToTauFakeRate = os.path.join(
self.dirs[DKEY_SCRIPTS], "sbatch_comp_jetToTauFakeRate.py")
if self.is_sbatch:
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_analyze)
self.createScript_sbatch_analyze(self.executable_analyze,
self.sbatchFile_analyze,
self.jobOptions_analyze)
logging.info(
"Creating script for submitting '%s' jobs to batch system" %
self.executable_comp_jetToTauFakeRate)
self.createScript_sbatch(self.executable_comp_jetToTauFakeRate,
self.sbatchFile_comp_jetToTauFakeRate,
self.jobOptions_comp_jetToTauFakeRate)
lines_makefile = []
self.addToMakefile_analyze(lines_makefile)
self.addToMakefile_hadd_stage1(lines_makefile)
self.addToMakefile_hadd_stage2(lines_makefile,
make_dependency="phony_hadd_stage1",
max_mem='4096M')
self.addToMakefile_comp_jetToTauFakeRate(lines_makefile)
self.addToMakefile_comp_hadd(lines_makefile)
self.addToMakefile_make_plots(lines_makefile)
self.createMakefile(lines_makefile)
logging.info("Done.")
return self.num_jobs
def __init__(
self,
configDir,
outputDir,
output_file,
executable,
projection_module,
samples,
max_files_per_job,
era,
plot,
check_output_files,
running_method,
num_parallel_jobs,
pool_id='',
verbose=False,
dry_run=False,
use_home=False,
submission_cmd=None,
):
self.configDir = configDir
self.outputDir = outputDir
self.executable = executable
self.projection_module = projection_module
self.max_num_jobs = 200000
self.samples = samples
self.max_files_per_job = max_files_per_job
self.era = era
self.plot = plot
self.check_output_files = check_output_files
self.verbose = verbose
self.dry_run = dry_run
self.use_home = use_home
if running_method.lower() not in ["sbatch", "makefile"]:
raise ValueError("Invalid running method: %s" % running_method)
self.running_method = running_method
self.is_sbatch = self.running_method.lower() == "sbatch"
self.is_makefile = not self.is_sbatch
self.makefile = os.path.join(
self.configDir, "Makefile_{}".format(self.projection_module))
self.num_parallel_jobs = num_parallel_jobs
self.pool_id = pool_id if pool_id else uuid.uuid4()
self.workingDir = os.getcwd()
logging.info("Working directory is: %s" % self.workingDir)
self.template_dir = os.path.join(os.getenv('CMSSW_BASE'), 'src',
'tthAnalysis', 'HiggsToTauTau',
'test', 'templates')
logging.info("Templates directory is: %s" % self.template_dir)
create_if_not_exists(self.configDir)
create_if_not_exists(self.outputDir)
self.output_file = os.path.join(self.outputDir, output_file)
self.stdout_file_path = os.path.join(
self.configDir, "stdout_{}.log".format(self.projection_module))
self.stderr_file_path = os.path.join(
self.configDir, "stderr_{}.log".format(self.projection_module))
self.sw_ver_file_cfg = os.path.join(
self.configDir, "VERSION_{}.log".format(self.projection_module))
self.sw_ver_file_out = os.path.join(
self.outputDir, "VERSION_{}.log".format(self.projection_module))
self.submission_out = os.path.join(self.configDir, "SUBMISSION.log")
self.stdout_file_path, self.stderr_file_path, self.sw_ver_file_cfg, self.sw_ver_file_out, self.submission_out = get_log_version(
(self.stdout_file_path, self.stderr_file_path,
self.sw_ver_file_cfg, self.sw_ver_file_out, self.submission_out))
check_submission_cmd(self.submission_out, submission_cmd)
self.sbatchFile_projection = os.path.join(
self.configDir, "sbatch_{}.py".format(self.projection_module))
self.cfgFiles_projection = {}
self.logFiles_projection = {}
self.scriptFiles_projection = {}
self.jobOptions_sbatch = {}
self.inputFiles = {}
self.outputFiles_tmp = {}
self.outputFiles = {}
self.phoniesToAdd = []
self.filesToClean = []
self.targets = []
self.makefile_target = "sbatch_{}".format(self.projection_module)
self.dirs = {}
all_dirs = [
DKEY_CFGS, DKEY_HISTO_TMP, DKEY_HISTO, DKEY_PLOTS, DKEY_LOGS,
DKEY_SCRIPTS, DKEY_HADD_RT
]
cfg_dirs = [
DKEY_CFGS, DKEY_LOGS, DKEY_PLOTS, DKEY_SCRIPTS, DKEY_HADD_RT
]
ref_genWeightsFile = os.path.join(
os.environ['CMSSW_BASE'], 'src', 'tthAnalysis', 'HiggsToTauTau',
'data', 'refGenWeight_{}.txt'.format(self.era))
self.ref_genWeights = load_refGenWeightsFromFile(
ref_genWeightsFile) if projection_module != 'puHist' else {}
for sample_name, sample_info in self.samples.items():
if not sample_info['use_it']:
continue
process_name = sample_info["process_name_specific"]
key_dir = getKey(process_name)
for dir_type in all_dirs:
if dir_type == DKEY_PLOTS:
continue
initDict(self.dirs, [key_dir, dir_type])
if dir_type in cfg_dirs:
self.dirs[key_dir][dir_type] = os.path.join(
self.configDir, dir_type, process_name)
else:
self.dirs[key_dir][dir_type] = os.path.join(
self.outputDir, dir_type, process_name)
for dir_type in cfg_dirs:
initDict(self.dirs, [dir_type])
self.dirs[dir_type] = os.path.join(self.configDir, dir_type)
self.cvmfs_error_log = {}
self.num_jobs = {
'hadd': 0,
'project': 0,
'plot': 0,
}
def __init__(self, outputDir, executable_analyze, channel, central_or_shifts,
max_files_per_job, era, use_lumi, lumi, debug, running_method, num_parallel_jobs,
histograms_to_fit, executable_prep_dcard="prepareDatacards", executable_make_plots="makePlots"):
self.outputDir = outputDir
self.executable_analyze = executable_analyze
self.channel = channel
self.central_or_shifts = central_or_shifts
self.max_files_per_job = max_files_per_job
self.max_num_jobs = 20000
self.era = era
self.use_lumi = use_lumi
self.lumi = lumi
self.debug = debug
assert(running_method.lower() in [
"sbatch", "makefile"]), "Invalid running method: %s" % running_method
self.running_method = running_method
self.is_sbatch = False
self.is_makefile = False
if self.running_method.lower() == "sbatch":
self.is_sbatch = True
else:
self.is_makefile = True
self.makefile = os.path.join(
self.outputDir, "Makefile_%s" % self.channel)
self.num_parallel_jobs = num_parallel_jobs
self.histograms_to_fit = histograms_to_fit
self.executable_prep_dcard = executable_prep_dcard
self.prep_dcard_processesToCopy = [
"data_obs", "TT", "TTW", "TTZ", "EWK", "Rares"]
self.prep_dcard_signals = ["ttH_hww", "ttH_hzz", "ttH_htt"]
self.executable_make_plots = executable_make_plots
self.workingDir = os.getcwd()
print "Working directory is: " + self.workingDir
create_if_not_exists(self.outputDir)
self.stdout_file = codecs.open(os.path.join(
self.outputDir, "stdout_%s.log" % self.channel), 'w', 'utf-8')
self.stderr_file = codecs.open(os.path.join(
self.outputDir, "stderr_%s.log" % self.channel), 'w', 'utf-8')
self.dirs = {}
self.samples = {}
self.cfgFiles_analyze_modified = {}
self.logFiles_analyze = {}
self.sbatchFile_analyze = os.path.join(
self.outputDir, "sbatch_analyze_%s.py" % self.channel)
self.ntupleFiles = {}
self.histogramFiles = {}
self.inputFiles_hadd_stage1 = []
self.histogramFile_hadd_stage1 = os.path.join(
self.outputDir, DKEY_HIST, "histograms_harvested_stage1_%s.root" % self.channel)
self.inputFiles_hadd_stage1_5 = []
self.histogramFile_hadd_stage1_5 = os.path.join(
self.outputDir, DKEY_HIST, "histograms_harvested_stage1_5_%s.root" % self.channel)
self.inputFiles_hadd_stage2 = []
self.histogramFile_hadd_stage2 = os.path.join(
self.outputDir, DKEY_HIST, "histograms_harvested_stage2_%s.root" % self.channel)
self.datacardFiles = {}
self.cfgFile_prep_dcard_original = os.path.join(
self.workingDir, "prepareDatacards_cfg.py")
self.cfgFile_prep_dcard_modified = {}
self.histogramDir_prep_dcard = None
self.make_plots_backgrounds = ["TT", "TTW", "TTZ", "EWK", "Rares"]
self.make_plots_signal = "signal"
self.cfgFile_make_plots_original = os.path.join(
self.workingDir, "makePlots_cfg.py")
self.cfgFiles_make_plots_modified = []
self.filesToClean = []
self.rleOutputFiles = {}
self.rootOutputFiles = {}
self.rootOutputAux = {}
if era == '2015':
self.triggers_1e = ['HLT_BIT_HLT_Ele23_WPLoose_Gsf_v']
self.triggers_2e = [
'HLT_BIT_HLT_Ele17_Ele12_CaloIdL_TrackIdL_IsoVL_DZ_v']
self.triggers_1mu = [
'HLT_BIT_HLT_IsoMu20_v', 'HLT_BIT_HLT_IsoTkMu20_v']
self.triggers_2mu = ['HLT_BIT_HLT_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_v',
'HLT_BIT_HLT_Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZ_v']
self.triggers_1e1mu = ['HLT_BIT_HLT_Mu17_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL_v',
'HLT_BIT_HLT_Mu8_TrkIsoVVL_Ele17_CaloIdL_TrackIdL_IsoVL_v']
elif era == '2016':
# CV: HLT_Ele25_WPTight_Gsf_v* was prescaled during part of 2016
# Runs B-D, so use HLT_Ele27_eta2p1_WPLoose_Gsf_v in addition
self.triggers_1e = ['HLT_BIT_HLT_Ele25_WPTight_Gsf_v',
'HLT_BIT_HLT_Ele27_eta2p1_WPLoose_Gsf_v']
self.triggers_2e = [
'HLT_BIT_HLT_Ele23_Ele12_CaloIdL_TrackIdL_IsoVL_DZ_v']
self.triggers_1mu = [
'HLT_BIT_HLT_IsoMu22_v', 'HLT_BIT_HLT_IsoTkMu22_v']
self.triggers_2mu = ['HLT_BIT_HLT_Mu17_TrkIsoVVL_Mu8_TrkIsoVVL_DZ_v',
'HLT_BIT_HLT_Mu17_TrkIsoVVL_TkMu8_TrkIsoVVL_DZ_v']
self.triggers_1e1mu = ['HLT_BIT_HLT_Mu23_TrkIsoVVL_Ele12_CaloIdL_TrackIdL_IsoVL_v',
'HLT_BIT_HLT_Mu8_TrkIsoVVL_Ele23_CaloIdL_TrackIdL_IsoVL_v']
self.triggers_2tau = [
'HLT_BIT_HLT_DoubleMediumIsoPFTau35_Trk1_eta2p1_Reg_v*']
else:
raise ValueError(
"Invalid Configuration parameter 'era' = %s !!" % era)
self.cvmfs_error_log = {}