diff --git a/HHbbgg_flow/__pycache__/__init__.cpython-311.pyc b/HHbbgg_flow/__pycache__/__init__.cpython-311.pyc new file mode 100644 index 0000000..e682edc Binary files /dev/null and b/HHbbgg_flow/__pycache__/__init__.cpython-311.pyc differ diff --git a/HHbbgg_flow/__pycache__/__init__.cpython-39.pyc b/HHbbgg_flow/__pycache__/__init__.cpython-39.pyc new file mode 100644 index 0000000..7b9061d Binary files /dev/null and b/HHbbgg_flow/__pycache__/__init__.cpython-39.pyc differ diff --git a/HHbbgg_flow/analysis_manager/__init__.py b/HHbbgg_flow/analysis_manager/__init__.py index 61f8582..e69de29 100644 --- a/HHbbgg_flow/analysis_manager/__init__.py +++ b/HHbbgg_flow/analysis_manager/__init__.py @@ -1 +0,0 @@ -from .run_analysis import main as analysis_runner \ No newline at end of file diff --git a/HHbbgg_flow/analysis_manager/analysis.py b/HHbbgg_flow/analysis_manager/analysis.py new file mode 100644 index 0000000..abb0785 --- /dev/null +++ b/HHbbgg_flow/analysis_manager/analysis.py @@ -0,0 +1,10 @@ +import os, sys +from HHbbgg_flow.ttH_killer import process_ttH_vars, process_ttH_sideband +import logging +logger = logging.getLogger(__name__) + +def run_analysis(args): + if args.ttH_vars_bool: + process_ttH_vars(args.ttH_vars_config, args.out_pq_size, args.output_dir_path) + elif args.ttH_sideband_bool: + process_ttH_sideband(args.ttH_sideband_config, args.out_pq_size) diff --git a/HHbbgg_flow/condor/__init__.py b/HHbbgg_flow/condor/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/HHbbgg_flow/condor/exe_template.sh b/HHbbgg_flow/condor/exe_template.sh new file mode 100644 index 0000000..df35138 --- /dev/null +++ b/HHbbgg_flow/condor/exe_template.sh @@ -0,0 +1,31 @@ +#!/bin/bash + +# Set proxy +export X509_USER_PROXY=$PWD/GRID_PROXY + +# >>> conda initialize >>> +# !! Contents within this block are managed by 'conda init' !! +__conda_setup="$('/usr/bin/conda' 'shell.bash' 'hook' 2> /dev/null)" +if [ $? -eq 0 ]; then + eval "$__conda_setup" +else + if [ -f "/usr/etc/profile.d/conda.sh" ]; then + . "/usr/etc/profile.d/conda.sh" + else + export PATH="/usr/bin:$PATH" + fi +fi +unset __conda_setup + +mkdir -p HHbbgg # dir to unload the conda env +xrdcp root://cmseos.fnal.gov//store/user/idutta/HiggsDNA_env_vars_Run3/HHbbgg_conda_env.tar.gz . +tar -xf HHbbgg_conda_env.tar.gz -C HHbbgg +ls -lrth HHbbgg/*/* +source HHbbgg/bin/activate + +tar -xf hhbbgg-flow.tar.gz # dir to unload the HHbbggFlow repo contents +ls -lrth +python run_analysis.py + +#for i in *.parquet; do xrdcp -f $i root://cmseos.fnal.gov//store/user/idutta/HiggsDNA/EOS_OUTPUT_DIR/SAMPLE/JOB/$i; rm -rf *.parquet; done +#for i in *summary*; do xrdcp -f $i root://cmseos.fnal.gov//store/user/idutta/HiggsDNA/EOS_OUTPUT_DIR/SAMPLE/JOB/$i; rm -rf *summary*; done diff --git a/HHbbgg_flow/condor/submit_condor_jobs.py b/HHbbgg_flow/condor/submit_condor_jobs.py new file mode 100644 index 0000000..1fa8e5c --- /dev/null +++ b/HHbbgg_flow/condor/submit_condor_jobs.py @@ -0,0 +1,110 @@ +import json +import os, sys +import math +import subprocess +import shutil, fileinput + +# Define the maximum number of files to process per job (as defined in `run_analysis.py`) +FILES_PER_JOB = 5 # Adjust this value as needed + + +# Get user proxy +status, proxy_info = subprocess.getstatusoutput("voms-proxy-info") +proxy_info = proxy_info.split('\n') +for line in proxy_info: + if "path" in line: + user_proxy = line.split(":")[-1].strip() + + +xrd_analysis_tarfile= "/uscms/home/idutta/nobackup/HiggsDNA_central_Run3/HHbbggFlow/hhbbgg-flow.tar.gz" +python_file="/uscms/home/idutta/nobackup/HiggsDNA_central_Run3/HHbbggFlow/scripts/run_analysis.py" +executable="exe_template.sh" +req_memory= "4096" +req_disk="10000" +req_ncpus="1" + +# Path to the original SMsamples.json file +samples_file = '../metadata/samples/SMsamples.json' +samples_to_run = { + "Run3_2022postEE" : { + "ttHToGG" : ["nominal"] + }, + "Run3_2022preEE" : { + "ttHToGG" : ["nominal"] + } +} +# Load the JSON data +with open(samples_file, 'r') as f: + samples_data = json.load(f) + +# Create output directories for job scripts and JSON files +output_dir = 'job_samples/' +os.makedirs(output_dir, exist_ok=True) +exe_dir = 'job_executables/' +os.makedirs(exe_dir, exist_ok=True) +log_dir='job_logs/' +os.makedirs(log_dir, exist_ok=True) + +# Prepare job list +job_list = [] + +# Split the samples into smaller JSON files +for era, sample_names in samples_to_run.items(): + for sname, s_types in sample_names.items(): + for stype in s_types: + files = samples_data['data_eras'][era]['samples'][sname]['files'][stype] + num_jobs = math.ceil(len(files) / FILES_PER_JOB) + + for job_index in range(num_jobs): + # Calculate file range for this job + start_index = job_index * FILES_PER_JOB + end_index = start_index + FILES_PER_JOB + job_files = files[start_index:end_index] + + # Create new JSON structure + job_sample_info = { + sname: { + 'xs': samples_data['data_eras'][era]['samples'][sname]['xs'], + 'bf': samples_data['data_eras'][era]['samples'][sname]['bf'], + 'files': { + stype: job_files + } + , } + } + + # Write to a new JSON file + job_json_file = os.path.join(output_dir, f'{era}_{sname}_{stype}_job_{job_index}.json') + with open(job_json_file, 'w') as jf: + json.dump(job_sample_info, jf, indent=4) + + # Add to job list + job_list.append(job_json_file) + output_file = os.path.join(log_dir, f'{era}_{sname}_{stype}_job_{job_index}.out') + error_file = os.path.join(log_dir, f'{era}_{sname}_{stype}_job_{job_index}.err') + log_file = os.path.join(log_dir, f'{era}_{sname}_{stype}_job_{job_index}.log') + + # Create a job_exe.sh script for this job + job_jdl_file = os.path.join(exe_dir, f'{era}_{sname}_{stype}_job_{job_index}.jdl') + shutil.copyfile("submit_template.txt",job_jdl_file) + for line in fileinput.FileInput(job_jdl_file, inplace=1): + line=line.replace("GRID_PROXY", user_proxy) + line=line.replace("XRD_ANALYSIS_TARFILE",xrd_analysis_tarfile) + line=line.replace("CONFIG_FILE",job_json_file) + line=line.replace("PYTHON_FILE",python_file) + line=line.replace("EXECUTABLE",executable) + line=line.replace("OUTPUT",output_file) + line=line.replace("ERROR",error_file) + line=line.replace("LOG",log_file) + line=line.replace("REQ_MEMORY",req_memory) + line=line.replace("REQ_DISK",req_disk) + line=line.replace("REQ_NCPUS",req_ncpus) + print(line.rstrip()) + + submitCommand = "condor_submit "+job_jdl_file + print(submitCommand) + os.system(submitCommand) + +# Write job list to file +with open('sample_jobs.txt', 'w') as jf: + for job_file in job_list: + jf.write(f"HHbbgg_flow/condor/{job_file}\n") diff --git a/HHbbgg_flow/condor/submit_template.txt b/HHbbgg_flow/condor/submit_template.txt new file mode 100644 index 0000000..4d328e9 --- /dev/null +++ b/HHbbgg_flow/condor/submit_template.txt @@ -0,0 +1,15 @@ +universe = vanilla +should_transfer_files = Yes ++SingularityImage = "/cvmfs/unpacked.cern.ch/registry.hub.docker.com/coffeateam/coffea-dask:latest" + +transfer_input_files = GRID_PROXY, XRD_ANALYSIS_TARFILE, CONFIG_FILE, PYTHON_FILE +executable = EXECUTABLE +output = OUTPUT +error = ERROR +log = LOG + +RequestMemory = REQ_MEMORY +RequestDisk = REQ_DISK +RequestCpus = REQ_NCPUS + +queue 1 diff --git a/HHbbgg_flow/metadata/samples/SMsamples.json b/HHbbgg_flow/metadata/samples/SMsamples.json new file mode 100644 index 0000000..f0f8bb4 --- /dev/null +++ b/HHbbgg_flow/metadata/samples/SMsamples.json @@ -0,0 +1,3056 @@ +{ + "data_eras" : { + "Run3_2022postEE" : { + "lumi" : 26.6717, + "file_prefix" : "/eos/uscms/store/group/lpcdihiggsboost/tsievert/HiggsDNA_parquet/v1", + "samples" : { + "ttHToGG" : { + "xs" : 506.5, + "bf" : 0.00228, + "files" : { + "nominal" : [ + "0d264dfc-666d-11ee-aef7-0166210abeef_%2FEvents%3B1_0-2625.parquet", + "136ea416-6780-11ee-a3c5-b004640abeef_%2FEvents%3B1_0-6762.parquet", + "38ac79b0-6785-11ee-bedb-a718000abeef_%2FEvents%3B1_0-22509.parquet", + "3d8dee46-6799-11ee-8603-020013acbeef_%2FEvents%3B1_0-13340.parquet", + 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import load_config import awkward as ak import pyarrow.parquet as pq import vector as vec @@ -14,7 +14,7 @@ # lxplus_fileprefix = "/eos/cms/store/group/phys_b2g/HHbbgg/HiggsDNA_parquet/v1" # LPC_FILEPREFIX = "/eos/uscms/store/group/lpcdihiggsboost/tsievert/HiggsDNA_parquet/v1" FILEPREFIX = str() -OUTPUT_DIRPATH = f'{str(Path().absolute())}/../../ttH_killer_vars_output' +OUTPUT_DIRPATH = f'{str(Path().absolute())}/ttH_killer_vars_output' FORCE_RERUN = False DEBUG = False @@ -248,97 +248,49 @@ def deltaR_bjet_lepton(sample, lepton_type='lead', bjet_type='lead'): if 'puppiMET_eta' not in set(sample.fields): sample['puppiMET_eta'] = [-999 for _ in range(ak.num(sample['event'], axis=0))] -def main(config: dict, out_pq_size: float): +def main(config: dict, out_pq_size: float, outdir=OUTPUT_DIRPATH): """ Runs the script to compute the ttH-Killer variables """ - dir_lists = {data_era: list() for data_era in config['data_eras']} - - for data_era in dir_lists.keys(): - run_samples = [] - if os.path.exists(FILEPREFIX+'/'+data_era+'/processing_output.json'): - with open(FILEPREFIX+'/'+data_era+'/processing_output.json', 'r') as f: - processing_output = json.load(f) - if processing_output['config_json'] == config and not FORCE_RERUN: - run_samples = processing_output['run_samples'] - - dir_lists[data_era] = list( - ( - set(config["samples"]) & set(os.listdir(FILEPREFIX+'/'+data_era)) - ) - set(run_samples) - ) - - # MC Era: total era luminosity [fb^-1] # - luminosities = {'Run3_2022preEE': 7.9804, 'Run3_2022postEE': 26.6717} + check_config_json(config) + config = load_config(config) + data_eras = config.get('data_eras', {}) - # Name: cross section [fb] @ sqrrt{s}=13.6 TeV & m_H=125.09 GeV # - # -> Do we not need to care about other HH processes? https://arxiv.org/pdf/1910.00012.pdf - cross_sections = { - # https://twiki.cern.ch/twiki/bin/view/LHCPhysics/LHCHWGHH?redirectedfrom=LHCPhysics.LHCHXSWGHH#Current_recommendations_for_HH_c - 'GluGluToHH': 34.43*0.0026, - # https://xsdb-temp.app.cern.ch/xsdb/?columns=37748736¤tPage=0&pageSize=10&searchQuery=DAS%3DGG-Box-3Jets_MGG-80_13p6TeV_sherpa - 'GGJets': 88750, - # https://xsdb-temp.app.cern.ch/xsdb/?columns=37748736¤tPage=0&pageSize=10&searchQuery=DAS%3DGJet_PT-20to40_DoubleEMEnriched_MGG-80_TuneCP5_13p6TeV_pythia8 - 'GJetPt20To40': 242500, - # https://xsdb-temp.app.cern.ch/xsdb/?columns=37748736¤tPage=0&pageSize=10&searchQuery=DAS%3DGJet_PT-40_DoubleEMEnriched_MGG-80_TuneCP5_13p6TeV_pythia8 - 'GJetPt40': 919100, - # https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt13TeV#gluon_gluon_Fusion_Process - 'GluGluHToGG': 48520*0.00228, - # https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt13TeV#ttH_Process - 'ttHToGG': 506.5*0.00228, - # https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt13TeV#VBF_Process - 'VBFHToGG': 3779*0.00228, - # https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt13TeV#WH_Process + https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt13TeV#ZH_Process - 'VHToGG': (1369 + 882.4)*0.00228, - } - for data_era in dir_lists.keys(): - for dir_name in dir_lists[data_era]: - if dir_name in cross_sections or re.match('Data', dir_name) is not None: - continue - cross_sections[dir_name] = 0.001 # set to 1e-3 [fb] for now, need to find actual numbers for many of these samples - - - for data_era, dir_list in dir_lists.items(): - for dir_name in dir_list: + for era,era_details in data_eras.items(): + for sample_name in era_details["samples"].keys(): for sample_type in ['nominal']: # Eventually change to os.listdir(LPC_FILEPREFIX+'/'+data_era+'/'+dir_name) # Load all the parquets of a single sample into an ak array sample = ak.concatenate( - [ak.from_parquet(FILEPREFIX+'/'+data_era+'/'+dir_name+'/'+sample_type+'/'+file) for file in os.listdir(FILEPREFIX+'/'+data_era+'/'+dir_name+'/'+sample_type+'/')] + [ak.from_parquet(era_details['file_prefix']+'/'+era+'/'+sample_name+'/'+sample_type+'/'+file) for file in era_details["samples"][sample_name]['files'][sample_type]] ) add_ttH_vars(sample) - if re.match('Data', dir_name) is None: + if re.match('Data', sample_name) is None: # Compute the sum of genWeights for proper MC rescaling. sample['sumGenWeights'] = sum( float(pq.read_table(file).schema.metadata[b'sum_genw_presel']) for file in glob.glob( - FILEPREFIX+'/'+data_era+'/'+dir_name+'/'+sample_type+'/*' + era_details['file_prefix']+'/'+era+'/'+sample_name+'/'+sample_type+'/*' ) ) - # Store luminostity computed from https://twiki.cern.ch/twiki/bin/viewauth/CMS/PdmVRun3Analysis # and summing over lumis of the same type (e.g. all 22EE era lumis summed). - sample['luminosity'] = luminosities[data_era] + sample['luminosity'] = era_details["lumi"] # If the process has a defined cross section, use defined xs otherwise use 1e-3 [fb] for now. - sample['cross_section'] = cross_sections[dir_name] + sample['cross_section'] = era_details["samples"][sample_name]["xs"]*era_details["samples"][sample_name]["bf"] # Define eventWeight array for hist plotting. sample['eventWeight'] = ak.where(sample['genWeight'] < 0, -1, 1) * (sample['luminosity'] * sample['cross_section'] / sample['sumGenWeights']) - - destdir = OUTPUT_DIRPATH + ('/' if OUTPUT_DIRPATH[-1] != '/' else '') - processed_parquet = ak.to_parquet(sample, destdir+dir_name+'_'+sample_type+'.parquet') + + destdir = outdir + ('/' if outdir[-1] != '/' else '') + if not os.path.exists(destdir): + # If it doesn't exist, create it + os.makedirs(destdir) + print(f"Directory '{destdir}' created.") + processed_parquet = ak.to_parquet(sample, destdir+era+'_'+sample_type+'.parquet') del sample - if DEBUG: - print('======================== \n', dir_name) - run_samples.append(dir_name) - with open(FILEPREFIX+'/'+data_era+'/processing_output.json', 'w') as f: - processing_output = { - 'run_samples': run_samples, - 'config_json': config - } - json.dump(processing_output, f) - + def check_config_json(config_json): if not os.path.exists(config_json): print("You provided a JSON filename, but the path doesn't exist. Maybe you mistyped the path?") @@ -347,7 +299,7 @@ def check_config_json(config_json): config = json.load(f) minimal_config_json = { - "data_eras", "samples", "file_prefix" + "data_eras" # Should we require they specify variables to compute? or we can assume all if not passed } if set(config.keys()) < minimal_config_json: @@ -357,38 +309,3 @@ def check_config_json(config_json): print(f"WARNING: You provided a valid JSON file, however it contains some extra (unused) keys: \n{set(config.keys()) - minimal_config_json}") return config - -if __name__ == '__main__': - parser = argparse.ArgumentParser( - description='Process the v1 HiggsDNA parquets to add the ttH-killer variables.' - ) - parser.add_argument('config_json', dest='config_json', action='store', - help='JSON file that defines how the computations should be performed, including what files to run over.' - ) - parser.add_argument('--dump', dest='output_dir_path', action='store', default=f'{str(Path().absolute())}/../../ttH_killer_vars_output', - help='Name of the output path in which the processed parquets will be stored.' - ) - parser.add_argument('-f', '--force', dest='FORCE_RERUN', action='store_true', - help='Forces the reprocessing to happen, even if the input config_json is identical to the previous processing.' - ) - parser.add_argument('-d', '--debug', dest='DEBUG', action='store_true', - help='Toggles whether or not to print debugging statements.' - ) - parser.add_argument('--output_parquet_size', dest='out_pq_size', action='store', - help='*NOT IMPLEMENTED YET* Specifies the approx. size (in MB) of the output parquets. Useful with large datasets that require multi-processing. Defaults to 1 parquet per sample.' - ) # Likely using Dask - https://stackoverflow.com/questions/63768642/pandas-df-to-parquet-write-to-multiple-smaller-files - - args = parser.parse_args() - # Logic for config_json argument - config = check_config_json(args.config_json) - # Global vars setting - FILEPREFIX = config['file_prefix'] - FORCE_RERUN = args.FORCE_RERUN - DEBUG = args.DEBUG - # Logic for output_dir_path argument - OUTPUT_DIRPATH = args.output_dir_path - if not os.path.exists(OUTPUT_DIRPATH): - os.makedirs(OUTPUT_DIRPATH) - out_pq_size = args.out_pq_size - - main(config, out_pq_size) diff --git a/HHbbgg_flow/utils/__init__.py b/HHbbgg_flow/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/HHbbgg_flow/utils/logger_utils.py b/HHbbgg_flow/utils/logger_utils.py new file mode 100644 index 0000000..9b1a73d --- /dev/null +++ b/HHbbgg_flow/utils/logger_utils.py @@ -0,0 +1,44 @@ +import logging +from rich.logging import RichHandler +from rich.console import Console + +LOGGER_NAME = "hhbbgg_flow" + +def setup_logger(level="INFO", logfile=None): + """Setup a logger that uses RichHandler to write the same message both in stdout + and in a log file called logfile. Level of information can be customized and + dumping a logfile is optional. + + :param level: level of information + :type level: str, optional + :param logfile: file where information are stored + :type logfile: str + """ + logger = logging.getLogger(LOGGER_NAME) # need to give it a name, otherwise *way* too much info gets printed out from e.g. numba + + # Set up level of information + possible_levels = ["INFO", "DEBUG"] + if level not in possible_levels: + raise ValueError("Passed wrong level for the logger. Allowed levels are: {}".format( + ', '.join(possible_levels))) + logger.setLevel(getattr(logging, level)) + + formatter = logging.Formatter("%(message)s") + + # Set up stream handler (for stdout) + stream_handler = RichHandler(show_time=False, rich_tracebacks=True) + stream_handler.setFormatter(formatter) + logger.addHandler(stream_handler) + + # Set up file handler (for logfile) + if logfile: + file_handler = RichHandler( + show_time=False, + rich_tracebacks=True, + console=Console(file=open(logfile, "wt")) + ) + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + return logger + diff --git a/HHbbgg_flow/utils/misc_utils.py b/HHbbgg_flow/utils/misc_utils.py new file mode 100644 index 0000000..5d8b91a --- /dev/null +++ b/HHbbgg_flow/utils/misc_utils.py @@ -0,0 +1,170 @@ +import os +import sys +import json +import copy + +import logging +logger = logging.getLogger(__name__) + +from higgs_dna.utils.metis_utils import do_cmd + +def load_config(config): + """ + Load a dictionary or path to json file into a dictionary. + + :param config: dictionary or path to json file with config options + :type config: dict/str + :return: config options as dictionary + :rtype: dict + """ + + if isinstance(config, dict): + return config + + elif isinstance(config, str): + if not config.endswith(".json"): + logger.warning("[load_config] : You specified a string, meaning we load config options from a json file, but %s does not look like a json file!" % config) + + with open(expand_path(config), "r") as f_in: + try: c = json.load(f_in) + except: raise RuntimeError("[load_config] : error loading file %s"%config) + else: return c + + else: + message = "[load_config] : You tried to load a config file with '%s' which has type <%s>, but only loading from json file () or are supported." % (str(config), str(type(config))) + logger.exception(message) + raise TypeError(message) + + +def get_module(module_name): + """ + Check if module has been imported. + Raises ImportError if not, otherwise returns the module. + + :param module_name: name of module in format "higgs_dna.module", e.g. "higgs_dna.systematics.lepton_systematics" + :type module_name: str + :return: corresponding module in higgs_dna + :rtype: module + """ + if module_name not in sys.modules: + logger.exception("[misc_utils : get_module] Module '%s' has not been imported. Please add 'import %s' to your analysis script" % (module_name, module_name)) + raise ImportError() + + return sys.modules[module_name] + + +def get_HiggsDNA_base(): + """ + Find the path up to and including /HiggsDNA. + Assumes that you are at least somewhere under /HiggsDNA + """ + return os.path.dirname(__file__)+"/../../" + + +def get_HiggsDNA_conda(): + """ + Find the absolute path to higgs-dna conda env. + """ + return os.path.abspath(do_cmd("echo $CONDA_PREFIX")) + + +def get_conda(): + """ + Find the absolute path to conda + """ + conda, hdna = os.path.split( + os.path.abspath( + do_cmd("echo $CONDA_PREFIX") + ) + ) + return conda + + +def expand_path(relative_path): + """ + Convert a relative path (assumed to be the path under HiggsDNA/) into an absolute path. + + :param relative_path: path under HiggsDNA/ + :type relative_path: str + :return: absolute path + :rtype: str + """ + + return os.path.dirname(__file__)+"/../../"+relative_path + + +def update_dict(original, new): + """ + Update nested dictionary (dictionary possibly containing dictionaries) + If a field is present in new and original, take the value from new. + If a field is present in new but not original, insert this field + + + :param original: source dictionary + :type original: dict + :param new: dictionary to take new values from + :type new: dict + :return: updated dictionary + :rtype: dict + """ + + updated = copy.deepcopy(original) + + for key, value in original.items(): + if key in new.keys(): + if isinstance(value, dict): + updated[key] = update_dict(value, new[key]) + else: + updated[key] = new[key] + + return updated + +def check_proxy(): + """ + Check if a valid grid proxy exists. + + :return: path to proxy if it exists, otherwise None + :rtype: str + """ + + proxy = None + bad_proxy = False + proxy_info = do_cmd("voms-proxy-info").split("\n") + for line in proxy_info: + if "path" in line: + proxy = line.split(":")[-1].strip() + + if "timeleft" in line: + time_left = int(line.replace("timeleft", "").replace(":", "").strip()) + if not time_left > 0: + bad_proxy = True + + if "Couldn't find a valid proxy." in line: + bad_proxy = True + + if proxy is None or bad_proxy: + logger.warning("[misc_utils : check_proxy] We were not able to find grid proxy or proxy was found to be expired. Output of 'voms-proxy-info': %s" % (str(proxy_info))) + return None + + else: + return os.path.abspath(proxy) + + +def create_chunks(lst, n): + """Yield successive n-sized chunks from lst.""" + chunks = [] + for i in range(0, len(lst), n): + chunks.append(lst[i:i+n]) + return chunks + + +def is_json_serializable(x): + """ + Returns True if `x` is json serializable, False if not + """ + try: + json.dumps(x) + return True + except: + return False + diff --git a/environment.yml b/environment.yml new file mode 100644 index 0000000..cdfd361 --- /dev/null +++ b/environment.yml @@ -0,0 +1,52 @@ +name: hhbbgg-flow +channels: + - conda-forge + - pytorch +dependencies: + - python>=3.6 + - ipython + - coffea~=0.7 + - uproot~=4.3 + - pyaml + - xrootd + - numba + - pyarrow + - pandas + - rich + - matplotlib~=3.8 + - jupyterlab~=4.0 + - vector + - conda-pack + - tqdm + - numpy~=1.23 + - pandas~=2.2 + - cuda-python~=11.8 + - ruamel.yaml + - xgboost==1.5.1 + - dask + - distributed + - dask-jobqueue + - sphinx + - breathe + - sphinx_rtd_theme + - sphinx-argparse + - nbsphinx + - ipywidgets + - nbconvert>=5.5.0 + - jinja2>=3.0.3 + - pandoc + - pytorch + - torchvision + - awkward>=1.10 + - hist~=2.7 + - mplhep~=0.3 + - pyarrow~=14.0 + - vector~=1.1 + - torchvision + - torchaudio + - scikit-learn~=1.4 + - scikit-optimize>=0.10 + - xgboost~=1.5 + - pip: + - zuko==1.0.1 + \ No newline at end of file diff --git a/makeSMsamplesJSON.sh b/makeSMsamplesJSON.sh new file mode 100644 index 0000000..5976bbc --- /dev/null +++ b/makeSMsamplesJSON.sh @@ -0,0 +1,112 @@ +#!/bin/bash + +# Define the base directory +BASE_DIR="/eos/uscms/store/group/lpcdihiggsboost/tsievert/HiggsDNA_parquet/v1" + +# Define output JSON file +OUTPUT_FILE="SMsamples.json" + +# Declare associative arrays for luminosity, cross-sections, and branching fractions +declare -A LUMI_VALUES=( + ["Run3_2022preEE"]="7.9804", + ["Run3_2022postEE"]="26.6717" + # Add more ERA values with their luminosities here +) + +declare -A XS_VALUES=( + #in fb + ["ttHToGG"]="506.5", + ["GluGluToHH"]="34.43", + ["GGJets"]="88750", + ["GJetPt20To40"]="242500", + ["GJetPt40"]="919100", + ["GluGluHToGG"]="48520", + ["VBFHToGG"]="3779", + ["VHToGG"]="2251.4", #1369 + 882.4 + ["Data_EraC"]="1", + ["Data_EraD"]="1", + ["Data_EraE"]="1", + ["Data_EraF"]="1", + ["Data_EraG"]="1" + # Add more SAMPLE values with their cross-section values here +) + +declare -A BF_VALUES=( + ["ttHToGG"]="0.00228", #htogg + ["GluGluToHH"]="0.00265", #hh to bbgg + ["GGJets"]="1", + ["GJetPt20To40"]="1", + ["GJetPt40"]="1", + ["GluGluHToGG"]="0.00228", + ["VBFHToGG"]="0.00228", + ["VHToGG"]="0.00228", + ["Data_EraC"]="1", + ["Data_EraD"]="1", + ["Data_EraE"]="1", + ["Data_EraF"]="1", + ["Data_EraG"]="1" + # Add more SAMPLE values with their branching fraction values here +) + +# Start building the JSON structure +echo "{" > $OUTPUT_FILE +echo ' "data_eras" : {' >> $OUTPUT_FILE + +# Loop through each ERA directory +for ERA in "${!LUMI_VALUES[@]}"; do + ERA_DIR="$BASE_DIR/$ERA" + + if [ -d "$ERA_DIR" ]; then + echo ' "'$ERA'" : {' >> $OUTPUT_FILE + echo ' "lumi" : '${LUMI_VALUES[$ERA]}',' >> $OUTPUT_FILE + echo ' "file_prefix" : "'$BASE_DIR'",' >> $OUTPUT_FILE + echo ' "samples" : {' >> $OUTPUT_FILE + + # Loop through each SAMPLE directory under ERA + for SAMPLE in "${!XS_VALUES[@]}"; do + SAMPLE_DIR="$ERA_DIR/$SAMPLE/nominal" + + if [ -d "$SAMPLE_DIR" ]; then + # Get the list of files + FILES=$(ls "$SAMPLE_DIR") + + # Start the sample's JSON entry + echo ' "'$SAMPLE'" : {' >> $OUTPUT_FILE + echo ' "xs" : '${XS_VALUES[$SAMPLE]}'' >> $OUTPUT_FILE + echo ' "bf" : '${BF_VALUES[$SAMPLE]}'' >> $OUTPUT_FILE + echo ' "files" : {' >> $OUTPUT_FILE + echo ' "nominal" : [' >> $OUTPUT_FILE + + # Loop through each file and add it to the JSON structure + for FILE in $FILES; do + echo ' "'$FILE'",' >> $OUTPUT_FILE + done + + # Remove the trailing comma from the last file entry + sed -i '$ s/,$//' $OUTPUT_FILE + + # Close the sample's JSON entry + echo ' ]' >> $OUTPUT_FILE + echo ' }' >> $OUTPUT_FILE + echo ' },' >> $OUTPUT_FILE + fi + done + + # Remove the trailing comma from the last sample entry + sed -i '$ s/,$//' $OUTPUT_FILE + + # Close the ERA's JSON entry + echo ' }' >> $OUTPUT_FILE + echo ' },' >> $OUTPUT_FILE + fi +done + +# Remove the trailing comma from the last ERA entry +sed -i '$ s/,$//' $OUTPUT_FILE + +# Close the JSON structure +echo ' }' >> $OUTPUT_FILE +echo "}" >> $OUTPUT_FILE + +# Notify the user +echo "JSON output written to $OUTPUT_FILE" diff --git a/HHbbgg_flow/analysis_manager/run_analysis.py b/scripts/run_analysis.py similarity index 56% rename from HHbbgg_flow/analysis_manager/run_analysis.py rename to scripts/run_analysis.py index 32c4476..13b23f7 100644 --- a/HHbbgg_flow/analysis_manager/run_analysis.py +++ b/scripts/run_analysis.py @@ -2,50 +2,58 @@ import os, sys from pathlib import Path sys.path.insert(1, os.getcwd()) -from HHbbgg_flow.ttH_killer import process_ttH_vars, process_ttH_sideband -def main( - ttH_vars_bool: bool = False, ttH_vars_config: dict = None, - tth_sideband_bool: bool = False, ttH_sideband_config: dict = None, - out_pq_size: float = 0 -): - if ttH_vars_bool: - process_ttH_vars(ttH_vars_config, out_pq_size) - elif tth_sideband_bool: - process_ttH_sideband(ttH_sideband_config, out_pq_size) +from HHbbgg_flow.analysis_manager import analysis +from HHbbgg_flow.utils.logger_utils import setup_logger +def main(args): + logger = setup_logger(args.log_level, args.log_file) + logger.debug("Running HHbbggFlow") + analysis.run_analysis(args) + if __name__ == '__main__': parser = argparse.ArgumentParser( description='Runs the analysis script.' ) - parser.add_argument('--ttH_vars', dest='ttH_vars_bool', action='store_true', + parser.add_argument('--ttH_vars', dest='ttH_vars_bool', required=False, action='store_true', default =False, help='Toggles whether or not to process ttH variables.' ) - parser.add_argument('--ttH_vars_config', dest='ttH_vars_config', action='store', + parser.add_argument('--ttH_vars_config', dest='ttH_vars_config', required=False, action='store', default =None, help='JSON file that defines how the ttH_vars computations should be performed, including what files to run over.' ) - parser.add_argument('--ttH_sideband', dest='ttH_sideband_bool', action='store_true', + parser.add_argument('--ttH_sideband', dest='ttH_sideband_bool', required=False, action='store_true', default = False, help='Toggles whether or not to print ttH sideband cuts.' ) - parser.add_argument('--ttH_sideband_config', dest='ttH_sideband_config', action='store', + parser.add_argument('--ttH_sideband_config', dest='ttH_sideband_config', required=False, action='store',default = None, help='JSON file that defines how the ttH_sideband computations should be performed, including what files to run over.' ) - parser.add_argument('--output_parquet_size', dest='out_pq_size', action='store', + parser.add_argument('--output_parquet_size', dest='out_pq_size', required=False, action='store', default = 0, help='*NOT IMPLEMENTED YET* Specifies the approx. size (in MB) of the output parquets. Useful with large datasets that require multi-processing. Defaults to 1 parquet per sample.' ) # Likely using Dask - https://stackoverflow.com/questions/63768642/pandas-df-to-parquet-write-to-multiple-smaller-files - parser.add_argument('--dump', dest='output_dir_path', action='store', default=f'{str(Path().absolute())}/../../analysis_output', + parser.add_argument('--outdir', dest='output_dir_path', action='store', default=f'{str(Path().absolute())}/analysis_output', help='Name of the output path in which the analysis output will be stored.' ) parser.add_argument('-d', '--debug', dest='DEBUG', action='store_true', help='Toggles whether or not to print debugging statements.' ) - args = parser.parse_args() + parser.add_argument("--condor", required=False, action='store_true', default=None, + help="option to run on condor" + ) + parser.add_argument( + "--log-level", + required=False, + default="INFO", + type=str, + help="Level of information printed by the logger") - main( - args.ttH_vars_bool, args.ttH_vars_config, - args.ttH_sideband_bool, args.ttH_sideband_config, - args.out_pq_size - ) + parser.add_argument( + "--log-file", + required=False, + type=str, + help="Name of the log file") + + args = parser.parse_args() + main(args)