def main():
debug = True
styled.HEADER('Start shapes for FF productions')
styled.HEADER('\n # 0 - prepareConfig')
config = analysis_shapes.prepareConfig(
analysis_shapes=analysis_shapes,
config_file='data/tes_config.yaml',
debug=debug
)
if debug:
import copy
config_old = copy.deepcopy(config)
# Changing the analysis config to correspond to ff shapes setup
config['shifts'] = ['nominal']
old_context = config['context_analysis'] # TODO: context and tags are the same
new_context = 'ff_shapes_' + config['context_analysis']
dict_replace(old=old_context, new=new_context, d=config)
if debug:
from python_wrappers.dictdiffer import DictDiffer
print DictDiffer(
new_dict=config,
old_dict=config_old,
show_none=False,
show_unchanged=False,
)
# Targeted analysis class should be passed
produce_shapes_variables(config=config)
styled.HEADER('End')
def main():
debug = False
logging.info(styled.HEADER('Start'))
# styled.HEADER('Start')
logging.info(styled.HEADER('# 0 - prepareConfig'))
config = analysis_shapes.prepareConfig(analysis_shapes=analysis_shapes,
config_file='data/tes_config.yaml',
debug=debug)
produce_shapes_variables(config=config)
logging.info(styled.HEADER('End'))
def main():
styled.HEADER('Start MSSM shapes production')
debug = False
styled.HEADER('\n # 1 - prepareConfig')
config = analysis_shapes_mssm.prepareConfig(
analysis_shapes=analysis_shapes_mssm,
config_file='data/mssm_legacy_mva_config.yaml',
debug=debug)
if 'yaml_conf' in config.keys() and config['yaml_conf'] is not None:
config = analysis_shapes_mssm.prepareConfig(
analysis_shapes=analysis_shapes_mt,
config_file=config['yaml_conf'],
debug=debug)
produce_shapes_variables(config=config)
styled.HEADER('End')
def produce_shapes_variables(config):
styled.HEADER('\n # 1 - init FF shapes production')
shapes = analysis_shapes(**config)
styled.HEADER('\n # 2 - setup_logging')
shapes.setup_logging(
output_file="{}_ff_shapes.log".format(shapes._tag),
level=config['log_level'],
logger=shapes._logger,
)
styled.HEADER('\n # 3 - era evaluation')
shapes.evaluateEra()
styled.HEADER('\n # 4 - import necessary estimation methods')
shapes.importEstimationMethods()
styled.HEADER('\n # 5 - evaluating channels (processes, variables,cattegories)')
shapes.evaluateChannels()
styled.HEADER('\n # 5.5 - invert isolation cuts')
for key in shapes.channels.keys():
shapes.channels[key].replace_all_cuts(name='tau_iso', value='byTightIsolationMVArun2017v2DBoldDMwLT2017_2<0.5')
styled.HEADER('\n # 6 - add systematics')
shapes.evaluateSystematics()
# return 0
styled.HEADER('\n # 7 - produce shapes')
shapes.produce()
styled.HEADER('\n # 8 - convert to synched shapes')
shapes_dir = os.path.join('/'.join(os.path.realpath(os.path.dirname(__file__)).split('/')[:-1]), 'converted_shapes')
output_file_name = convertToShapes(
input_path=shapes._output_file,
output_dir=os.path.join(shapes_dir, shapes._output_file[:-5]),
channels=['mt'],
context='_tes',
)
# styled.HEADER(, t '\n # 9 - implement the nominal ploting if you want', bcolors.ENDC
styled.HEADER('Output shapes:\n', output_file_name)
def main():
styled.HEADER('Start FES shapes production')
debug = True
styled.HEADER('\n # 1 - prepareConfig')
config = analysis_shapes_et.prepareConfig(
analysis_shapes=analysis_shapes_et,
config_file='data/et_fes_legacy2017_config.yaml',
debug=debug)
if config['context_analysis'] == 'mtFes':
config = analysis_shapes_mt.prepareConfig(
analysis_shapes=analysis_shapes_mt,
config_file='data/mt_fes_legacy_config.yaml',
debug=debug)
elif config['yaml_conf'] is not None:
config = analysis_shapes_et.prepareConfig(
analysis_shapes=analysis_shapes_mt,
config_file=config['yaml_conf'],
debug=debug)
produce_shapes_variables(config=config)
styled.HEADER('End')
def produce_shapes_variables(config):
logging.info(styled.HEADER('# 1 - init ControlShapes'))
shapes = analysis_shapes(**config)
logging.info(styled.HEADER('# 2 - setup_logging'))
handler, file_handler = shapes.setup_logging(
output_file="{}_controlshapes.log".format(shapes._tag),
level=config['log_level'],
logger=logging.getLogger(), # shapes._logger,
danger=False,
add_file_handler=False,
add_stream_handler=False,
)
# Disabling some printouts
# logging.getLogger('shape_producer').setLevel(log.INFO)
# logging.getLogger('shape_producer.systematics').setLevel(log.INFO)
# logging.getLogger('shape_producer.histogram').setLevel(log.INFO)
logging.getLogger('shape_producer.histogram').setLevel(log.DEBUG)
if handler is not None:
handler.setLevel(log.INFO)
# logging.getLogger('shape_producer.histogram').addHandler(handler)
if file_handler is not None:
file_handler.setLevel(log.DEBUG)
logging.info(styled.HEADER('# 3 - era evaluation'))
shapes.evaluateEra()
logging.info(styled.HEADER('# 4 - import necessary estimation methods'))
shapes.importEstimationMethods()
logging.info(styled.HEADER('# 5 - evaluating channels (processes, variables,cattegories)'))
shapes.evaluateChannels()
logging.info(styled.HEADER('# 6 - add systematics'))
shapes.evaluateSystematics()
logging.info(styled.HEADER('# 7 - produce shapes'))
shapes.produce()
# TODO: close the output file properly
logging.info(styled.HEADER('# 8 - convert to synched shapes'))
shapes_dir = os.path.join('/'.join(os.path.realpath(os.path.dirname(__file__)).split('/')[:-1]), 'converted_shapes')
output_file_name = convertToShapes(
input_path=shapes._output_file,
output_dir=os.path.join(shapes_dir, shapes._output_file[:-5]),
channels=['mt'],
variables=shapes.variables_names,
context='_control',
use_number_coding=False,
)
# logging.info(styled.HEADER( t '\n # 9 - implement the nominal ploting if you want'))
logging.info(styled.UNDERLINE(styled.HEADER('Output shapes:')))
if isinstance(output_file_name, string_types):
output_file_name = [output_file_name]
for o in output_file_name:
logging.info(styled.BOLD(styled.HEADER(o)))