def get_cluster(config_file_arg):
if io.file_exists(config_file_arg):
cluster_obj = cluster.read_cluster_data(config_file_arg)
else:
config_file = cluster.get_cluster_config(config_file_arg)
if config_file:
cluster_obj = cluster.read_cluster_data(config_file)
else:
print("Error finding cluster configuration file. Try passing the full path to the file.")
return
return cluster_obj
def process_commandline_arguments(cluster_obj):
print("Processing commandline arguments")
args = get_arguments()
cluster_obj = None
if None not in [
args.name, args.abundance, args.nH, args.redshift, args.obsids
]:
ciao.initialize_cluster(name=args.name,
obsids=args.obsids,
abundance=args.abundance,
redshift=args.redshift,
nH=args.nH)
if args.init_cluster:
cluster_obj.initialize_cluster()
if args.config_file != "":
if io.file_exists(args.config_file):
cluster_obj = cluster.read_cluster_data(args.config_file)
else:
config_file = cluster.get_cluster_config(args.config_file)
if config_file:
cluster_obj = cluster.read_cluster_data(config_file)
else:
print(
"Error finding cluster configuration file. Try passing the full path to the file."
)
return
if args.find_sources:
ciao.find_sources(cluster_obj, ecf=args.ecf, energy=args.energy)
if args.cont:
if cluster_obj is None:
cluster_obj = config.current_cluster()
if cluster_obj is None:
print("Cannot find a current working cluster.")
exit(-1)
if args.parallel and cluster_obj.last_step_completed == '1':
ciao.run_stage_2_parallel(cluster_obj, args)
else:
ciao.start_from_last(cluster_obj, args)
return cluster_obj
def process_commandline_arguments(cluster_obj):
print("Processing commandline arguments")
args = get_arguments()
cluster_obj = None
if io.file_exists(args.batch_file):
ciao.automated_cluster_init(args.batch_file)
if None not in [args.name, args.abundance, args.nH, args.redshift, args.obsids]:
ciao.initialize_cluster(name=args.name, obsids=args.obsids, abundance=args.abundance,
redshift=args.redshift, nH=args.nH)
if args.init_cluster:
cluster_obj.initialize_cluster()
if args.config_file != "":
if io.file_exists(args.config_file):
cluster_obj = cluster.read_cluster_data(args.config_file)
else:
config_file = cluster.get_cluster_config(args.config_file)
if config_file:
cluster_obj = cluster.read_cluster_data(config_file)
else:
print("Error finding cluster configuration file. Try passing the full path to the file.")
return
if args.cont:
if cluster_obj is None:
cluster_obj = config.current_cluster()
if cluster_obj is None:
print("Cannot find a current working cluster.")
exit(-1)
print("Continuing {}.".format(cluster_obj.name))
ciao.start_from_last(cluster_obj)
if args.download_data:
if 0 == cluster_obj.last_step_completed:
cluster_obj.get_cluster_info_from_user()
ciao.download_data(cluster_obj)
if args.remove_sources:
ciao.remove_sources(cluster_obj)
return cluster_obj
)
print(log_string)
log_file = "{super_comp_dir}/{p_name}_time.txt".format(
super_comp_dir=cluster_obj.super_comp_dir,
p_name=mp.current_process().name)
io.write_contents_to_file(log_string, log_file, False)
print("Manual garbage collection.")
gc.collect()
mp.Queue().put('Regions processed: {}'.format(len(regions_processed)))
if __name__ == '__main__':
args = get_arguments()
if args.cluster_config is not None:
clstr = cluster.read_cluster_data(args.cluster_config)
if args.cont:
print("Continuing spectral fits")
regions = clstr.unfinished_regions_to_fit(args.resolution)
original = len(clstr.scale_map_regions_to_fit(args.resolution))
print('{reg} of {orig} regions left to fit.'.format(
reg=len(regions), orig=original))
else:
clstr.initialize_best_fits_file()
clstr.initialize_worst_fits_file()
clstr.initialize_all_fits_file()
regions = clstr.scale_map_regions_to_fit(args.resolution)
start_time = time.time()
if args.parallel:
def change_current_cluster(cluster_config):
new_cluster = cluster.read_cluster_data(cluster_config)
config.set_current_cluster(new_cluster)
def current_cluster():
if current_cluster_file() is not None:
return cluster.read_cluster_data(current_cluster_file())
else:
return None