def parse_args():
"""Parse incoming args.
:return argparse.Namespace: args"""
parser = common.get_default_parser("PyGame fractal viewer")
parser.add_argument(
"-t", "--terminate", action="store_true",
help="terminate window exactly after rendering.")
return parser.parse_args()
tag=tag,
show=show,
host=host)
downloaded.append(obj)
if not preserve_ccdb_structure:
print("Printing")
for i in downloaded:
j = i.split("/")[-2]
j = os.path.join(out_path, f"{j}.root")
print(i, "->", j)
os.rename(i, j)
if __name__ == "__main__":
parser = get_default_parser(
"Fetch data from CCDB"
"Basic example: `./fetch_output.py qc/TOF/MO/TaskRaw/hDiagnostic`")
parser.add_argument(
'ccdb_path',
metavar='path_to_object',
type=str,
help=
'Path of the object in the CCDB repository. If a `.txt` file is passed the all the file input is downloaded'
)
parser.add_argument(
'--timestamp',
"-t",
metavar='object_timestamp',
type=str,
default=["-1"],
nargs="+",
nnet.cuda()
criterion = nn.CrossEntropyLoss()
optimizer = th.optim.Adam(nnet.parameters(), lr=args.learning_rate)
train_dataset = THCHS30(root=args.data_dir, data_type='train', left_context=left_context,
right_context=right_context, model_type='cnn')
train_loader = data.DataLoader(dataset=train_dataset, batch_size=args.min_batch,
shuffle=True, num_workers=6)
test_dataset = THCHS30(root=args.data_dir, data_type='test', left_context=left_context,
right_context=right_context, model_type='cnn')
test_loader = data.DataLoader(dataset=test_dataset, batch_size=args.min_batch,
shuffle=True, num_workers=6)
cross_validate(-1, nnet, test_dataset, test_loader)
for epoch in range(args.num_epochs):
common.train_one_epoch(nnet, criterion, optimizer, train_loader)
cross_validate(epoch, nnet, test_dataset, test_loader)
th.save(nnet, common..join_path(args.checkout_dir, 'cnn.{}.pkl'.format(epoch + 1)))
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description="""Trains a simple CNN acoustic model using CE loss function""",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
conflict_handler='resolve',
parents=[common.get_default_parser()])
args = parser.parse_args()
print(args)
train(args)
msg("Merging", len(files_per_type[i]), "files to", merged_file)
run_cmd(
f"hadd -j {njobs} -f {merged_file} `cat {merge_file_list}`",
log_file=merge_file_list.replace(".txt", ".log"),
time_it=True,
comment=f"Merging to {merged_file}")
if len(merged_files) == 0:
warning_msg("Merged no files")
else:
msg("Merging completed, merged:",
*merged_files,
color=bcolors.BOKGREEN)
if __name__ == "__main__":
parser = get_default_parser(description="Runner for O2 analyses")
parser.add_argument(
"modes",
type=str,
nargs="+",
help="Running modes, as defined in the input configuration file")
parser.add_argument(
"--input",
"-i",
type=str,
nargs="+",
default=["listfiles.txt"],
help=
"Input file, can be in form of a list of AODs or a list of text files with the list of AODs"
)
parser.add_argument("--out_path",
bunched_aod_names[fn] = {
"out_aod": out_aod,
"file_index": i,
"total_files": len(bunched_files),
"input_size": bunched_sizes[i]
}
run_in_parallel(jobs,
run_merge,
list(bunched_aod_names.keys()),
job_message="Running AOD merging",
linearize_single_core=True)
if __name__ == "__main__":
parser = get_default_parser(__doc__)
parser.add_argument("input_files",
type=str,
nargs="+",
help="Input files to merge")
parser.add_argument(
"--max_bunch_size",
"--max",
"-m",
default=1000,
type=float,
help="Approximate maximum size of the bunch to merge in MB")
parser.add_argument("--output_path",
"-o",
default="./",
type=str,
run_cmd(f"mv {summaryfile} {output_path}")
run_cmd(f"ln -s {os.path.join(output_path, summaryfile)} ./")
if qa:
msg(" --- running test analysis", color=bcolors.HEADER)
run_cmd(
f"./diagnostic_tools/doanalysis.py TrackQA RICH TOF -i {output_list_file} -M 25 -B 25"
)
if tof_mismatch == 1: # TOF mismatch in create mode
run_cmd(
f"hadd -j {njobs} -f tofMM.root tof_mismatch_template_DF_*.root && rm tof_mismatch_template_DF_*.root"
)
if __name__ == "__main__":
parser = get_default_parser(description=__doc__)
parser.add_argument(
"configuration_file",
type=str,
help=
"Input configuration file e.g. you can use the provided default_configfile.ini or variations of it."
)
parser.add_argument(
"--entry",
"-e",
type=str,
default="DEFAULT",
help=
"Entry in the configuration file, e.g. the INEL or CCBAR entries in the configuration file."
)
parser.add_argument(
copyfile(i)
elif args.command == "copylist":
for i in input_files:
copylist(i, jobs=args.jobs)
elif args.command == "copied":
for i in input_files:
print(copied(i))
elif args.command == "merge_aod":
for i in input_files:
merge_aod(i, input_file=args.what)
else:
warning_msg("Did not do anything")
if __name__ == "__main__":
parser = get_default_parser(description=__doc__, njobs=False)
parser.add_argument(
"input_files",
type=str, # nargs="+",
help="List of files in .txt file or files to download")
# parser.add_argument("--input_files", "--input", "-i", type=str,# nargs="+",
# default=[],
# help="List of files in .txt file or files to download")
subparsers = parser.add_subparsers(dest='command', help='sub-commands')
def add_subp(fn, g=None):
if g is None:
g = subparsers.add_parser(fn.__name__, help=fn.__doc__)
a = inspect.getfullargspec(fn)
for i, j in enumerate(a.args):
d = a.defaults[i]
