def test_predict(tmp_path):
indir = os.path.join(data_dir, 'deepmased_trained')
outdir = os.path.join(tmp_path, 'predict_cpu')
args = ['--cpu_only', '--data_path', indir, '--save_path', outdir]
args = Predict_CMD.parse_args(args)
Predict_CMD.main(args)
F = os.path.join(outdir, 'predictions', 'deepmased_trained',
'predictions.csv')
assert os.path.isfile(F)
def test_predict_default_model(tmpdir, caplog):
caplog.set_level(logging.INFO)
save_path = tmpdir.mkdir('save_dir')
args = [
'--cpu-only', '--save-path',
str(save_path),
os.path.join(data_dir, 'n10_r2/feature_files.tsv')
]
args = Predict_CMD.parse_args(args)
Predict_CMD.main(args)
def main(args=None):
"""Main entry point for application
"""
if args is None:
args = sys.argv[1:]
desc = 'DeepMAsED: Deep learning for Metagenome Assembly Error Detection'
epi = """DESCRIPTION:
Usage: DeepMAsED <subcommand> <subcommand_params>
Example: DeepMAsED train -h
For general info, see https://github.com/leylabmpi/DeepMAsED/
"""
parser = argparse.ArgumentParser(
description=desc,
epilog=epi,
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--version', action='version', version=__version__)
# subparsers
subparsers = parser.add_subparsers()
## train
train = Train.parse_args(subparsers=subparsers)
train.set_defaults(func=Train.main)
## predict
predict = Predict.parse_args(subparsers=subparsers)
predict.set_defaults(func=Predict.main)
## evaluate
evaluate = Evaluate.parse_args(subparsers=subparsers)
evaluate.set_defaults(func=Evaluate.main)
## evaluate
features = Features.parse_args(subparsers=subparsers)
features.set_defaults(func=Features.main)
# parsing args
if args:
args = parser.parse_args(args)
else:
args = parser.parse_args()
# running subcommands
if len(vars(args)) > 0:
args.func(args)
else:
parser.parse_args(['--help'])
def main(args=None):
"""Main entry point for application
"""
if args is None:
args = sys.argv[1:]
desc = 'Template python script'
epi = """DESCRIPTION:
Test
"""
parser = argparse.ArgumentParser(description=desc,
epilog=epi,
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument('--version', action='version', version='0.0.1')
# subparsers
subparsers = parser.add_subparsers()
## train
train = Train.parse_args(subparsers=subparsers)
train.set_defaults(func=Train.main)
## predict
predict = Predict.parse_args(subparsers=subparsers)
predict.set_defaults(func=Predict.main)
## evaluate
evaluate = Evaluate.parse_args(subparsers=subparsers)
evaluate.set_defaults(func=Evaluate.main)
# parsing args
if args:
args = parser.parse_args(args)
else:
args = parser.parse_args()
# running subcommands
if len(vars(args)) > 0:
args.func(args)
else:
parser.parse_args(['--help'])
def test_help():
args = ['-h']
with pytest.raises(SystemExit) as pytest_wrapped_e:
Predict_CMD.parse_args(args)
assert pytest_wrapped_e.type == SystemExit
assert pytest_wrapped_e.value.code == 0
def test_predict_r3(tmpdir):
out_path = tmpdir.mkdir('save_dir')
model_path = os.path.join(data_dir, 'n1000_r3/', 'model')
args = [os.path.join(data_dir, 'n1000_r3/'), '--cpu-only']
args = Predict_CMD.parse_args(args)
Predict_CMD.main(args)