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add download function to CLI
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This commit adds the download functionality to the CLI via dedicated arguments.
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@PeerHerholz
PeerHerholz committed Jan 13, 2023
1 parent 12668a7 commit 75fc9c3
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Showing 2 changed files with 109 additions and 88 deletions.
2 changes: 1 addition & 1 deletion bids_bep16_conv/datasets.py
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Original file line number Diff line number Diff line change
Expand Up @@ -204,7 +204,7 @@ def download_HBN(dataset_path=None):
if dataset_path is None:
path = Path(os.curdir + '/bids_bep16_datasets/HBN/derivatives/QSIprep/sub-NDAREK918EC2/ses-HBNsiteSI/dwi')
else:
path = Path(dataset_path + '/bids_bep16_datasets/HBN/derivatives/QSIprep/sub-NDAREK918EC2/ses-HBNsiteSI/dwi')
path = Path(str(dataset_path) + '/bids_bep16_datasets/HBN/derivatives/QSIprep/sub-NDAREK918EC2/ses-HBNsiteSI/dwi')

# in either case: check if path exists and if not, create it
if not path.exists():
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195 changes: 108 additions & 87 deletions bids_bep16_conv/run_bids_bep16_conv.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@
from pathlib import Path
from bids_bep16_conv.converters import dipy_dti, dipy_bep16, dipy_csd
from bids_bep16_conv.utils import validate_input_dir, create_dataset_description
from bids_bep16_conv.datasets import download_HBN
from bids import BIDSLayout


Expand Down Expand Up @@ -39,6 +40,14 @@ def get_parser():
help='Assume the input dataset is BIDS compliant and skip the validation \
(default: True).',
action="store_true")
parser.add_argument('--download_dataset',
help='Download example dataset. If this argument is set, no processing or'
'conversion will be performed but only the indicated example'
'dataset be download to the path indicated via --download_path',
choices=['HBN'])
parser.add_argument('--download_path',
help='Path where the example dataset should be downloaded to.',
action='store', type=Path)
parser.add_argument('-v', '--version', action='version',
version='BIDS-App version {}'.format(__version__))

Expand All @@ -60,100 +69,112 @@ def run_bids_bep16_conv():
else:
exec_env = 'local'

# check if BIDS validation should be run or skipped
if args.skip_bids_validation:
print("Input data will not be checked for BIDS compliance.")
else:
print("Making sure the input data is BIDS compliant "
"(warnings can be ignored in most cases).")
validate_input_dir(exec_env, args.bids_dir, args.participant_label)
if not args.download_dataset:

# check if BIDS validation should be run or skipped
if args.skip_bids_validation:
print("Input data will not be checked for BIDS compliance.")
else:
print("Making sure the input data is BIDS compliant "
"(warnings can be ignored in most cases).")
validate_input_dir(exec_env, args.bids_dir, args.participant_label)

# intialize BIDS dataset layout
layout = BIDSLayout(args.bids_dir, derivatives=True)

# intialize empty subject list
subjects_to_analyze = []

# check analysis level and gather subject list
if args.analysis_level == "participant":
if args.participant_label:
subjects_to_analyze = args.participant_label
else:
print("No participant label indicated. Please do so.")
else:
subjects_to_analyze = layout.get(return_type='id', target='subject')

# intialize BIDS dataset layout
layout = BIDSLayout(args.bids_dir, derivatives=True)
# check if indicated participants are missing and if so, provide a list of them
list_part_prob = []
for part in subjects_to_analyze:
if part not in layout.get_subjects():
list_part_prob.append(part)
if len(list_part_prob) >= 1:
raise Exception("The participant(s) you indicated are not present in the BIDS dataset, please check again."
"This refers to:")
print(list_part_prob)

# intialize empty subject list
subjects_to_analyze = []
# gather sessions that should be analyzed and provide a respective update
sessions_to_analyze = layout.get(return_type='id', target='session')

# check analysis level and gather subject list
if args.analysis_level == "participant":
if args.participant_label:
subjects_to_analyze = args.participant_label
if not sessions_to_analyze:
print('Processing data from one session.')
else:
print("No participant label indicated. Please do so.")
else:
subjects_to_analyze = layout.get(return_type='id', target='subject')

# check if indicated participants are missing and if so, provide a list of them
list_part_prob = []
for part in subjects_to_analyze:
if part not in layout.get_subjects():
list_part_prob.append(part)
if len(list_part_prob) >= 1:
raise Exception("The participant(s) you indicated are not present in the BIDS dataset, please check again."
"This refers to:")
print(list_part_prob)

# gather sessions that should be analyzed and provide a respective update
sessions_to_analyze = layout.get(return_type='id', target='session')

if not sessions_to_analyze:
print('Processing data from one session.')
print('Processing data from %s sessions:' % str(len(sessions_to_analyze)))
print(sessions_to_analyze)

# loop over subjects and run analysis, as well as subsequent output conversion
for subject_label in subjects_to_analyze:
# get needed files and check if data from multiple sessions should be gathered
if not sessions_to_analyze:
list_dwi_nii_gz = layout.get(subject=subject_label, extension='nii.gz', suffix='dwi',
return_type='filename')
list_dwi_bval = layout.get(subject=subject_label, extension='bval', suffix='dwi',
return_type='filename')
list_dwi_bvec = layout.get(subject=subject_label, extension='bvec', suffix='dwi',
return_type='filename')
list_dwi_mask = layout.get(subject=subject_label, extension='nii.gz', suffix='mask',
return_type='filename')
else:
list_dwi_nii_gz = layout.get(subject=subject_label, extension='nii.gz', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_bval = layout.get(subject=subject_label, extension='bval', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_bvec = layout.get(subject=subject_label, extension='bvec', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_mask = layout.get(subject=subject_label, extension='nii.gz', suffix='mask',
return_type='filename', session=sessions_to_analyze)

# loop over respective sets of files
for dwi_nii_gz, bval, bvec, mask in zip(list_dwi_nii_gz, list_dwi_bval, list_dwi_bvec, list_dwi_mask):
# check if software argument was provided, if not raise error and indicate problem
if args.software is None:
raise Exception("Please indicate the software you want to use for processing."
"For DIPY use: --software dipy and for mrtrix use: --software mrtrix.")
# check if analysis argument was provided, if not raise error and indicate problem
if args.analysis is None:
raise Exception("Please indicate the analysis you want to run."
"For DTI use: --analysis DTI")

# if dipy was selected, run DIPY and define output path in derivatives folder respectively
if args.software == "dipy":
outpath = str(args.out_dir) + '/dipy/sub-' + subject_label + '/dwi/'
if sessions_to_analyze:
ses_label = dwi_nii_gz.split('/')[-1].split('_')[1].split('-')[1]
outpath = str(args.out_dir) + '/dipy/sub-' + subject_label + '/ses-' + ses_label + '/dwi/'
# if DTI analysis should be run, setup and run dipy_dti function
if args.analysis == "DTI":
dipy_dti(dwi_nii_gz, bval, bvec,
mask, outpath)
dipy_bep16(dwi_nii_gz, bval, bvec,
mask, outpath, json_metadata=args.metadata)

# if CSD analysis should be run, setup and run dipy_csd function
elif args.analysis == "CSD":
dipy_csd(dwi_nii_gz, bval, bvec,
mask, outpath)
# create the respective dataset_description.json file for the run analysis
create_dataset_description("dipy", args.out_dir)

else:
print('Processing data from %s sessions:' % str(len(sessions_to_analyze)))
print(sessions_to_analyze)

# loop over subjects and run analysis, as well as subsequent output conversion
for subject_label in subjects_to_analyze:
# get needed files and check if data from multiple sessions should be gathered
if not sessions_to_analyze:
list_dwi_nii_gz = layout.get(subject=subject_label, extension='nii.gz', suffix='dwi',
return_type='filename')
list_dwi_bval = layout.get(subject=subject_label, extension='bval', suffix='dwi',
return_type='filename')
list_dwi_bvec = layout.get(subject=subject_label, extension='bvec', suffix='dwi',
return_type='filename')
list_dwi_mask = layout.get(subject=subject_label, extension='nii.gz', suffix='mask',
return_type='filename')
if args.download_path is None:
raise Exception("Please indicate a path where the dataset should be downloaded to.")
elif os.path.exists(args.download_path) is False:
raise Exception("If you use the Docker container, please make sure that the indicated path is accessible.")
else:
list_dwi_nii_gz = layout.get(subject=subject_label, extension='nii.gz', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_bval = layout.get(subject=subject_label, extension='bval', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_bvec = layout.get(subject=subject_label, extension='bvec', suffix='dwi',
return_type='filename', session=sessions_to_analyze)
list_dwi_mask = layout.get(subject=subject_label, extension='nii.gz', suffix='mask',
return_type='filename', session=sessions_to_analyze)

# loop over respective sets of files
for dwi_nii_gz, bval, bvec, mask in zip(list_dwi_nii_gz, list_dwi_bval, list_dwi_bvec, list_dwi_mask):
# check if software argument was provided, if not raise error and indicate problem
if args.software is None:
raise Exception("Please indicate the software you want to use for processing."
"For DIPY use: --software dipy and for mrtrix use: --software mrtrix.")
# check if analysis argument was provided, if not raise error and indicate problem
if args.analysis is None:
raise Exception("Please indicate the analysis you want to run."
"For DTI use: --analysis DTI")

# if dipy was selected, run DIPY and define output path in derivatives folder respectively
if args.software == "dipy":
outpath = str(args.out_dir) + '/dipy/sub-' + subject_label + '/dwi/'
if sessions_to_analyze:
ses_label = dwi_nii_gz.split('/')[-1].split('_')[1].split('-')[1]
outpath = str(args.out_dir) + '/dipy/sub-' + subject_label + '/ses-' + ses_label + '/dwi/'
# if DTI analysis should be run, setup and run dipy_dti function
if args.analysis == "DTI":
dipy_dti(dwi_nii_gz, bval, bvec,
mask, outpath)
dipy_bep16(dwi_nii_gz, bval, bvec,
mask, outpath, json_metadata=args.metadata)

# if CSD analysis should be run, setup and run dipy_csd function
elif args.analysis == "CSD":
dipy_csd(dwi_nii_gz, bval, bvec,
mask, outpath)
# create the respective dataset_description.json file for the run analysis
create_dataset_description("dipy", args.out_dir)
if args.download_dataset == "HBN":
download_HBN(args.download_path)


# run the CLI
Expand Down

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