def run_command(self, args):
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
from os.path import exists, join
from clinica.utils.stream import cprint
from colorama import Fore
from time import sleep
adni_to_bids = AdniToBids()
# Check dcm2nii and dcm2niix dependencies
adni_to_bids.check_adni_dependencies()
if 'fMRI' in args.modalities and not exists(join(args.clinical_data_directory, 'IDA_MR_Metadata_Listing.csv')):
cprint(Fore.RED + '[Warning] We could not detect file IDA_MR_Metadata_Listing.csv in your clinical data folder.'
+ ' Therefore, fMRI conversion is disabled.' + Fore.GREEN
+ '\nADNI conversion will start in a few seconds...' + Fore.RESET)
# Enough time for the user to read the message
sleep(7)
args.modalities.remove('fMRI')
if not args.clinical_data_only:
adni_to_bids.convert_images(self.absolute_path(args.dataset_directory),
self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory),
args.subjects_list,
args.modalities)
adni_to_bids.convert_clinical_data(self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory))
def test_run_Adni2Bids(cmdopt):
from os.path import abspath, dirname, join
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
root = join(dirname(abspath(__file__)), pardir, pardir, "data", "Adni2Bids")
clean_folder(join(root, "out", "bids"), recreate=True)
adni_to_bids = AdniToBids()
adni_to_bids.check_adni_dependencies()
dataset_directory = join(root, "in", "unorganized_data")
clinical_data_directory = join(root, "in", "clinical_data")
bids_directory = join(root, "out", "bids")
subjects_list = join(root, "in", "subjects.txt")
modalities = ["T1", "PET_FDG", "PET_AMYLOID", "PET_TAU", "DWI", "FLAIR", "fMRI"]
adni_to_bids.convert_images(
dataset_directory,
clinical_data_directory,
bids_directory,
subjects_list,
modalities,
)
adni_to_bids.convert_clinical_data(clinical_data_directory, bids_directory)
# Generate tree of output files
compare_folders(join(root, "out"), join(root, "ref"), shared_folder_name="bids")
clean_folder(join(root, "out", "bids"), recreate=True)
def test_run_Adni2Bids(cmdopt):
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
from os.path import dirname, join, abspath
root = join(dirname(abspath(__file__)), pardir, 'data', 'Adni2Bids')
clean_folder(join(root, 'out', 'bids'), recreate=True)
adni_to_bids = AdniToBids()
adni_to_bids.check_adni_dependencies()
dataset_directory = join(root, 'in', 'unorganized_data')
clinical_data_directory = join(root, 'in', 'clinical_data_25-04-19')
bids_directory = join(root, 'out', 'bids')
subjects_list = join(root, 'in', 'subjects.txt')
modalities = [
'T1', 'PET_FDG', 'PET_AMYLOID', 'PET_TAU', 'DWI', 'FLAIR', 'fMRI'
]
adni_to_bids.convert_images(dataset_directory, clinical_data_directory,
bids_directory, subjects_list, modalities)
adni_to_bids.convert_clinical_data(clinical_data_directory, bids_directory)
# Generate tree of output files
compare_folders(join(root, 'out'),
join(root, 'ref'),
shared_folder_name='bids')
clean_folder(join(root, 'out', 'bids'), recreate=True)
def run_adni2bids(input_dir: PathLike, output_dir: PathLike,
ref_dir: PathLike) -> None:
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
# Arrange
clinical_data_directory = input_dir / "clinical_data"
dataset_directory = input_dir / "unorganized_data"
subjects_list = input_dir / "subjects.txt"
modalities = [
"T1", "PET_FDG", "PET_AMYLOID", "PET_TAU", "DWI", "FLAIR", "fMRI"
]
# Act
adni_to_bids = AdniToBids()
adni_to_bids.check_adni_dependencies()
adni_to_bids.convert_images(
dataset_directory,
clinical_data_directory,
output_dir / "bids",
subjects_list,
modalities,
)
adni_to_bids.convert_clinical_data(clinical_data_directory,
output_dir / "bids")
# Assert
compare_folders(output_dir / "bids", ref_dir / "bids", output_dir)
def run_command(self, args):
from colorama import Fore
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
from clinica.utils.exceptions import ClinicaParserError
adni_to_bids = AdniToBids()
# Check dcm2nii and dcm2niix dependencies
adni_to_bids.check_adni_dependencies()
if args.clinical_data_only and args.force_new_extraction:
raise ClinicaParserError(
f"{Fore.RED}\n[Error] Arguments clinical_data_only and force_new_extraction are mutually exclusive.{Fore.RESET}"
)
if not args.clinical_data_only:
adni_to_bids.convert_images(
self.absolute_path(args.dataset_directory),
self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory),
args.subjects_list,
args.modalities,
args.force_new_extraction,
)
adni_to_bids.convert_clinical_data(
self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory),
)
def run_command(self, args):
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
adni_to_bids = AdniToBids()
# Check dcm2nii and dcm2niix dependencies
adni_to_bids.check_adni_dependencies()
if not args.clinical_data_only:
adni_to_bids.convert_images(
self.absolute_path(args.dataset_directory),
self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory), args.subjects_list,
args.modalities)
adni_to_bids.convert_clinical_data(
self.absolute_path(args.clinical_data_directory),
self.absolute_path(args.bids_directory))
def cli(
dataset_directory: str,
clinical_data_directory: str,
bids_directory: str,
subjects_list: Optional[str] = None,
clinical_data_only: bool = False,
force_new_extraction: bool = False,
modalities: List[str] = ALL_MODALITIES,
) -> None:
"""ADNI to BIDS converter.
Convert the imaging and clinical data of ADNI (http://adni.loni.usc.edu/), located in DATASET_DIRECTORY and
CLINICAL_DATA_DIRECTORY respectively, to a BIDS dataset in the target BIDS_DIRECTORY.
"""
from clinica.iotools.converters.adni_to_bids.adni_to_bids import AdniToBids
from clinica.utils.exceptions import ClinicaParserError
adni_to_bids = AdniToBids()
adni_to_bids.check_adni_dependencies()
if clinical_data_only and force_new_extraction:
raise ClinicaParserError(
"Arguments `clinical_data_only` and `force_new_extraction` are mutually exclusive."
)
if not clinical_data_only:
adni_to_bids.convert_images(
dataset_directory,
clinical_data_directory,
bids_directory,
subjects_list,
modalities,
force_new_extraction,
)
adni_to_bids.convert_clinical_data(
clinical_data_dir=clinical_data_directory,
out_path=bids_directory,
clinical_data_only=clinical_data_only,
subjects_list_path=subjects_list,
)