def test_run_T1VolumeCreateDartel(cmdopt):
from os.path import dirname, join, abspath
import shutil
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import T1VolumeCreateDartel
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'T1VolumeCreateDartel')
# Remove potential residual of previous UT
clean_folder(join(working_dir, 'T1VolumeCreateDartel'))
clean_folder(join(root, 'out', 'caps'), recreate=False)
shutil.copytree(join(root, 'in', 'caps'), join(root, 'out', 'caps'))
parameters = {'group_id': 'UnitTest'}
# Instantiate pipeline
pipeline = T1VolumeCreateDartel(bids_directory=join(root, 'in', 'bids'),
caps_directory=join(root, 'out', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
base_dir=join(working_dir,
'T1VolumeCreateDartel'),
parameters=parameters)
pipeline.build()
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': 4},
bypass_check=True)
# Check output vs ref
out_data_template = join(
root,
'out/caps/groups/group-UnitTest/t1/group-UnitTest_template.nii.gz')
ref_data_template = join(root, 'ref/group-UnitTest_template.nii.gz')
assert likeliness_measure(out_data_template, ref_data_template,
(1e-3, 0.1), (1e-2, 0.1))
subjects = [
'sub-ADNI011S4105', 'sub-ADNI023S4020', 'sub-ADNI035S4082',
'sub-ADNI128S4832'
]
out_data_forward_def = [
join(
root, 'out', 'caps', 'subjects', sub, 'ses-M00', 't1', 'spm',
'dartel', 'group-UnitTest', sub +
'_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz'
) for sub in subjects
]
ref_data_forward_def = [
join(
root, 'ref', sub +
'_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz'
) for sub in subjects
]
for i in range(len(out_data_forward_def)):
assert likeliness_measure(out_data_forward_def[i],
ref_data_forward_def[i], (1e-3, 0.25),
(1e-2, 0.1))
# Remove data in out folder
clean_folder(join(root, 'out', 'caps'), recreate=False)
def run_command(self, args):
"""
"""
from tempfile import mkdtemp
from clinica.utils.stream import cprint
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import T1VolumeCreateDartel
pipeline = T1VolumeCreateDartel(bids_directory=self.absolute_path(args.bids_directory),
caps_directory=self.absolute_path(args.caps_directory),
tsv_file=self.absolute_path(args.subjects_sessions_tsv),
group_id=args.group_id)
pipeline.parameters.update({'dartel_tissues': args.dartel_tissues})
if args.working_directory is None:
args.working_directory = mkdtemp()
pipeline.base_dir = self.absolute_path(args.working_directory)
if args.n_procs:
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': args.n_procs})
else:
pipeline.run()
cprint("The " + self._name + " pipeline has completed. You can now delete the working directory (" + args.working_directory + ").")
def test_instantiate_T1VolumeCreateDartel():
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import T1VolumeCreateDartel
from os.path import dirname, join, abspath
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'T1VolumeCreateDartel')
pipeline = T1VolumeCreateDartel(bids_directory=join(root, 'in', 'bids'),
caps_directory=join(root, 'in', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
group_id='UnitTest')
pipeline.build()
def test_instantiate_T1VolumeCreateDartel(cmdopt):
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import (
T1VolumeCreateDartel, )
input_dir = Path(cmdopt["input"])
root = input_dir / "T1VolumeCreateDartel"
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeCreateDartel(
bids_directory=fspath(root / "in" / "bids"),
caps_directory=fspath(root / "in" / "caps"),
tsv_file=fspath(root / "in" / "subjects.tsv"),
parameters=parameters,
)
pipeline.build()
def test_instantiate_T1VolumeCreateDartel():
from os.path import abspath, dirname, join
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import (
T1VolumeCreateDartel, )
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, "data", "T1VolumeCreateDartel")
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeCreateDartel(
bids_directory=join(root, "in", "bids"),
caps_directory=join(root, "in", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
parameters=parameters,
)
pipeline.build()
def run_T1VolumeCreateDartel(
input_dir: Path, output_dir: Path, ref_dir: Path, working_dir: Path
) -> None:
import shutil
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import (
T1VolumeCreateDartel,
)
# Copy necessary data from in to out
shutil.copytree(input_dir / "caps", output_dir / "caps", copy_function=shutil.copy)
parameters = {"group_label": "UnitTest"}
# Instantiate pipeline
pipeline = T1VolumeCreateDartel(
bids_directory=fspath(input_dir / "bids"),
caps_directory=fspath(output_dir / "caps"),
tsv_file=fspath(input_dir / "subjects.tsv"),
base_dir=fspath(working_dir),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc", plugin_args={"n_procs": 4}, bypass_check=True)
# Check output vs ref
out_data_template = fspath(
output_dir / "caps/groups/group-UnitTest/t1/group-UnitTest_template.nii.gz"
)
ref_data_template = fspath(ref_dir / "group-UnitTest_template.nii.gz")
assert likeliness_measure(
out_data_template, ref_data_template, (1e-3, 0.1), (1e-2, 0.1)
)
subjects = [
"sub-ADNI011S4105",
"sub-ADNI023S4020",
"sub-ADNI035S4082",
"sub-ADNI128S4832",
]
out_data_forward_def = [
fspath(
output_dir
/ "caps"
/ "subjects"
/ sub
/ "ses-M00"
/ "t1"
/ "spm"
/ "dartel"
/ "group-UnitTest"
/ (
sub
+ "_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz"
)
)
for sub in subjects
]
ref_data_forward_def = [
fspath(
ref_dir
/ (
sub
+ "_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz"
)
)
for sub in subjects
]
for i in range(len(out_data_forward_def)):
assert likeliness_measure(
out_data_forward_def[i], ref_data_forward_def[i], (1e-3, 0.25), (1e-2, 0.1)
)
def test_run_T1VolumeCreateDartel(cmdopt):
import shutil
from os.path import abspath, dirname, join
from clinica.pipelines.t1_volume_create_dartel.t1_volume_create_dartel_pipeline import (
T1VolumeCreateDartel, )
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir, pardir)))
root = join(root, "data", "T1VolumeCreateDartel")
# Remove potential residual of previous UT
clean_folder(join(working_dir, "T1VolumeCreateDartel"))
clean_folder(join(root, "out", "caps"), recreate=False)
shutil.copytree(join(root, "in", "caps"), join(root, "out", "caps"))
parameters = {"group_label": "UnitTest"}
# Instantiate pipeline
pipeline = T1VolumeCreateDartel(
bids_directory=join(root, "in", "bids"),
caps_directory=join(root, "out", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
base_dir=join(working_dir, "T1VolumeCreateDartel"),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc",
plugin_args={"n_procs": 4},
bypass_check=True)
# Check output vs ref
out_data_template = join(
root,
"out/caps/groups/group-UnitTest/t1/group-UnitTest_template.nii.gz")
ref_data_template = join(root, "ref/group-UnitTest_template.nii.gz")
assert likeliness_measure(out_data_template, ref_data_template,
(1e-3, 0.1), (1e-2, 0.1))
subjects = [
"sub-ADNI011S4105",
"sub-ADNI023S4020",
"sub-ADNI035S4082",
"sub-ADNI128S4832",
]
out_data_forward_def = [
join(
root,
"out",
"caps",
"subjects",
sub,
"ses-M00",
"t1",
"spm",
"dartel",
"group-UnitTest",
sub +
"_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz",
) for sub in subjects
]
ref_data_forward_def = [
join(
root,
"ref",
sub +
"_ses-M00_T1w_target-UnitTest_transformation-forward_deformation.nii.gz",
) for sub in subjects
]
for i in range(len(out_data_forward_def)):
assert likeliness_measure(out_data_forward_def[i],
ref_data_forward_def[i], (1e-3, 0.25),
(1e-2, 0.1))
# Remove data in out folder
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "T1VolumeCreateDartel"), recreate=False)
