def test_run_T1VolumeRegisterDartel(cmdopt):
from os.path import dirname, join, abspath
import shutil
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import T1VolumeRegisterDartel
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'T1VolumeExistingDartel')
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'T1VolumeExistingDartel'))
# Copy necessary data to run pipeline
shutil.copytree(join(root, 'in', 'caps'), join(root, 'out', 'caps'))
# Instantiate and run pipeline
parameters = {'group_id': 'UnitTest'}
pipeline = T1VolumeRegisterDartel(bids_directory=join(root, 'in', 'bids'),
caps_directory=join(root, 'out', 'caps'),
tsv_file=join(root, 'in',
'subjects.tsv'),
base_dir=join(working_dir,
'T1VolumeExistingDartel'),
parameters=parameters)
pipeline.build()
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': 4},
bypass_check=True)
# Check output vs ref
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, 'T1VolumeExistingDartel'), recreate=False)
def test_instantiate_T1VolumeRegisterDartel():
from os.path import dirname, join, abspath
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import T1VolumeRegisterDartel
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'T1VolumeExistingDartel')
parameters = {'group_label': 'UnitTest'}
pipeline = T1VolumeRegisterDartel(bids_directory=join(root, 'in', 'bids'),
caps_directory=join(root, 'in', 'caps'),
tsv_file=join(root, 'in',
'subjects.tsv'),
parameters=parameters)
pipeline.build()
def test_instantiate_T1VolumeRegisterDartel(cmdopt):
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import (
T1VolumeRegisterDartel, )
input_dir = Path(cmdopt["input"])
root = input_dir / "T1VolumeRegisterDartel"
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeRegisterDartel(
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_T1VolumeRegisterDartel():
from os.path import abspath, dirname, join
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import (
T1VolumeRegisterDartel, )
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, "data", "T1VolumeExistingDartel")
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeRegisterDartel(
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_T1VolumeRegisterDartel(
input_dir: Path, output_dir: Path, ref_dir: Path, working_dir: Path
) -> None:
import shutil
from os.path import abspath, dirname, join
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import (
T1VolumeRegisterDartel,
)
# Copy necessary data from in to out
shutil.copytree(input_dir / "caps", output_dir / "caps", copy_function=shutil.copy)
# Instantiate and run pipeline
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeRegisterDartel(
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
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_T1VolumeRegisterDartel(cmdopt):
import shutil
from os.path import abspath, dirname, join
from clinica.pipelines.t1_volume_register_dartel.t1_volume_register_dartel_pipeline import (
T1VolumeRegisterDartel, )
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir, pardir)))
root = join(root, "data", "T1VolumeExistingDartel")
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "T1VolumeExistingDartel"))
# Copy necessary data to run pipeline
shutil.copytree(join(root, "in", "caps"), join(root, "out", "caps"))
# Instantiate and run pipeline
parameters = {"group_label": "UnitTest"}
pipeline = T1VolumeRegisterDartel(
bids_directory=join(root, "in", "bids"),
caps_directory=join(root, "out", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
base_dir=join(working_dir, "T1VolumeExistingDartel"),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc",
plugin_args={"n_procs": 4},
bypass_check=True)
# Check output vs ref
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, "T1VolumeExistingDartel"), recreate=False)