def run_command(self, args):
from tempfile import mkdtemp
from clinica.utils.stream import cprint
from clinica.pipelines.pet_surface.pet_surface_pipeline import PetSurface
if args.working_directory is None:
args.working_directory = mkdtemp()
pipeline = PetSurface(
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))
pipeline.parameters = {
'pet_type': args.pet_tracer,
'wd': self.absolute_path(args.working_directory),
'n_procs': args.n_procs
}
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_run_PETSurfaceCrossSectional(cmdopt):
from os.path import dirname, join, abspath
import shutil
import nibabel as nib
import numpy as np
from clinica.pipelines.pet_surface.pet_surface_pipeline import PetSurface
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'PETSurface')
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'PETSurface'))
shutil.copytree(join(root, 'in', 'caps'), join(root, 'out', 'caps'))
parameters = {
'acq_label': 'FDG',
'suvr_reference_region': 'pons',
'pvc_psf_tsv': join(root, 'in', 'subjects.tsv'),
'longitudinal': False
}
pipeline = PetSurface(bids_directory=join(root, 'in', 'bids'),
caps_directory=join(root, 'out', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'),
base_dir=join(working_dir, 'PETSurface'),
parameters=parameters)
pipeline.build()
pipeline.run(bypass_check=True)
# Check files
out_files = [
join(
root, 'out/caps/subjects/sub-ADNI011S4105/ses-M00/pet/surface',
'sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-'
+ h + '_fwhm-' + str(f) + '_projection.mgh') for h in ['lh', 'rh']
for f in [0, 5, 10, 15, 20, 25]
]
ref_files = [
join(
root, 'ref',
'sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-'
+ h + '_fwhm-' + str(f) + '_projection.mgh') for h in ['lh', 'rh']
for f in [0, 5, 10, 15, 20, 25]
]
for i in range(len(out_files)):
assert np.allclose(np.squeeze(nib.load(out_files[i]).get_data()),
np.squeeze(nib.load(ref_files[i]).get_data()),
rtol=3e-2,
equal_nan=True)
clean_folder(join(root, 'out', 'caps'), recreate=False)
clean_folder(join(working_dir, 'PETSurface'), recreate=False)
def test_run_PETSurfaceCrossSectional(cmdopt):
import shutil
from os.path import abspath, dirname, join
import nibabel as nib
import numpy as np
from clinica.pipelines.pet_surface.pet_surface_pipeline import PetSurface
working_dir = cmdopt
root = dirname(abspath(join(abspath(__file__), pardir, pardir)))
root = join(root, "data", "PETSurface")
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "PETSurface"))
shutil.copytree(join(root, "in", "caps"), join(root, "out", "caps"))
parameters = {
"acq_label": "FDG",
"suvr_reference_region": "pons",
"pvc_psf_tsv": join(root, "in", "subjects.tsv"),
"longitudinal": False,
}
pipeline = PetSurface(
bids_directory=join(root, "in", "bids"),
caps_directory=join(root, "out", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
base_dir=join(working_dir, "PETSurface"),
parameters=parameters,
)
pipeline.build()
pipeline.run(bypass_check=True)
# Check files
out_files = [
join(
root,
"out/caps/subjects/sub-ADNI011S4105/ses-M00/pet/surface",
"sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-"
+ h + "_fwhm-" + str(f) + "_projection.mgh",
) for h in ["lh", "rh"] for f in [0, 5, 10, 15, 20, 25]
]
ref_files = [
join(
root,
"ref",
"sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-"
+ h + "_fwhm-" + str(f) + "_projection.mgh",
) for h in ["lh", "rh"] for f in [0, 5, 10, 15, 20, 25]
]
for i in range(len(out_files)):
assert np.allclose(
np.squeeze(nib.load(out_files[i]).get_data()),
np.squeeze(nib.load(ref_files[i]).get_data()),
rtol=3e-2,
equal_nan=True,
)
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(join(working_dir, "PETSurface"), recreate=False)
def run_PETSurfaceCrossSectional(
input_dir: Path, output_dir: Path, ref_dir: Path, working_dir: Path
) -> None:
import shutil
import nibabel as nib
import numpy as np
from clinica.pipelines.pet_surface.pet_surface_pipeline import PetSurface
shutil.copytree(input_dir / "caps", output_dir / "caps", copy_function=shutil.copy)
parameters = {
"acq_label": "FDG",
"suvr_reference_region": "pons",
"pvc_psf_tsv": fspath(input_dir / "subjects.tsv"),
"longitudinal": False,
"skip_question": False,
}
pipeline = PetSurface(
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(bypass_check=True)
# Check files
out_files = [
(
output_dir
/ "caps/subjects/sub-ADNI011S4105/ses-M00/pet/surface"
/ (
"sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-"
+ h
+ "_fwhm-"
+ str(f)
+ "_projection.mgh"
)
)
for h in ["lh", "rh"]
for f in [0, 5, 10, 15, 20, 25]
]
ref_files = [
(
ref_dir
/ (
"sub-ADNI011S4105_ses-M00_task-rest_acq-fdg_pet_space-fsaverage_suvr-pons_pvc-iy_hemi-"
+ h
+ "_fwhm-"
+ str(f)
+ "_projection.mgh"
)
)
for h in ["lh", "rh"]
for f in [0, 5, 10, 15, 20, 25]
]
for i in range(len(out_files)):
assert np.allclose(
np.squeeze(nib.load(fspath(out_files[i])).get_fdata(dtype="float32")),
np.squeeze(nib.load(fspath(ref_files[i])).get_fdata(dtype="float32")),
rtol=3e-2,
equal_nan=True,
)