def test_instantiate_DWIConnectome():
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
from os.path import dirname, join, abspath
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'DWIConnectome')
pipeline = DwiConnectome(caps_directory=join(root, 'in', 'caps'),
tsv_file=join(root, 'in', 'subjects.tsv'))
pipeline.parameters = {'n_tracks': 1000}
pipeline.build()
def test_instantiate_DWIConnectome(cmdopt):
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
input_dir = Path(cmdopt["input"])
root = input_dir / "DWIConnectome"
parameters = {"n_tracks": 1000}
pipeline = DwiConnectome(
caps_directory=fspath(root / "in" / "caps"),
tsv_file=fspath(root / "in" / "subjects.tsv"),
parameters=parameters,
)
pipeline.build()
def test_instantiate_DWIConnectome():
from os.path import abspath, dirname, join
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, "data", "DWIConnectome")
parameters = {"n_tracks": 1000}
pipeline = DwiConnectome(
caps_directory=join(root, "in", "caps"),
tsv_file=join(root, "in", "subjects.tsv"),
parameters=parameters,
)
pipeline.build()
def test_run_DWIConnectome(cmdopt):
from os.path import dirname, join, abspath
import shutil
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
# Initialization
working_dir = join(abspath(cmdopt), 'DWIConnectome')
root = dirname(abspath(join(abspath(__file__), pardir)))
root = join(root, 'data', 'DWIConnectome')
in_tsv = join(root, 'in', 'subjects.tsv')
out_caps_dir = join(root, 'out', 'caps')
subject_id = 'sub-HMTC20110506MEMEPPAT27'
session_id = 'ses-M00'
clean_folder(out_caps_dir, recreate=False)
clean_folder(working_dir)
shutil.copytree(join(root, 'in', 'caps'), out_caps_dir)
parameters = {'n_tracks': 1000}
pipeline = DwiConnectome(caps_directory=out_caps_dir,
tsv_file=in_tsv,
base_dir=working_dir,
parameters=parameters)
pipeline.build()
pipeline.run(plugin='MultiProc',
plugin_args={'n_procs': 4},
bypass_check=True)
# Check files
atlases = ['desikan', 'destrieux']
out_fod_file = join(
root, 'out', 'caps', 'subjects', subject_id, session_id, 'dwi',
'connectome_based_processing', subject_id + '_' + session_id +
'_dwi_space-b0_model-CSD_diffmodel.nii.gz')
ref_fod_file = join(
root, 'ref', subject_id + '_' + session_id +
'_dwi_space-b0_model-CSD_diffmodel.nii.gz')
out_parc_files = [
join(
root, 'out', 'caps', 'subjects', subject_id, session_id, 'dwi',
'connectome_based_processing', subject_id + '_' + session_id +
'_dwi_space-b0_atlas-' + a + '_parcellation.nii.gz')
for a in atlases
]
ref_parc_files = [
join(
root, 'ref', subject_id + '_' + session_id +
'_dwi_space-b0_atlas-' + a + '_parcellation.nii.gz')
for a in atlases
]
assert similarity_measure(out_fod_file, ref_fod_file, 0.97)
for i in range(len(out_parc_files)):
assert similarity_measure(out_parc_files[i], ref_parc_files[i], 0.955)
clean_folder(join(root, 'out', 'caps'), recreate=False)
def run_DWIConnectome(input_dir: Path, output_dir: Path, ref_dir: Path,
working_dir: Path) -> None:
import shutil
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
caps_dir = output_dir / "caps"
tsv = input_dir / "subjects.tsv"
# Copy necessary data from in to out
shutil.copytree(input_dir / "caps", caps_dir, copy_function=shutil.copy)
parameters = {"n_tracks": 1000}
pipeline = DwiConnectome(
caps_directory=fspath(caps_dir),
tsv_file=fspath(tsv),
base_dir=fspath(working_dir),
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc",
plugin_args={"n_procs": 4},
bypass_check=True)
# Check files
atlases = ["desikan", "destrieux"]
subject_id = "sub-HMTC20110506MEMEPPAT27"
session_id = "ses-M00"
out_fod_file = fspath(caps_dir / "subjects" / subject_id / session_id /
"dwi" / "connectome_based_processing" /
(subject_id + "_" + session_id +
"_dwi_space-b0_model-CSD_diffmodel.nii.gz"))
ref_fod_file = fspath(
ref_dir / (subject_id + "_" + session_id +
"_dwi_space-b0_model-CSD_diffmodel.nii.gz"), )
out_parc_files = [
fspath(caps_dir / "subjects" / subject_id / session_id / "dwi" /
"connectome_based_processing" /
(subject_id + "_" + session_id + "_dwi_space-b0_atlas-" + a +
"_parcellation.nii.gz")) for a in atlases
]
ref_parc_files = [
fspath(ref_dir / (subject_id + "_" + session_id +
"_dwi_space-b0_atlas-" + a + "_parcellation.nii.gz"))
for a in atlases
]
assert similarity_measure(out_fod_file, ref_fod_file, 0.97)
for i in range(len(out_parc_files)):
assert similarity_measure(out_parc_files[i], ref_parc_files[i], 0.955)
def test_run_DWIConnectome(cmdopt):
import shutil
from os.path import abspath, dirname, join
from clinica.pipelines.dwi_connectome.dwi_connectome_pipeline import DwiConnectome
# Initialization
working_dir = join(abspath(cmdopt), "DWIConnectome")
root = dirname(abspath(join(abspath(__file__), pardir, pardir)))
root = join(root, "data", "DWIConnectome")
in_tsv = join(root, "in", "subjects.tsv")
out_caps_dir = join(root, "out", "caps")
subject_id = "sub-HMTC20110506MEMEPPAT27"
session_id = "ses-M00"
clean_folder(out_caps_dir, recreate=False)
clean_folder(working_dir)
shutil.copytree(join(root, "in", "caps"), out_caps_dir)
parameters = {"n_tracks": 1000}
pipeline = DwiConnectome(
caps_directory=out_caps_dir,
tsv_file=in_tsv,
base_dir=working_dir,
parameters=parameters,
)
pipeline.build()
pipeline.run(plugin="MultiProc",
plugin_args={"n_procs": 4},
bypass_check=True)
# Check files
atlases = ["desikan", "destrieux"]
out_fod_file = join(
root,
"out",
"caps",
"subjects",
subject_id,
session_id,
"dwi",
"connectome_based_processing",
subject_id + "_" + session_id +
"_dwi_space-b0_model-CSD_diffmodel.nii.gz",
)
ref_fod_file = join(
root,
"ref",
subject_id + "_" + session_id +
"_dwi_space-b0_model-CSD_diffmodel.nii.gz",
)
out_parc_files = [
join(
root,
"out",
"caps",
"subjects",
subject_id,
session_id,
"dwi",
"connectome_based_processing",
subject_id + "_" + session_id + "_dwi_space-b0_atlas-" + a +
"_parcellation.nii.gz",
) for a in atlases
]
ref_parc_files = [
join(
root,
"ref",
subject_id + "_" + session_id + "_dwi_space-b0_atlas-" + a +
"_parcellation.nii.gz",
) for a in atlases
]
assert similarity_measure(out_fod_file, ref_fod_file, 0.97)
for i in range(len(out_parc_files)):
assert similarity_measure(out_parc_files[i], ref_parc_files[i], 0.955)
clean_folder(join(root, "out", "caps"), recreate=False)
clean_folder(working_dir, recreate=False)