def test_MakeAverageSubject_inputs():
input_map = dict(
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
out_name=dict(
argstr='--out %s',
usedefault=True,
),
subjects_dir=dict(),
subjects_ids=dict(
argstr='--subjects %s',
mandatory=True,
sep=' ',
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = MakeAverageSubject.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_MakeAverageSubject_outputs():
output_map = dict(average_subject_name=dict(), )
outputs = MakeAverageSubject.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def test_MakeAverageSubject_inputs():
input_map = dict(args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
out_name=dict(argstr='--out %s',
usedefault=True,
),
subjects_dir=dict(),
subjects_ids=dict(argstr='--subjects %s',
mandatory=True,
sep=' ',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = MakeAverageSubject.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
def test_MakeAverageSubject_outputs():
output_map = dict(average_subject_name=dict(),
)
outputs = MakeAverageSubject.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
def processT1(t1_filename):
import os
import nipype.pipeline.engine as pe
import nipype.interfaces.io as nio
from nipype.interfaces.freesurfer.preprocess import ReconAll
from nipype.interfaces.freesurfer.utils import MakeAverageSubject
subject_list = ['s1', 's3']
data_dir = os.path.abspath('data')
subjects_dir = os.path.abspath('amri_freesurfer_tutorial/subjects_dir')
wf = pe.Workflow(name="l1workflow")
wf.base_dir = os.path.abspath('amri_freesurfer_tutorial/workdir')
datasource = pe.MapNode(interface=nio.DataGrabber(infields=['subject_id'],
outfields=['struct']),
name='datasource',
iterfield=['subject_id'])
datasource.inputs.base_directory = data_dir
datasource.inputs.template = '%s/%s.nii'
datasource.inputs.template_args = dict(struct=[['subject_id', 'struct']])
datasource.inputs.subject_id = subject_list
recon_all = pe.MapNode(interface=ReconAll(),
name='recon_all',
iterfield=['subject_id', 'T1_files'])
recon_all.inputs.subject_id = subject_list
if not os.path.exists(subjects_dir):
os.mkdir(subjects_dir)
recon_all.inputs.subjects_dir = subjects_dir
wf.connect(datasource, 'struct', recon_all, 'T1_files')
average = pe.Node(interface=MakeAverageSubject(), name="average")
average.inputs.subjects_dir = subjects_dir
wf.connect(recon_all, 'subject_id', average, 'subjects_ids')
wf.run("MultiProc", plugin_args={'n_procs': 4})
datasource.inputs.base_directory = data_dir
datasource.inputs.template = '%s/%s.nii'
datasource.inputs.template_args = dict(struct=[['subject_id', 'struct']])
datasource.inputs.subject_id = subject_list
datasource.inputs.sort_filelist = True
wf.connect(inputspec, 'subject_id', datasource, 'subject_id')
"""
Run recon-all
"""
recon_all = create_reconall_workflow()
recon_all.inputs.inputspec.subjects_dir = subjects_dir
wf.connect(datasource, 'struct', recon_all, 'inputspec.T1_files')
wf.connect(inputspec, 'subject_id', recon_all, 'inputspec.subject_id')
"""
Make average subject
"""
average = pe.JoinNode(interface=MakeAverageSubject(),
joinsource="inputspec",
joinfield="subjects_ids",
name="average")
average.inputs.subjects_dir = subjects_dir
wf.connect(recon_all, 'postdatasink_outputspec.subject_id', average,
'subjects_ids')
wf.run("MultiProc", plugin_args={'n_procs': 4})
datasource.inputs.template = '%s/%s.nii'
datasource.inputs.template_args = dict(struct=[['subject_id', 'struct']])
datasource.inputs.subject_id = subject_list
datasource.inputs.sort_filelist = True
wf.connect(inputspec, 'subject_id', datasource, 'subject_id')
"""
Run recon-all
"""
recon_all = create_reconall_workflow()
recon_all.inputs.inputspec.subjects_dir = subjects_dir
wf.connect(datasource, 'struct', recon_all, 'inputspec.T1_files')
wf.connect(inputspec, 'subject_id', recon_all, 'inputspec.subject_id')
"""
Make average subject
"""
average = pe.JoinNode(
interface=MakeAverageSubject(),
joinsource="inputspec",
joinfield="subjects_ids",
name="average")
average.inputs.subjects_dir = subjects_dir
wf.connect(recon_all, 'postdatasink_outputspec.subject_id', average,
'subjects_ids')
wf.run("MultiProc", plugin_args={'n_procs': 4})
outfields=['struct']),
name='datasource',
iterfield=['subject_id'])
datasource.inputs.base_directory = data_dir
datasource.inputs.template = '%s/%s.nii'
datasource.inputs.template_args = dict(struct=[['subject_id', 'struct']])
datasource.inputs.subject_id = subject_list
"""
Run recon-all
"""
recon_all = pe.MapNode(interface=ReconAll(),
name='recon_all',
iterfield=['subject_id', 'T1_files'])
recon_all.inputs.subject_id = subject_list
if not os.path.exists(subjects_dir):
os.mkdir(subjects_dir)
recon_all.inputs.subjects_dir = subjects_dir
wf.connect(datasource, 'struct', recon_all, 'T1_files')
"""
Make average subject
"""
average = pe.Node(interface=MakeAverageSubject(), name="average")
average.inputs.subjects_dir = subjects_dir
wf.connect(recon_all, 'subject_id', average, 'subjects_ids')
wf.run("MultiProc", plugin_args={'n_procs': 4})
