def test_PrepareFieldmap_outputs():
output_map = dict(out_fieldmap=dict(), )
outputs = PrepareFieldmap.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 _fugue_pipeline(self, **name_maps):
pipeline = self.new_pipeline(
name='preprocess_pipeline',
desc=("Fugue distortion correction pipeline"),
citations=[fsl_cite],
name_maps=name_maps)
reorient_epi_in = pipeline.add(
'reorient_epi_in',
fsl.utils.Reorient2Std(output_type='NIFTI_GZ'),
inputs={'in_file': ('series', nifti_gz_format)},
requirements=[fsl_req.v('5.0.9')])
fm_mag_reorient = pipeline.add(
'reorient_fm_mag',
fsl.utils.Reorient2Std(output_type='NIFTI_GZ'),
inputs={'in_file': ('field_map_mag', nifti_gz_format)},
requirements=[fsl_req.v('5.0.9')])
fm_phase_reorient = pipeline.add(
'reorient_fm_phase',
fsl.utils.Reorient2Std(output_type='NIFTI_GZ'),
inputs={'in_file': ('field_map_phase', nifti_gz_format)},
requirements=[fsl_req.v('5.0.9')])
bet = pipeline.add("bet",
BET(robust=True, output_type='NIFTI_GZ'),
inputs={'in_file': (fm_mag_reorient, 'out_file')},
wall_time=5,
requirements=[fsl_req.v('5.0.9')])
create_fmap = pipeline.add(
"prepfmap",
PrepareFieldmap(
# delta_TE=2.46
),
inputs={
'delta_TE': ('field_map_delta_te', float),
"in_magnitude": (bet, "out_file"),
'in_phase': (fm_phase_reorient, 'out_file')
},
wall_time=5,
requirements=[fsl_req.v('5.0.9')])
pipeline.add(
'fugue',
FUGUE(unwarp_direction='x',
dwell_time=self.parameter('fugue_echo_spacing'),
unwarped_file='example_func.nii.gz',
output_type='NIFTI_GZ'),
inputs={
'fmap_in_file': (create_fmap, 'out_fieldmap'),
'in_file': (reorient_epi_in, 'out_file')
},
outputs={'series_preproc': ('unwarped_file', nifti_gz_format)},
wall_time=5,
requirements=[fsl_req.v('5.0.9')])
return pipeline
def test_PrepareFieldmap_outputs():
output_map = dict(out_fieldmap=dict(),
)
outputs = PrepareFieldmap.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 _fugue_pipeline(self, **kwargs):
pipeline = self.create_pipeline(
name='preproc_pipeline',
inputs=[
DatasetSpec('primary', nifti_gz_format),
DatasetSpec('field_map_mag', nifti_gz_format),
DatasetSpec('field_map_phase', nifti_gz_format),
FieldSpec('field_map_delta_te', float)
],
outputs=[DatasetSpec('preproc', nifti_gz_format)],
desc=("Fugue distortion correction pipeline"),
version=1,
citations=[fsl_cite],
**kwargs)
reorient_epi_in = pipeline.create_node(fsl.utils.Reorient2Std(),
name='reorient_epi_in',
requirements=[fsl509_req])
pipeline.connect_input('primary', reorient_epi_in, 'in_file')
fm_mag_reorient = pipeline.create_node(fsl.utils.Reorient2Std(),
name='reorient_fm_mag',
requirements=[fsl509_req])
pipeline.connect_input('field_map_mag', fm_mag_reorient, 'in_file')
fm_phase_reorient = pipeline.create_node(fsl.utils.Reorient2Std(),
name='reorient_fm_phase',
requirements=[fsl509_req])
pipeline.connect_input('field_map_phase', fm_phase_reorient, 'in_file')
bet = pipeline.create_node(BET(),
name="bet",
wall_time=5,
requirements=[fsl509_req])
bet.inputs.robust = True
pipeline.connect(fm_mag_reorient, 'out_file', bet, 'in_file')
create_fmap = pipeline.create_node(PrepareFieldmap(),
name="prepfmap",
wall_time=5,
requirements=[fsl509_req])
# create_fmap.inputs.delta_TE = 2.46
pipeline.connect_input('field_map_delta_te', create_fmap, 'delta_TE')
pipeline.connect(bet, "out_file", create_fmap, "in_magnitude")
pipeline.connect(fm_phase_reorient, 'out_file', create_fmap,
'in_phase')
fugue = pipeline.create_node(FUGUE(),
name='fugue',
wall_time=5,
requirements=[fsl509_req])
fugue.inputs.unwarp_direction = 'x'
fugue.inputs.dwell_time = self.parameter('fugue_echo_spacing')
fugue.inputs.unwarped_file = 'example_func.nii.gz'
pipeline.connect(create_fmap, 'out_fieldmap', fugue, 'fmap_in_file')
pipeline.connect(reorient_epi_in, 'out_file', fugue, 'in_file')
pipeline.connect_output('preproc', fugue, 'unwarped_file')
return pipeline
def test_PrepareFieldmap_inputs():
input_map = dict(
args=dict(argstr='%s', ),
delta_TE=dict(
argstr='%f',
mandatory=True,
position=-2,
usedefault=True,
),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_magnitude=dict(
argstr='%s',
mandatory=True,
position=3,
),
in_phase=dict(
argstr='%s',
mandatory=True,
position=2,
),
nocheck=dict(
argstr='--nocheck',
position=-1,
usedefault=True,
),
out_fieldmap=dict(
argstr='%s',
position=4,
),
output_type=dict(),
scanner=dict(
argstr='%s',
position=1,
usedefault=True,
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = PrepareFieldmap.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_PrepareFieldmap_inputs():
input_map = dict(delta_TE=dict(mandatory=True,
usedefault=True,
position=-2,
argstr='%f',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
out_fieldmap=dict(position=5,
argstr='%s',
),
args=dict(argstr='%s',
),
nocheck=dict(position=-1,
argstr='--nocheck',
usedefault=True,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
environ=dict(nohash=True,
usedefault=True,
),
in_phase=dict(position=2,
mandatory=True,
argstr='%s',
),
in_magnitude=dict(position=3,
mandatory=True,
argstr='%s',
),
output_type=dict(),
scanner=dict(position=1,
usedefault=True,
argstr='%s',
),
)
inputs = PrepareFieldmap.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
