def test_StreamlineTrack_outputs():
output_map = dict(tracked=dict(), )
outputs = StreamlineTrack.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_StreamlineTrack_outputs():
output_map = dict(tracked=dict(),
)
outputs = StreamlineTrack.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_StreamlineTrack_inputs():
input_map = dict(do_not_precompute=dict(argstr='-noprecomputed',
),
maximum_number_of_tracks=dict(argstr='-maxnum %d',
),
exclude_file=dict(position=2,
argstr='-exclude %s',
),
cutoff_value=dict(units='NA',
argstr='-cutoff %s',
),
seed_file=dict(position=2,
argstr='-seed %s',
),
step_size=dict(units='mm',
argstr='-step %s',
),
in_file=dict(position=-2,
mandatory=True,
argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
no_mask_interpolation=dict(argstr='-nomaskinterp',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
include_file=dict(position=2,
argstr='-include %s',
),
maximum_tract_length=dict(units='mm',
argstr='-length %s',
),
args=dict(argstr='%s',
),
stop=dict(argstr='-gzip',
),
minimum_radius_of_curvature=dict(units='mm',
argstr='-curvature %s',
),
inputmodel=dict(position=-3,
usedefault=True,
argstr='%s',
),
initial_direction=dict(units='voxels',
argstr='-initdirection %s',
),
exclude_spec=dict(sep=',',
units='mm',
position=2,
argstr='-seed %s',
),
desired_number_of_tracks=dict(argstr='-number %d',
),
seed_spec=dict(sep=',',
units='mm',
position=2,
argstr='-seed %s',
),
initial_cutoff_value=dict(units='NA',
argstr='-initcutoff %s',
),
minimum_tract_length=dict(units='mm',
argstr='-minlength %s',
),
mask_spec=dict(sep=',',
units='mm',
position=2,
argstr='-seed %s',
),
out_file=dict(position=-1,
genfile=True,
argstr='%s',
),
include_spec=dict(sep=',',
units='mm',
position=2,
argstr='-seed %s',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
unidirectional=dict(argstr='-unidirectional',
),
mask_file=dict(position=2,
argstr='-exclude %s',
),
)
inputs = StreamlineTrack.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_StreamlineTrack_inputs():
input_map = dict(
args=dict(argstr='%s', ),
cutoff_value=dict(
argstr='-cutoff %s',
units='NA',
),
desired_number_of_tracks=dict(argstr='-number %d', ),
do_not_precompute=dict(argstr='-noprecomputed', ),
environ=dict(
nohash=True,
usedefault=True,
),
exclude_file=dict(
argstr='-exclude %s',
xor=['exclude_file', 'exclude_spec'],
),
exclude_spec=dict(
argstr='-exclude %s',
position=2,
sep=',',
units='mm',
xor=['exclude_file', 'exclude_spec'],
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='%s',
mandatory=True,
position=-2,
),
include_file=dict(
argstr='-include %s',
xor=['include_file', 'include_spec'],
),
include_spec=dict(
argstr='-include %s',
position=2,
sep=',',
units='mm',
xor=['include_file', 'include_spec'],
),
initial_cutoff_value=dict(
argstr='-initcutoff %s',
units='NA',
),
initial_direction=dict(
argstr='-initdirection %s',
units='voxels',
),
inputmodel=dict(
argstr='%s',
position=-3,
usedefault=True,
),
mask_file=dict(
argstr='-mask %s',
xor=['mask_file', 'mask_spec'],
),
mask_spec=dict(
argstr='-mask %s',
position=2,
sep=',',
units='mm',
xor=['mask_file', 'mask_spec'],
),
maximum_number_of_tracks=dict(argstr='-maxnum %d', ),
maximum_tract_length=dict(
argstr='-length %s',
units='mm',
),
minimum_radius_of_curvature=dict(
argstr='-curvature %s',
units='mm',
),
minimum_tract_length=dict(
argstr='-minlength %s',
units='mm',
),
no_mask_interpolation=dict(argstr='-nomaskinterp', ),
out_file=dict(
argstr='%s',
name_source=['in_file'],
name_template='%s_tracked.tck',
output_name='tracked',
position=-1,
),
seed_file=dict(
argstr='-seed %s',
xor=['seed_file', 'seed_spec'],
),
seed_spec=dict(
argstr='-seed %s',
position=2,
sep=',',
units='mm',
xor=['seed_file', 'seed_spec'],
),
step_size=dict(
argstr='-step %s',
units='mm',
),
stop=dict(argstr='-stop', ),
terminal_output=dict(
mandatory=True,
nohash=True,
),
unidirectional=dict(argstr='-unidirectional', ),
)
inputs = StreamlineTrack.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
