def test_DTITracker_outputs():
output_map = dict(track_file=dict(),
mask_file=dict(),
)
outputs = DTITracker.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_DTITracker_outputs():
output_map = dict(mask_file=dict(),
track_file=dict(),
)
outputs = DTITracker.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_DTITracker_inputs():
input_map = dict(
angle_threshold=dict(argstr='-at %f', ),
angle_threshold_weight=dict(argstr='-atw %f', ),
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
input_data_prefix=dict(
argstr='%s',
position=0,
usedefault=True,
),
input_type=dict(argstr='-it %s', ),
invert_x=dict(argstr='-ix', ),
invert_y=dict(argstr='-iy', ),
invert_z=dict(argstr='-iz', ),
mask1_file=dict(
argstr='-m %s',
mandatory=True,
position=2,
),
mask1_threshold=dict(position=3, ),
mask2_file=dict(
argstr='-m2 %s',
position=4,
),
mask2_threshold=dict(position=5, ),
output_file=dict(
argstr='%s',
position=1,
usedefault=True,
),
output_mask=dict(argstr='-om %s', ),
primary_vector=dict(argstr='-%s', ),
random_seed=dict(argstr='-rseed', ),
step_length=dict(argstr='-l %f', ),
swap_xy=dict(argstr='-sxy', ),
swap_yz=dict(argstr='-syz', ),
swap_zx=dict(argstr='-szx', ),
tensor_file=dict(),
terminal_output=dict(nohash=True, ),
tracking_method=dict(argstr='-%s', ),
)
inputs = DTITracker.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_DTITracker_inputs():
input_map = dict(mask2_threshold=dict(position=5,
),
input_data_prefix=dict(position=0,
usedefault=True,
argstr='%s',
),
mask2_file=dict(position=4,
argstr='-m2 %s',
),
invert_y=dict(argstr='-iy',
),
invert_x=dict(argstr='-ix',
),
invert_z=dict(argstr='-iz',
),
tensor_file=dict(),
input_type=dict(argstr='-it %s',
),
mask1_threshold=dict(position=3,
),
output_file=dict(position=1,
usedefault=True,
argstr='%s',
),
tracking_method=dict(argstr='-%s',
),
step_length=dict(argstr='-l %f',
),
output_mask=dict(argstr='-om %s',
),
primary_vector=dict(argstr='-%s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
random_seed=dict(argstr='-rseed',
),
args=dict(argstr='%s',
),
angle_threshold_weight=dict(argstr='-atw %f',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
mask1_file=dict(position=2,
mandatory=True,
argstr='-m %s',
),
angle_threshold=dict(argstr='-at %f',
),
swap_zx=dict(argstr='-szx',
),
swap_xy=dict(argstr='-sxy',
),
environ=dict(nohash=True,
usedefault=True,
),
swap_yz=dict(argstr='-syz',
),
)
inputs = DTITracker.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
