def test_TrackBayesDirac_outputs():
output_map = dict(tracked=dict(), )
outputs = TrackBayesDirac.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_TrackBayesDirac_outputs():
output_map = dict(tracked=dict(),
)
outputs = TrackBayesDirac.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_TrackBayesDirac_inputs():
input_map = dict(anisfile=dict(argstr='-anisfile %s',
),
anisthresh=dict(argstr='-anisthresh %f',
),
args=dict(argstr='%s',
),
curvepriorg=dict(argstr='-curvepriorg %G',
),
curvepriork=dict(argstr='-curvepriork %G',
),
curvethresh=dict(argstr='-curvethresh %f',
),
data_dims=dict(argstr='-datadims %s',
units='voxels',
),
datamodel=dict(argstr='-datamodel %s',
),
environ=dict(nohash=True,
usedefault=True,
),
extpriordatatype=dict(argstr='-extpriordatatype %s',
),
extpriorfile=dict(argstr='-extpriorfile %s',
),
gzip=dict(argstr='-gzip',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='-inputfile %s',
mandatory=True,
position=1,
),
inputdatatype=dict(argstr='-inputdatatype %s',
),
inputmodel=dict(argstr='-inputmodel %s',
usedefault=True,
),
ipthresh=dict(argstr='-ipthresh %f',
),
iterations=dict(argstr='-iterations %d',
units='NA',
),
maxcomponents=dict(argstr='-maxcomponents %d',
units='NA',
),
numpds=dict(argstr='-numpds %d',
units='NA',
),
out_file=dict(argstr='-outputfile %s',
genfile=True,
position=-1,
),
output_root=dict(argstr='-outputroot %s',
position=-1,
),
outputtracts=dict(argstr='-outputtracts %s',
),
pdf=dict(argstr='-pdf %s',
),
pointset=dict(argstr='-pointset %s',
),
scheme_file=dict(argstr='-schemefile %s',
mandatory=True,
),
seed_file=dict(argstr='-seedfile %s',
position=2,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
voxel_dims=dict(argstr='-voxeldims %s',
units='mm',
),
)
inputs = TrackBayesDirac.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_TrackBayesDirac_inputs():
input_map = dict(
anisfile=dict(argstr='-anisfile %s', ),
anisthresh=dict(argstr='-anisthresh %f', ),
args=dict(argstr='%s', ),
curveinterval=dict(
argstr='-curveinterval %f',
requires=['curvethresh'],
),
curvepriorg=dict(argstr='-curvepriorg %G', ),
curvepriork=dict(argstr='-curvepriork %G', ),
curvethresh=dict(argstr='-curvethresh %f', ),
data_dims=dict(
argstr='-datadims %s',
units='voxels',
),
datamodel=dict(argstr='-datamodel %s', ),
environ=dict(
nohash=True,
usedefault=True,
),
extpriordatatype=dict(argstr='-extpriordatatype %s', ),
extpriorfile=dict(argstr='-extpriorfile %s', ),
gzip=dict(argstr='-gzip', ),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='-inputfile %s',
position=1,
),
inputdatatype=dict(argstr='-inputdatatype %s', ),
inputmodel=dict(
argstr='-inputmodel %s',
usedefault=True,
),
interpolator=dict(argstr='-interpolator %s', ),
ipthresh=dict(argstr='-ipthresh %f', ),
iterations=dict(
argstr='-iterations %d',
units='NA',
),
maxcomponents=dict(
argstr='-maxcomponents %d',
units='NA',
),
numpds=dict(
argstr='-numpds %d',
units='NA',
),
out_file=dict(
argstr='-outputfile %s',
genfile=True,
position=-1,
),
output_root=dict(
argstr='-outputroot %s',
position=-1,
),
outputtracts=dict(argstr='-outputtracts %s', ),
pdf=dict(argstr='-pdf %s', ),
pointset=dict(argstr='-pointset %s', ),
scheme_file=dict(
argstr='-schemefile %s',
mandatory=True,
),
seed_file=dict(
argstr='-seedfile %s',
position=2,
),
stepsize=dict(
argstr='-stepsize %f',
requires=['tracker'],
),
terminal_output=dict(nohash=True, ),
tracker=dict(
argstr='-tracker %s',
usedefault=True,
),
voxel_dims=dict(
argstr='-voxeldims %s',
units='mm',
),
)
inputs = TrackBayesDirac.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
