def test_ComputeMeanDiffusivity_inputs():
input_map = dict(
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='< %s',
mandatory=True,
position=1,
),
inputdatatype=dict(argstr='-inputdatatype %s', ),
inputmodel=dict(argstr='-inputmodel %s', ),
out_file=dict(
argstr='> %s',
genfile=True,
position=-1,
),
outputdatatype=dict(argstr='-outputdatatype %s', ),
scheme_file=dict(
argstr='%s',
position=2,
),
terminal_output=dict(nohash=True, ),
)
inputs = ComputeMeanDiffusivity.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_ComputeMeanDiffusivity_outputs():
output_map = dict(md=dict(), )
outputs = ComputeMeanDiffusivity.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_ComputeMeanDiffusivity_inputs():
input_map = dict(args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='< %s',
mandatory=True,
position=1,
),
inputdatatype=dict(argstr='-inputdatatype %s',
),
inputmodel=dict(argstr='-inputmodel %s',
),
out_file=dict(argstr='> %s',
genfile=True,
position=-1,
),
outputdatatype=dict(argstr='-outputdatatype %s',
),
scheme_file=dict(argstr='%s',
position=2,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = ComputeMeanDiffusivity.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_ComputeMeanDiffusivity_outputs():
output_map = dict(md=dict(),
)
outputs = ComputeMeanDiffusivity.output_spec()
for key, metadata in output_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(outputs.traits()[key], metakey), value
