def test_Tensor2ApparentDiffusion_outputs():
output_map = dict(ADC=dict(), )
outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs():
input_map = dict(args=dict(argstr='%s',
),
debug=dict(argstr='-debug',
position=1,
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='%s',
mandatory=True,
position=-2,
),
out_filename=dict(argstr='%s',
genfile=True,
position=-1,
),
quiet=dict(argstr='-quiet',
position=1,
),
terminal_output=dict(mandatory=True,
nohash=True,
),
)
inputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_outputs():
output_map = dict(ADC=dict(),
)
outputs = Tensor2ApparentDiffusion.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_Tensor2ApparentDiffusion_inputs():
input_map = dict(
args=dict(argstr='%s', ),
debug=dict(
argstr='-debug',
position=1,
),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
in_file=dict(
argstr='%s',
mandatory=True,
position=-2,
),
out_filename=dict(
argstr='%s',
genfile=True,
position=-1,
),
quiet=dict(
argstr='-quiet',
position=1,
),
terminal_output=dict(
mandatory=True,
nohash=True,
),
)
inputs = Tensor2ApparentDiffusion.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value