def test_MRIsConvert_outputs():
output_map = dict(converted=dict(), )
outputs = MRIsConvert.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_MRIsConvert_inputs():
input_map = dict(out_datatype=dict(mandatory=True,
),
scale=dict(argstr='-s %.3f',
),
functional_file=dict(argstr='-f %s',
),
labelstats_outfile=dict(argstr='--labelstats %s',
),
in_file=dict(position=-2,
mandatory=True,
argstr='%s',
),
talairachxfm_subjid=dict(argstr='-t %s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
origname=dict(argstr='-o %s',
),
normal=dict(argstr='-n',
),
rescale=dict(argstr='-r',
),
args=dict(argstr='%s',
),
vertex=dict(argstr='-v',
),
terminal_output=dict(mandatory=True,
nohash=True,
),
subjects_dir=dict(),
xyz_ascii=dict(argstr='-a',
),
out_file=dict(position=-1,
genfile=True,
argstr='./%s',
),
patch=dict(argstr='-p',
),
environ=dict(nohash=True,
usedefault=True,
),
label_file=dict(argstr='--label %s',
),
parcstats_file=dict(argstr='--parcstats %s',
),
annot_file=dict(argstr='--annot %s',
),
scalarcurv_file=dict(argstr='-c %s',
),
dataarray_num=dict(argstr='--da_num %d',
),
)
inputs = MRIsConvert.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_MRIsConvert_outputs():
output_map = dict(converted=dict(),
)
outputs = MRIsConvert.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_MRIsConvert_inputs():
input_map = dict(annot_file=dict(argstr='--annot %s',
),
args=dict(argstr='%s',
),
dataarray_num=dict(argstr='--da_num %d',
),
environ=dict(nohash=True,
usedefault=True,
),
functional_file=dict(argstr='-f %s',
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
in_file=dict(argstr='%s',
mandatory=True,
position=-2,
),
label_file=dict(argstr='--label %s',
),
labelstats_outfile=dict(argstr='--labelstats %s',
),
normal=dict(argstr='-n',
),
origname=dict(argstr='-o %s',
),
out_datatype=dict(mandatory=True,
),
out_file=dict(argstr='./%s',
genfile=True,
position=-1,
),
parcstats_file=dict(argstr='--parcstats %s',
),
patch=dict(argstr='-p',
),
rescale=dict(argstr='-r',
),
scalarcurv_file=dict(argstr='-c %s',
),
scale=dict(argstr='-s %.3f',
),
subjects_dir=dict(),
talairachxfm_subjid=dict(argstr='-t %s',
),
terminal_output=dict(nohash=True,
),
vertex=dict(argstr='-v',
),
xyz_ascii=dict(argstr='-a',
),
)
inputs = MRIsConvert.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value