def test_SimilarityIndex_inputs():
input_map = dict(ANNContinuousVolume=dict(argstr='--ANNContinuousVolume %s',
),
args=dict(argstr='%s',
),
environ=dict(nohash=True,
usedefault=True,
),
ignore_exception=dict(nohash=True,
usedefault=True,
),
inputManualVolume=dict(argstr='--inputManualVolume %s',
),
outputCSVFilename=dict(argstr='--outputCSVFilename %s',
),
terminal_output=dict(nohash=True,
),
thresholdInterval=dict(argstr='--thresholdInterval %f',
),
)
inputs = SimilarityIndex.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_SimilarityIndex_outputs():
output_map = dict()
outputs = SimilarityIndex.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_SimilarityIndex_outputs():
output_map = dict()
outputs = SimilarityIndex.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_SimilarityIndex_inputs():
input_map = dict(
ANNContinuousVolume=dict(argstr='--ANNContinuousVolume %s', ),
args=dict(argstr='%s', ),
environ=dict(
nohash=True,
usedefault=True,
),
ignore_exception=dict(
nohash=True,
usedefault=True,
),
inputManualVolume=dict(argstr='--inputManualVolume %s', ),
outputCSVFilename=dict(argstr='--outputCSVFilename %s', ),
terminal_output=dict(nohash=True, ),
thresholdInterval=dict(argstr='--thresholdInterval %f', ),
)
inputs = SimilarityIndex.input_spec()
for key, metadata in input_map.items():
for metakey, value in metadata.items():
yield assert_equal, getattr(inputs.traits()[key], metakey), value
