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