def test_SmoothTessellation_outputs(): output_map = dict(surface=dict(), ) outputs = SmoothTessellation.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_SmoothTessellation_inputs(): input_map = dict( args=dict(argstr='%s', ), curvature_averaging_iterations=dict( argstr='-a %d', position=-1, usedefault=True, ), disable_estimates=dict(argstr='-nw', ), environ=dict( nohash=True, usedefault=True, ), gaussian_curvature_norm_steps=dict( argstr='%d ', position=4, ), gaussian_curvature_smoothing_steps=dict( argstr='%d', position=5, ), ignore_exception=dict( nohash=True, usedefault=True, ), in_file=dict( argstr='%s', mandatory=True, position=1, ), normalize_area=dict(argstr='-area', ), out_area_file=dict(argstr='-b %s', ), out_curvature_file=dict(argstr='-c %s', ), out_file=dict( argstr='%s', genfile=True, position=2, ), smoothing_iterations=dict( argstr='-n %d', position=-2, usedefault=True, ), snapshot_writing_iterations=dict(argstr='-w %d', ), subjects_dir=dict(), terminal_output=dict( mandatory=True, nohash=True, ), use_gaussian_curvature_smoothing=dict( argstr='-g', position=3, ), use_momentum=dict(argstr='-m', ), ) inputs = SmoothTessellation.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_SmoothTessellation_outputs(): output_map = dict(surface=dict(), ) outputs = SmoothTessellation.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_SmoothTessellation_inputs(): input_map = dict(ignore_exception=dict(nohash=True, usedefault=True, ), smoothing_iterations=dict(position=-2, argstr='-n %d', usedefault=True, ), normalize_area=dict(argstr='-area', ), snapshot_writing_iterations=dict(argstr='-w %d', ), out_file=dict(position=2, genfile=True, argstr='%s', ), disable_estimates=dict(argstr='-nw', ), out_area_file=dict(argstr='-b %s', ), args=dict(argstr='%s', ), use_gaussian_curvature_smoothing=dict(position=3, argstr='-g', ), out_curvature_file=dict(argstr='-c %s', ), curvature_averaging_iterations=dict(position=-1, argstr='-a %d', usedefault=True, ), terminal_output=dict(mandatory=True, nohash=True, ), environ=dict(nohash=True, usedefault=True, ), in_file=dict(position=1, mandatory=True, argstr='%s', ), gaussian_curvature_smoothing_steps=dict(position=5, argstr='%d', ), subjects_dir=dict(), gaussian_curvature_norm_steps=dict(position=4, argstr='%d ', ), use_momentum=dict(argstr='-m', ), ) inputs = SmoothTessellation.input_spec() for key, metadata in input_map.items(): for metakey, value in metadata.items(): yield assert_equal, getattr(inputs.traits()[key], metakey), value