code: def test_TractSkeleton_inputs():
      input_map = dict(
          alt_data_file=dict(
              argstr="-a %s",
              extensions=None,
          ),
          alt_skeleton=dict(
              argstr="-s %s",
              extensions=None,
          ),
          args=dict(
              argstr="%s",
          ),
          data_file=dict(
              extensions=None,
          ),
          distance_map=dict(
              extensions=None,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_file=dict(
              argstr="-i %s",
              extensions=None,
              mandatory=True,
          ),
          output_type=dict(),
          project_data=dict(
              argstr="-p %.3f %s %s %s %s",
              requires=["threshold", "distance_map", "data_file"],
          ),
          projected_data=dict(
              extensions=None,
          ),
          search_mask_file=dict(
              extensions=None,
              xor=["use_cingulum_mask"],
          ),
          skeleton_file=dict(
              argstr="-o %s",
          ),
          threshold=dict(),
          use_cingulum_mask=dict(
              usedefault=True,
              xor=["search_mask_file"],
          ),
      )
      inputs = TractSkeleton.input_spec()
  
      for key, metadata in list(input_map.items()):
          for metakey, value in list(metadata.items()):
              assert getattr(inputs.traits()[key], metakey) == value
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_TractSkeleton_inputs() without return types