code: def test_FIRST_inputs():
      input_map = dict(
          affine_file=dict(
              argstr="-a %s",
              extensions=None,
              position=6,
          ),
          args=dict(
              argstr="%s",
          ),
          brain_extracted=dict(
              argstr="-b",
              position=2,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_file=dict(
              argstr="-i %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
              position=-2,
          ),
          list_of_specific_structures=dict(
              argstr="-s %s",
              position=5,
              sep=",",
          ),
          method=dict(
              argstr="-m %s",
              position=4,
              usedefault=True,
              xor=["method_as_numerical_threshold"],
          ),
          method_as_numerical_threshold=dict(
              argstr="-m %.4f",
              position=4,
          ),
          no_cleanup=dict(
              argstr="-d",
              position=3,
          ),
          out_file=dict(
              argstr="-o %s",
              extensions=None,
              hash_files=False,
              mandatory=True,
              position=-1,
              usedefault=True,
          ),
          output_type=dict(),
          verbose=dict(
              argstr="-v",
              position=1,
          ),
      )
      inputs = FIRST.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_FIRST_inputs() without return types