code: def test_BET_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          center=dict(
              argstr="-c %s",
              units="voxels",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          frac=dict(
              argstr="-f %.2f",
          ),
          functional=dict(
              argstr="-F",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          in_file=dict(
              argstr="%s",
              copyfile=False,
              extensions=None,
              mandatory=True,
              position=0,
          ),
          mask=dict(
              argstr="-m",
          ),
          mesh=dict(
              argstr="-e",
          ),
          no_output=dict(
              argstr="-n",
          ),
          out_file=dict(
              argstr="%s",
              extensions=None,
              genfile=True,
              hash_files=False,
              position=1,
          ),
          outline=dict(
              argstr="-o",
          ),
          output_type=dict(),
          padding=dict(
              argstr="-Z",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          radius=dict(
              argstr="-r %d",
              units="mm",
          ),
          reduce_bias=dict(
              argstr="-B",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          remove_eyes=dict(
              argstr="-S",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          robust=dict(
              argstr="-R",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          skull=dict(
              argstr="-s",
          ),
          surfaces=dict(
              argstr="-A",
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          t2_guided=dict(
              argstr="-A2 %s",
              extensions=None,
              xor=(
                  "functional",
                  "reduce_bias",
                  "robust",
                  "padding",
                  "remove_eyes",
                  "surfaces",
                  "t2_guided",
              ),
          ),
          threshold=dict(
              argstr="-t",
          ),
          vertical_gradient=dict(
              argstr="-g %.2f",
          ),
      )
      inputs = BET.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_BET_inputs() without return types