code: def test_NwarpApply_inputs():
      input_map = dict(
          ainterp=dict(
              argstr="-ainterp %s",
          ),
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_file=dict(
              argstr="-source %s",
              mandatory=True,
          ),
          interp=dict(
              argstr="-interp %s",
              usedefault=True,
          ),
          inv_warp=dict(
              argstr="-iwarp",
          ),
          master=dict(
              argstr="-master %s",
              extensions=None,
          ),
          out_file=dict(
              argstr="-prefix %s",
              extensions=None,
              name_source="in_file",
              name_template="%s_Nwarp",
          ),
          quiet=dict(
              argstr="-quiet",
              xor=["verb"],
          ),
          short=dict(
              argstr="-short",
          ),
          verb=dict(
              argstr="-verb",
              xor=["quiet"],
          ),
          warp=dict(
              argstr="-nwarp %s",
              mandatory=True,
          ),
      )
      inputs = NwarpApply.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_NwarpApply_inputs() without return types