code: def test_ConcatenateLTA_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          in_lta1=dict(
              argstr="%s",
              extensions=None,
              mandatory=True,
              position=-3,
          ),
          in_lta2=dict(
              argstr="%s",
              mandatory=True,
              position=-2,
          ),
          invert_1=dict(
              argstr="-invert1",
          ),
          invert_2=dict(
              argstr="-invert2",
          ),
          invert_out=dict(
              argstr="-invertout",
          ),
          out_file=dict(
              argstr="%s",
              extensions=None,
              hash_files=False,
              keep_extension=True,
              name_source=["in_lta1"],
              name_template="%s_concat",
              position=-1,
          ),
          out_type=dict(
              argstr="-out_type %d",
          ),
          subject=dict(
              argstr="-subject %s",
          ),
          subjects_dir=dict(),
          tal_source_file=dict(
              argstr="-tal %s",
              extensions=None,
              position=-5,
              requires=["tal_template_file"],
          ),
          tal_template_file=dict(
              argstr="%s",
              extensions=None,
              position=-4,
              requires=["tal_source_file"],
          ),
      )
      inputs = ConcatenateLTA.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_ConcatenateLTA_inputs() without return types