code: def test_MS_LDA_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          conform=dict(
              argstr="-conform",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          images=dict(
              argstr="%s",
              copyfile=False,
              mandatory=True,
              position=-1,
          ),
          label_file=dict(
              argstr="-label %s",
              extensions=None,
          ),
          lda_labels=dict(
              argstr="-lda %s",
              mandatory=True,
              sep=" ",
          ),
          mask_file=dict(
              argstr="-mask %s",
              extensions=None,
          ),
          shift=dict(
              argstr="-shift %d",
          ),
          subjects_dir=dict(),
          use_weights=dict(
              argstr="-W",
          ),
          vol_synth_file=dict(
              argstr="-synth %s",
              extensions=None,
              mandatory=True,
          ),
          weight_file=dict(
              argstr="-weight %s",
              extensions=None,
              mandatory=True,
          ),
      )
      inputs = MS_LDA.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_MS_LDA_inputs() without return types