code: def test_TCorr1D_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          ktaub=dict(
              argstr=" -ktaub",
              position=1,
              xor=["pearson", "spearman", "quadrant"],
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_file=dict(
              argstr="-prefix %s",
              extensions=None,
              keep_extension=True,
              name_source="xset",
              name_template="%s_correlation.nii.gz",
          ),
          outputtype=dict(),
          pearson=dict(
              argstr=" -pearson",
              position=1,
              xor=["spearman", "quadrant", "ktaub"],
          ),
          quadrant=dict(
              argstr=" -quadrant",
              position=1,
              xor=["pearson", "spearman", "ktaub"],
          ),
          spearman=dict(
              argstr=" -spearman",
              position=1,
              xor=["pearson", "quadrant", "ktaub"],
          ),
          xset=dict(
              argstr=" %s",
              copyfile=False,
              extensions=None,
              mandatory=True,
              position=-2,
          ),
          y_1d=dict(
              argstr=" %s",
              extensions=None,
              mandatory=True,
              position=-1,
          ),
      )
      inputs = TCorr1D.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_TCorr1D_inputs() without return types