code: def test_MRConvert_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          extension=dict(
              position=2,
              usedefault=True,
          ),
          extract_at_axis=dict(
              argstr="-coord %s",
              position=1,
          ),
          extract_at_coordinate=dict(
              argstr="%s",
              position=2,
              sep=",",
          ),
          in_file=dict(
              argstr="%s",
              extensions=None,
              mandatory=True,
              position=-2,
          ),
          layout=dict(
              argstr="-output %s",
              position=2,
          ),
          offset_bias=dict(
              argstr="-scale %d",
              position=3,
              units="mm",
          ),
          out_filename=dict(
              argstr="%s",
              extensions=None,
              genfile=True,
              position=-1,
          ),
          output_datatype=dict(
              argstr="-output %s",
              position=2,
          ),
          prs=dict(
              argstr="-prs",
              position=3,
          ),
          replace_NaN_with_zero=dict(
              argstr="-zero",
              position=3,
          ),
          resample=dict(
              argstr="-scale %d",
              position=3,
              units="mm",
          ),
          voxel_dims=dict(
              argstr="-vox %s",
              position=3,
              sep=",",
          ),
      )
      inputs = MRConvert.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_MRConvert_inputs() without return types