code: def test_ODFRecon_inputs():
      input_map = dict(
          DWI=dict(
              argstr="%s",
              extensions=None,
              mandatory=True,
              position=1,
          ),
          args=dict(
              argstr="%s",
          ),
          dsi=dict(
              argstr="-dsi",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          filter=dict(
              argstr="-f",
          ),
          image_orientation_vectors=dict(
              argstr="-iop %f",
          ),
          matrix=dict(
              argstr="-mat %s",
              extensions=None,
              mandatory=True,
          ),
          n_b0=dict(
              argstr="-b0 %s",
              mandatory=True,
          ),
          n_directions=dict(
              argstr="%s",
              mandatory=True,
              position=2,
          ),
          n_output_directions=dict(
              argstr="%s",
              mandatory=True,
              position=3,
          ),
          oblique_correction=dict(
              argstr="-oc",
          ),
          out_prefix=dict(
              argstr="%s",
              position=4,
              usedefault=True,
          ),
          output_entropy=dict(
              argstr="-oe",
          ),
          output_type=dict(
              argstr="-ot %s",
              usedefault=True,
          ),
          sharpness=dict(
              argstr="-s %f",
          ),
          subtract_background=dict(
              argstr="-bg",
          ),
      )
      inputs = ODFRecon.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_ODFRecon_inputs() without return types