code: def test_FilterRegressor_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          design_file=dict(
              argstr="-d %s",
              extensions=None,
              mandatory=True,
              position=3,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          filter_all=dict(
              argstr="-f '%s'",
              mandatory=True,
              position=4,
              xor=["filter_columns"],
          ),
          filter_columns=dict(
              argstr="-f '%s'",
              mandatory=True,
              position=4,
              xor=["filter_all"],
          ),
          in_file=dict(
              argstr="-i %s",
              extensions=None,
              mandatory=True,
              position=1,
          ),
          mask=dict(
              argstr="-m %s",
              extensions=None,
          ),
          out_file=dict(
              argstr="-o %s",
              extensions=None,
              genfile=True,
              hash_files=False,
              position=2,
          ),
          out_vnscales=dict(
              argstr="--out_vnscales",
          ),
          output_type=dict(),
          var_norm=dict(
              argstr="--vn",
          ),
      )
      inputs = FilterRegressor.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_FilterRegressor_inputs() without return types