code: def test_dtiestim_inputs():
      input_map = dict(
          B0=dict(
              argstr="--B0 %s",
              hash_files=False,
          ),
          B0_mask_output=dict(
              argstr="--B0_mask_output %s",
              hash_files=False,
          ),
          DTI_double=dict(
              argstr="--DTI_double ",
          ),
          args=dict(
              argstr="%s",
          ),
          bad_region_mask=dict(
              argstr="--bad_region_mask %s",
              extensions=None,
          ),
          brain_mask=dict(
              argstr="--brain_mask %s",
              extensions=None,
          ),
          correction=dict(
              argstr="--correction %s",
          ),
          defaultTensor=dict(
              argstr="--defaultTensor %s",
              sep=",",
          ),
          dwi_image=dict(
              argstr="--dwi_image %s",
              extensions=None,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          idwi=dict(
              argstr="--idwi %s",
              hash_files=False,
          ),
          method=dict(
              argstr="--method %s",
          ),
          shiftNeg=dict(
              argstr="--shiftNeg ",
          ),
          shiftNegCoeff=dict(
              argstr="--shiftNegCoeff %f",
          ),
          sigma=dict(
              argstr="--sigma %f",
          ),
          step=dict(
              argstr="--step %f",
          ),
          tensor_output=dict(
              argstr="--tensor_output %s",
              hash_files=False,
          ),
          threshold=dict(
              argstr="--threshold %d",
          ),
          verbose=dict(
              argstr="--verbose ",
          ),
          weight_iterations=dict(
              argstr="--weight_iterations %d",
          ),
      )
      inputs = dtiestim.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_dtiestim_inputs() without return types