code: def test_dtiprocess_inputs():
      input_map = dict(
          DTI_double=dict(
              argstr="--DTI_double ",
          ),
          RD_output=dict(
              argstr="--RD_output %s",
              hash_files=False,
          ),
          affineitk_file=dict(
              argstr="--affineitk_file %s",
              extensions=None,
          ),
          args=dict(
              argstr="%s",
          ),
          color_fa_output=dict(
              argstr="--color_fa_output %s",
              hash_files=False,
          ),
          correction=dict(
              argstr="--correction %s",
          ),
          deformation_output=dict(
              argstr="--deformation_output %s",
              hash_files=False,
          ),
          dof_file=dict(
              argstr="--dof_file %s",
              extensions=None,
          ),
          dti_image=dict(
              argstr="--dti_image %s",
              extensions=None,
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          fa_gradient_output=dict(
              argstr="--fa_gradient_output %s",
              hash_files=False,
          ),
          fa_gradmag_output=dict(
              argstr="--fa_gradmag_output %s",
              hash_files=False,
          ),
          fa_output=dict(
              argstr="--fa_output %s",
              hash_files=False,
          ),
          forward=dict(
              argstr="--forward %s",
              extensions=None,
          ),
          frobenius_norm_output=dict(
              argstr="--frobenius_norm_output %s",
              hash_files=False,
          ),
          hField=dict(
              argstr="--hField ",
          ),
          interpolation=dict(
              argstr="--interpolation %s",
          ),
          lambda1_output=dict(
              argstr="--lambda1_output %s",
              hash_files=False,
          ),
          lambda2_output=dict(
              argstr="--lambda2_output %s",
              hash_files=False,
          ),
          lambda3_output=dict(
              argstr="--lambda3_output %s",
              hash_files=False,
          ),
          mask=dict(
              argstr="--mask %s",
              extensions=None,
          ),
          md_output=dict(
              argstr="--md_output %s",
              hash_files=False,
          ),
          negative_eigenvector_output=dict(
              argstr="--negative_eigenvector_output %s",
              hash_files=False,
          ),
          newdof_file=dict(
              argstr="--newdof_file %s",
              extensions=None,
          ),
          outmask=dict(
              argstr="--outmask %s",
              hash_files=False,
          ),
          principal_eigenvector_output=dict(
              argstr="--principal_eigenvector_output %s",
              hash_files=False,
          ),
          reorientation=dict(
              argstr="--reorientation %s",
          ),
          rot_output=dict(
              argstr="--rot_output %s",
              hash_files=False,
          ),
          scalar_float=dict(
              argstr="--scalar_float ",
          ),
          sigma=dict(
              argstr="--sigma %f",
          ),
          verbose=dict(
              argstr="--verbose ",
          ),
      )
      inputs = dtiprocess.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_dtiprocess_inputs() without return types