code: def test_FNIRT_inputs():
      input_map = dict(
          affine_file=dict(
              argstr="--aff=%s",
              extensions=None,
          ),
          apply_inmask=dict(
              argstr="--applyinmask=%s",
              sep=",",
              xor=["skip_inmask"],
          ),
          apply_intensity_mapping=dict(
              argstr="--estint=%s",
              sep=",",
              xor=["skip_intensity_mapping"],
          ),
          apply_refmask=dict(
              argstr="--applyrefmask=%s",
              sep=",",
              xor=["skip_refmask"],
          ),
          args=dict(
              argstr="%s",
          ),
          bias_regularization_lambda=dict(
              argstr="--biaslambda=%f",
          ),
          biasfield_resolution=dict(
              argstr="--biasres=%d,%d,%d",
          ),
          config_file=dict(
              argstr="--config=%s",
          ),
          derive_from_ref=dict(
              argstr="--refderiv",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          field_file=dict(
              argstr="--fout=%s",
              hash_files=False,
          ),
          fieldcoeff_file=dict(
              argstr="--cout=%s",
          ),
          hessian_precision=dict(
              argstr="--numprec=%s",
          ),
          in_file=dict(
              argstr="--in=%s",
              extensions=None,
              mandatory=True,
          ),
          in_fwhm=dict(
              argstr="--infwhm=%s",
              sep=",",
          ),
          in_intensitymap_file=dict(
              argstr="--intin=%s",
              copyfile=False,
          ),
          inmask_file=dict(
              argstr="--inmask=%s",
              extensions=None,
          ),
          inmask_val=dict(
              argstr="--impinval=%f",
          ),
          intensity_mapping_model=dict(
              argstr="--intmod=%s",
          ),
          intensity_mapping_order=dict(
              argstr="--intorder=%d",
          ),
          inwarp_file=dict(
              argstr="--inwarp=%s",
              extensions=None,
          ),
          jacobian_file=dict(
              argstr="--jout=%s",
              hash_files=False,
          ),
          jacobian_range=dict(
              argstr="--jacrange=%f,%f",
          ),
          log_file=dict(
              argstr="--logout=%s",
              extensions=None,
              genfile=True,
              hash_files=False,
          ),
          max_nonlin_iter=dict(
              argstr="--miter=%s",
              sep=",",
          ),
          modulatedref_file=dict(
              argstr="--refout=%s",
              hash_files=False,
          ),
          out_intensitymap_file=dict(
              argstr="--intout=%s",
              hash_files=False,
          ),
          output_type=dict(),
          ref_file=dict(
              argstr="--ref=%s",
              extensions=None,
              mandatory=True,
          ),
          ref_fwhm=dict(
              argstr="--reffwhm=%s",
              sep=",",
          ),
          refmask_file=dict(
              argstr="--refmask=%s",
              extensions=None,
          ),
          refmask_val=dict(
              argstr="--imprefval=%f",
          ),
          regularization_lambda=dict(
              argstr="--lambda=%s",
              sep=",",
          ),
          regularization_model=dict(
              argstr="--regmod=%s",
          ),
          skip_implicit_in_masking=dict(
              argstr="--impinm=0",
          ),
          skip_implicit_ref_masking=dict(
              argstr="--imprefm=0",
          ),
          skip_inmask=dict(
              argstr="--applyinmask=0",
              xor=["apply_inmask"],
          ),
          skip_intensity_mapping=dict(
              argstr="--estint=0",
              xor=["apply_intensity_mapping"],
          ),
          skip_lambda_ssq=dict(
              argstr="--ssqlambda=0",
          ),
          skip_refmask=dict(
              argstr="--applyrefmask=0",
              xor=["apply_refmask"],
          ),
          spline_order=dict(
              argstr="--splineorder=%d",
          ),
          subsampling_scheme=dict(
              argstr="--subsamp=%s",
              sep=",",
          ),
          warp_resolution=dict(
              argstr="--warpres=%d,%d,%d",
          ),
          warped_file=dict(
              argstr="--iout=%s",
              extensions=None,
              genfile=True,
              hash_files=False,
          ),
      )
      inputs = FNIRT.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_FNIRT_inputs() without return types