code: def test_VBMSegment_inputs():
      input_map = dict(
          bias_corrected_affine=dict(
              field="estwrite.output.bias.affine",
              usedefault=True,
          ),
          bias_corrected_native=dict(
              field="estwrite.output.bias.native",
              usedefault=True,
          ),
          bias_corrected_normalized=dict(
              field="estwrite.output.bias.warped",
              usedefault=True,
          ),
          bias_fwhm=dict(
              field="estwrite.opts.biasfwhm",
              usedefault=True,
          ),
          bias_regularization=dict(
              field="estwrite.opts.biasreg",
              usedefault=True,
          ),
          cleanup_partitions=dict(
              field="estwrite.extopts.cleanup",
              usedefault=True,
          ),
          csf_dartel=dict(
              field="estwrite.output.CSF.dartel",
              usedefault=True,
          ),
          csf_modulated_normalized=dict(
              field="estwrite.output.CSF.modulated",
              usedefault=True,
          ),
          csf_native=dict(
              field="estwrite.output.CSF.native",
              usedefault=True,
          ),
          csf_normalized=dict(
              field="estwrite.output.CSF.warped",
              usedefault=True,
          ),
          dartel_template=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
              field="estwrite.extopts.dartelwarp.normhigh.darteltpm",
          ),
          deformation_field=dict(
              field="estwrite.output.warps",
              usedefault=True,
          ),
          display_results=dict(
              field="estwrite.extopts.print",
              usedefault=True,
          ),
          gaussians_per_class=dict(
              usedefault=True,
          ),
          gm_dartel=dict(
              field="estwrite.output.GM.dartel",
              usedefault=True,
          ),
          gm_modulated_normalized=dict(
              field="estwrite.output.GM.modulated",
              usedefault=True,
          ),
          gm_native=dict(
              field="estwrite.output.GM.native",
              usedefault=True,
          ),
          gm_normalized=dict(
              field="estwrite.output.GM.warped",
              usedefault=True,
          ),
          in_files=dict(
              copyfile=False,
              field="estwrite.data",
              mandatory=True,
          ),
          jacobian_determinant=dict(
              field="estwrite.jacobian.warped",
              usedefault=True,
          ),
          matlab_cmd=dict(),
          mfile=dict(
              usedefault=True,
          ),
          mrf_weighting=dict(
              field="estwrite.extopts.mrf",
              usedefault=True,
          ),
          paths=dict(),
          pve_label_dartel=dict(
              field="estwrite.output.label.dartel",
              usedefault=True,
          ),
          pve_label_native=dict(
              field="estwrite.output.label.native",
              usedefault=True,
          ),
          pve_label_normalized=dict(
              field="estwrite.output.label.warped",
              usedefault=True,
          ),
          sampling_distance=dict(
              field="estwrite.opts.samp",
              usedefault=True,
          ),
          spatial_normalization=dict(
              usedefault=True,
          ),
          tissues=dict(
              extensions=[".hdr", ".img", ".img.gz", ".nii"],
              field="estwrite.tpm",
          ),
          use_mcr=dict(),
          use_sanlm_denoising_filter=dict(
              field="estwrite.extopts.sanlm",
              usedefault=True,
          ),
          use_v8struct=dict(
              min_ver="8",
              usedefault=True,
          ),
          warping_regularization=dict(
              field="estwrite.opts.warpreg",
              usedefault=True,
          ),
          wm_dartel=dict(
              field="estwrite.output.WM.dartel",
              usedefault=True,
          ),
          wm_modulated_normalized=dict(
              field="estwrite.output.WM.modulated",
              usedefault=True,
          ),
          wm_native=dict(
              field="estwrite.output.WM.native",
              usedefault=True,
          ),
          wm_normalized=dict(
              field="estwrite.output.WM.warped",
              usedefault=True,
          ),
      )
      inputs = VBMSegment.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_VBMSegment_inputs() without return types