code: def test_JointFusion_inputs():
      input_map = dict(
          alpha=dict(
              argstr="-a %s",
              usedefault=True,
          ),
          args=dict(
              argstr="%s",
          ),
          atlas_image=dict(
              argstr="-g %s...",
              mandatory=True,
          ),
          atlas_segmentation_image=dict(
              argstr="-l %s...",
              mandatory=True,
          ),
          beta=dict(
              argstr="-b %s",
              usedefault=True,
          ),
          constrain_nonnegative=dict(
              argstr="-c",
              usedefault=True,
          ),
          dimension=dict(
              argstr="-d %d",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          exclusion_image=dict(),
          exclusion_image_label=dict(
              argstr="-e %s",
              requires=["exclusion_image"],
          ),
          mask_image=dict(
              argstr="-x %s",
              extensions=None,
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          out_atlas_voting_weight_name_format=dict(
              requires=[
                  "out_label_fusion",
                  "out_intensity_fusion_name_format",
                  "out_label_post_prob_name_format",
              ],
          ),
          out_intensity_fusion_name_format=dict(
              argstr="",
          ),
          out_label_fusion=dict(
              argstr="%s",
              extensions=None,
              hash_files=False,
          ),
          out_label_post_prob_name_format=dict(
              requires=[
                  "out_label_fusion",
                  "out_intensity_fusion_name_format",
              ],
          ),
          patch_metric=dict(
              argstr="-m %s",
          ),
          patch_radius=dict(
              argstr="-p %s",
              maxlen=3,
              minlen=3,
          ),
          retain_atlas_voting_images=dict(
              argstr="-f",
              usedefault=True,
          ),
          retain_label_posterior_images=dict(
              argstr="-r",
              requires=["atlas_segmentation_image"],
              usedefault=True,
          ),
          search_radius=dict(
              argstr="-s %s",
              usedefault=True,
          ),
          target_image=dict(
              argstr="-t %s",
              mandatory=True,
          ),
          verbose=dict(
              argstr="-v",
          ),
      )
      inputs = JointFusion.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_JointFusion_inputs() without return types