code: def test_DenoiseImage_inputs():
      input_map = dict(
          args=dict(
              argstr="%s",
          ),
          dimension=dict(
              argstr="-d %d",
          ),
          environ=dict(
              nohash=True,
              usedefault=True,
          ),
          input_image=dict(
              argstr="-i %s",
              extensions=None,
              mandatory=True,
          ),
          noise_image=dict(
              extensions=None,
              hash_files=False,
              keep_extension=True,
              name_source=["input_image"],
              name_template="%s_noise",
          ),
          noise_model=dict(
              argstr="-n %s",
              usedefault=True,
          ),
          num_threads=dict(
              nohash=True,
              usedefault=True,
          ),
          output_image=dict(
              argstr="-o %s",
              extensions=None,
              hash_files=False,
              keep_extension=True,
              name_source=["input_image"],
              name_template="%s_noise_corrected",
          ),
          save_noise=dict(
              mandatory=True,
              usedefault=True,
              xor=["noise_image"],
          ),
          shrink_factor=dict(
              argstr="-s %s",
              usedefault=True,
          ),
          verbose=dict(
              argstr="-v",
          ),
      )
      inputs = DenoiseImage.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_DenoiseImage_inputs() without return types