code: def test_gibbs():
      """Test _transform method including gibbs sampling iterations."""
      expected = [
          [
              0.72269469,
              3.20993546,
              0.59599049,
              0.40400951,
              0.8,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
              1.0,
              1.0,
              1.0,
              1.0,
              1.0,
              -17.9650666,
              -4.50125762,
          ],
          [
              0.85025968,
              2.32993642,
              0.80166206,
              0.19833794,
              0.8,
              0.0,
              0.0,
              0.0,
              0.0,
              0.0,
              1.0,
              1.0,
              1.0,
              1.0,
              0.0,
              -19.21897121,
              -7.78773922,
          ],
      ]
  
      model = Hidalgo(
          K=2, n_iter=10, burn_in=0.5, sampling_rate=2, seed=1
      )
      _rng = check_random_state(model.seed)
  
      (
          N,
          mu,
          Iin,
          Iout,
          Iout_count,
          Iout_track,
      ) = model._get_neighbourhood_params(X)
      V, NN, a1, b1, c1, Z, f1, N_in = model._initialise_params(
          N, mu, Iin, _rng
      )
  
      sampling = model._gibbs_sampling(
          N,
          mu,
          Iin,
          Iout,
          Iout_count,
          Iout_track,
          V,
          NN,
          a1,
          b1,
          c1,
          Z,
          f1,
          N_in,
          _rng,
      )
      sampling = np.reshape(sampling, (10, 17))
      actual = sampling[[6, 8],]
  
      assert np.allclose(actual, expected)
  
imports: import numpy
  from sklearn.utils.validation import check_random_state
  from sktime.transformations.series.hidalgo import Hidalgo
label_desc: Use image node_id 4 for calling a global function with example usage: test_gibbs() without return types