code: def test_noncentral_chi2_mean(self):
      df_v = np.array([1.0, 3.0, 5.0], dtype=np.float64)
      nc_v = np.array([0.0, 2.0, 4.0], dtype=np.float64)
      expected_mean = stats.ncx2.mean(df=df_v, nc=nc_v)
      nc_chi2 = noncentral_chi2.NoncentralChi2(
          df=df_v, noncentrality=nc_v, validate_args=True
      )
  
      self.assertEqual(nc_chi2.mean().shape, (3,))
      self.assertAllClose(nc_chi2.mean(), expected_mean)
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow
  from tensorflow_probability.python.distributions import noncentral_chi2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the NoncentralChi2Test obj's underlying member method code with example usage: obj.test_noncentral_chi2_mean() without return types