code: def test_ensemble_adjustment_kalman_filter_expect_univariate(self):
      state = ekf.EnsembleKalmanFilterState(
          step=0, particles=[1.0], extra=None
      )
  
      # Multivariate observations not implemented.
      with self.assertRaises(NotImplementedError):
          state = eakf.ensemble_adjustment_kalman_filter_update(
              state,
              observation=[0.0, 1.0],
              observation_fn=lambda t, p, e: ([p, p], e),
          )
  
file_path: probability/tensorflow_probability/python/experimental/sequential/ensemble_adjustment_kalman_filter_test.py
imports: import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import joint_distribution_named
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.experimental.sequential import ensemble_adjustment_kalman_filter
  from tensorflow_probability.python.experimental.sequential import ensemble_kalman_filter
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the EnsembleAdjustmentKalmanFilterTest obj's underlying member method code with example usage: obj.test_ensemble_adjustment_kalman_filter_expect_univariate() without return types