code: def test_plot_predictions_runs(self):
      series = self._build_test_series(
          shape=[28], freq=pd.DateOffset(days=1)
      )
      predictions = anomaly_detection.detect_anomalies(
          series,
          anomaly_threshold=0.01,
          use_gibbs_predictive_dist=False,
          seed=test_util.test_seed(sampler_type="stateless"),
          num_warmup_steps=5,
          num_samples=5,
      )
      predictions = tf.nest.map_structure(
          lambda x: self.evaluate(x) if tf.is_tensor(x) else x,
          predictions,
      )
      anomaly_detection.plot_predictions(predictions)
  
      batch_predictions = tf.nest.map_structure(
          lambda x: np.stack([x, x], axis=0)
          if isinstance(x, np.ndarray)
          else x,
          predictions,
      )
      with self.assertRaisesRegex(
          ValueError, "must be one-dimensional"
      ):
          anomaly_detection.plot_predictions(batch_predictions)
  
file_path: probability/tensorflow_probability/python/sts/anomaly_detection/anomaly_detection_test.py
imports: from absl.testing import parameterized
  import numpy
  import pandas
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.sts import anomaly_detection
label_desc: Use image node_id 4 for calling the AnomalyDetectionTests obj's underlying member method code with example usage: obj.test_plot_predictions_runs() without return types