code: def test_predict_interval_ValueError_when_interval_is_not_symmetrical():
      """
      Raise ValueError if `interval` is not symmetrical.
      """
      forecaster = ForecasterSarimax(regressor=Sarimax(order=(1, 1, 1)))
      forecaster.fit(y=y)
      alpha = None
      interval_not_symmetrical = [5, 97.5]
  
      err_msg = re.escape(
          (
              f"When using `interval` in ForecasterSarimax, it must be symmetrical. "
              f"For example, interval of 95% should be as `interval = [2.5, 97.5]`. "
              f"Got {interval_not_symmetrical}."
          )
      )
      with pytest.raises(ValueError, match=err_msg):
          forecaster.predict_interval(
              steps=5, alpha=alpha, interval=interval_not_symmetrical
          )
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.exceptions import NotFittedError
  from pmdarima.arima import ARIMA
  from skforecast.Sarimax import Sarimax
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from skforecast.utils import expand_index
  from sklearn.compose import ColumnTransformer
  from sklearn.preprocessing import StandardScaler
  from sklearn.preprocessing import OneHotEncoder
  from .fixtures_ForecasterSarimax import y
  from .fixtures_ForecasterSarimax import y_lw
  from .fixtures_ForecasterSarimax import exog
  from .fixtures_ForecasterSarimax import exog_lw
  from .fixtures_ForecasterSarimax import exog_predict
  from .fixtures_ForecasterSarimax import exog_lw_predict
  from .fixtures_ForecasterSarimax import y_datetime
  from .fixtures_ForecasterSarimax import y_lw_datetime
  from .fixtures_ForecasterSarimax import exog_datetime
  from .fixtures_ForecasterSarimax import exog_lw_datetime
  from .fixtures_ForecasterSarimax import exog_predict_datetime
  from .fixtures_ForecasterSarimax import exog_lw_predict_datetime
  from .fixtures_ForecasterSarimax import df_exog
  from .fixtures_ForecasterSarimax import df_exog_lw
  from .fixtures_ForecasterSarimax import df_exog_predict
  from .fixtures_ForecasterSarimax import df_exog_lw_predict
  from .fixtures_ForecasterSarimax import df_exog_datetime
  from .fixtures_ForecasterSarimax import df_exog_lw_datetime
  from .fixtures_ForecasterSarimax import df_exog_predict_datetime
  from .fixtures_ForecasterSarimax import df_exog_lw_predict_datetime
label_desc: Use image node_id 4 for calling a global function with example usage: test_predict_interval_ValueError_when_interval_is_not_symmetrical() without return types