code: def test_predict_interval_output_ForecasterSarimax_with_transform_y_and_transform_exog(
      alpha, interval
  ):
      """
      Test predict_interval output of ForecasterSarimax, StandardScaler
      as transformer_y and transformer_exog as transformer_exog.
      """
      transformer_exog = ColumnTransformer(
          [
              ("scale", StandardScaler(), ["exog_1"]),
              ("onehot", OneHotEncoder(), ["exog_2"]),
          ],
          remainder="passthrough",
          verbose_feature_names_out=False,
      )
  
      forecaster = ForecasterSarimax(
          regressor=Sarimax(
              maxiter=1000, method="cg", disp=False, order=(1, 0, 1)
          ),
          transformer_y=StandardScaler(),
          transformer_exog=transformer_exog,
      )
      forecaster.fit(y=y, exog=df_exog)
      predictions = forecaster.predict_interval(
          steps=5, exog=df_exog_predict, alpha=alpha, interval=interval
      )
      expected = pd.DataFrame(
          data=np.array(
              [
                  [0.60687311, 0.50667956, 0.70706666],
                  [0.62484493, 0.49759696, 0.75209289],
                  [0.63515416, 0.50776733, 0.762541],
                  [0.67730912, 0.54992148, 0.80469675],
                  [0.69458838, 0.56720074, 0.82197602],
              ]
          ),
          columns=["pred", "lower_bound", "upper_bound"],
          index=pd.RangeIndex(start=50, stop=55, step=1),
      )
  
      pd.testing.assert_frame_equal(predictions, expected, atol=0.0001)
  
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 9 for calling a global function with example usage: test_predict_interval_output_ForecasterSarimax_with_transform_y_and_transform_exog(alpha, interval) without return types