code: def test_output_backtesting_sarimax_yes_refit_fixed_train_size_yes_exog_list_of_metrics_with_mocked():
      """
      Test output of backtesting_sarimax with backtesting mocked, Series y is mocked, yes exog,
      yes refit, fixed_train_size, 12 observations to backtest, steps=3 (no remainder),
      list of metrics. Mocked done with skforecast 0.7.0.
      """
      forecaster = ForecasterSarimax(
          regressor=Sarimax(
              order=(3, 2, 0), maxiter=1000, method="cg", disp=False
          )
      )
  
      metric, backtest_predictions = backtesting_sarimax(
          forecaster=forecaster,
          y=y_datetime,
          exog=exog_datetime,
          steps=3,
          metric=[my_metric, "mean_absolute_error"],
          initial_train_size=len(y_datetime) - 12,
          fixed_train_size=True,
          refit=True,
          alpha=None,
          interval=None,
          verbose=False,
      )
  
      expected_metric = [0.007877420102652216, 0.31329767191681507]
      expected_preds = pd.DataFrame(
          data=np.array(
              [
                  0.59409098,
                  0.78323365,
                  0.99609033,
                  0.88202026,
                  1.03241114,
                  1.16808941,
                  0.86535534,
                  0.87277596,
                  0.69357041,
                  0.16628876,
                  -0.17189178,
                  -0.56342057,
              ]
          ),
          columns=["pred"],
          index=pd.date_range(start="2038", periods=12, freq="A"),
      )
  
      assert expected_metric == approx(metric, abs=0.0001)
      pd.testing.assert_frame_equal(
          expected_preds, backtest_predictions, atol=0.0001
      )
  
imports: import re
  import pytest
  import platform
  from pytest import approx
  import numpy
  import pandas
  from sklearn.linear_model import Ridge
  from pmdarima.arima import ARIMA
  from skforecast.Sarimax import Sarimax
  from skforecast.ForecasterAutoreg import ForecasterAutoreg
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from skforecast.model_selection_sarimax import backtesting_sarimax
  from ...ForecasterSarimax.tests.fixtures_ForecasterSarimax import y_datetime
  from ...ForecasterSarimax.tests.fixtures_ForecasterSarimax import exog_datetime
label_desc: Use image node_id 15 for calling a global function with example usage: test_output_backtesting_sarimax_yes_refit_fixed_train_size_yes_exog_list_of_metrics_with_mocked() without return types