code: def test_output_backtesting_sarimax_yes_refit_fixed_train_size_yes_exog_interval_with_mocked(
      alpha, interval
  ):
      """
      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),
      metric='mean_absolute_error', interval. 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=["mean_absolute_error"],
          initial_train_size=len(y_datetime) - 12,
          fixed_train_size=True,
          refit=True,
          alpha=alpha,
          interval=interval,
          verbose=False,
      )
  
      expected_metric = [0.31329767191681507]
      expected_values = np.array(
          [
              [0.59409098, -1.08941968, 2.27760163],
              [0.78323365, -2.51570095, 4.08216824],
              [0.99609033, -4.02240666, 6.01458732],
              [0.88202026, -0.79712278, 2.56116331],
              [1.03241114, -2.26295601, 4.32777829],
              [1.16808941, -3.82752621, 6.16370504],
              [0.86535534, -0.82088676, 2.55159744],
              [0.87277596, -2.39786807, 4.14342],
              [0.69357041, -4.32350585, 5.71064667],
              [0.16628876, -1.53370994, 1.86628747],
              [-0.17189178, -3.5242321, 3.18044855],
              [-0.56342057, -5.74734656, 4.62050543],
          ]
      )
  
      expected_backtest_predictions = pd.DataFrame(
          data=expected_values,
          columns=["pred", "lower_bound", "upper_bound"],
          index=pd.date_range(start="2038", periods=12, freq="A"),
      )
  
      assert expected_metric == approx(metric, abs=0.0001)
      pd.testing.assert_frame_equal(
          expected_backtest_predictions,
          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 18 for calling a global function with example usage: test_output_backtesting_sarimax_yes_refit_fixed_train_size_yes_exog_interval_with_mocked(alpha, interval) without return types