code: def test_Sarimax_predict_interval_with_numpy():
      """
      Test Sarimax predict with confidence intervals using numpy `y` and `exog`.
      It is tested with the skforecast wrapper and the statsmodels SARIMAX.
      """
  
      alpha = 0.05
  
      # skforecast
      sarimax = Sarimax(
          order=(1, 1, 1), maxiter=1000, method="cg", disp=False
      )
      sarimax.fit(y=y_numpy, exog=exog_numpy)
      preds_skforecast = sarimax.predict(
          steps=10,
          exog=exog_predict_numpy,
          return_conf_int=True,
          alpha=alpha,
      )
  
      # statsmodels
      sarimax = SARIMAX(order=(1, 1, 1), endog=y_numpy, exog=exog_numpy)
      sarimax_res = sarimax.fit(maxiter=1000, method="cg", disp=False)
      preds_statsmodels = sarimax_res.get_forecast(
          steps=10, exog=exog_predict_numpy
      )
      preds_statsmodels = np.column_stack(
          [
              preds_statsmodels.predicted_mean,
              preds_statsmodels.conf_int(alpha=alpha),
          ]
      )
  
      # expected = np.array([[ 0.54251563, -1.19541248,  2.28044374],
      #                      [ 0.57444558, -1.81113178,  2.96002293],
      #                      [ 0.60419802, -2.26035953,  3.46875557],
      #                      [ 0.63585684, -2.62746432,  3.899178  ],
      #                      [ 0.67238625, -2.94147506,  4.28624756],
      #                      [ 0.70992311, -3.22142148,  4.64126771],
      #                      [ 0.76089838, -3.46329933,  4.98509609],
      #                      [ 0.7855481 , -3.7121082 ,  5.28320441],
      #                      [ 0.73117064, -4.02408271,  5.48642398],
      #                      [ 0.669226  , -4.3302976 ,  5.66874961]])
  
      # np.testing.assert_almost_equal(preds_skforecast, expected)
      # np.testing.assert_almost_equal(preds_statsmodels, expected)
      np.testing.assert_almost_equal(
          preds_skforecast, preds_statsmodels
      )
  
imports: import re
  import pytest
  import numpy
  import pandas
  from sklearn.exceptions import NotFittedError
  from skforecast.Sarimax import Sarimax
  from statsmodels.tsa.statespace.sarimax import SARIMAX
  from statsmodels.tsa.statespace.sarimax import SARIMAXResults
  from statsmodels.tsa.statespace.sarimax import SARIMAXResultsWrapper
  from .fixtures_Sarimax import y
  from .fixtures_Sarimax import y_lw
  from .fixtures_Sarimax import exog
  from .fixtures_Sarimax import exog_lw
  from .fixtures_Sarimax import exog_predict
  from .fixtures_Sarimax import exog_lw_predict
  from .fixtures_Sarimax import y_datetime
  from .fixtures_Sarimax import exog_datetime
  from .fixtures_Sarimax import exog_predict_datetime
label_desc: Use image node_id 13 for calling a global function with example usage: test_Sarimax_predict_interval_with_numpy() without return types