code: def test_output_random_search_sarimax_sarimax_with_mocked():
      """
      Test output of random_search_sarimax in ForecasterSarimax with mocked
      (mocked done in Skforecast v0.7.0).
      """
      forecaster = ForecasterSarimax(
          regressor=Sarimax(
              order=(3, 2, 0), maxiter=1000, method="cg", disp=False
          )
      )
  
      param_distributions = {"order": [(2, 2, 0), (3, 2, 0)]}
  
      results = random_search_sarimax(
          forecaster=forecaster,
          y=y_datetime,
          param_distributions=param_distributions,
          n_iter=2,
          random_state=123,
          steps=3,
          refit=False,
          metric="mean_absolute_error",
          initial_train_size=len(y_datetime) - 12,
          fixed_train_size=False,
          return_best=False,
          verbose=False,
      )
  
      expected_results = pd.DataFrame(
          data={
              "params": np.array(
                  [{"order": (3, 2, 0)}, {"order": (2, 2, 0)}],
                  dtype=object,
              ),
              "mean_absolute_error": np.array([0.15357204, 0.19853423]),
              "order": [(3, 2, 0), (2, 2, 0)],
          },
          index=pd.Index(np.array([1, 0]), dtype="int64"),
      )
  
      pd.testing.assert_frame_equal(
          results, expected_results, atol=0.001
      )
  
file_path: skforecast/skforecast/model_selection_sarimax/test/test_random_search_sarimax.py
imports: import re
  import pytest
  import platform
  import numpy
  import pandas
  from skforecast.Sarimax import Sarimax
  from skforecast.ForecasterSarimax import ForecasterSarimax
  from skforecast.model_selection_sarimax import random_search_sarimax
  from tqdm import tqdm
  from functools import partialmethod
  from ...ForecasterSarimax.tests.fixtures_ForecasterSarimax import y_datetime
label_desc: Use image node_id 1 for calling a global function with example usage: test_output_random_search_sarimax_sarimax_with_mocked() without return types