code: def test_backtesting_with_ForecasterEquivalentDate():
      """
      Test backtesting with ForecasterEquivalentDate.
      """
      forecaster = ForecasterEquivalentDate(
          offset=pd.DateOffset(days=10), n_offsets=2
      )
  
      metric, predictions = backtesting_forecaster(
          forecaster=forecaster,
          y=y,
          initial_train_size=30,
          steps=5,
          metric="mean_absolute_error",
          refit=True,
          verbose=False,
          n_jobs="auto",
      )
  
      expected = pd.DataFrame(
          data=np.array(
              [
                  0.48878949,
                  0.78924075,
                  0.58151378,
                  0.3353507,
                  0.56024382,
                  0.53047716,
                  0.27214019,
                  0.20185749,
                  0.41263271,
                  0.58140185,
                  0.36325295,
                  0.64156648,
                  0.57765904,
                  0.5523543,
                  0.57413684,
                  0.31761006,
                  0.39406999,
                  0.56082619,
                  0.61893703,
                  0.5664064,
              ]
          ),
          index=pd.date_range(start="2000-01-31", periods=20, freq="D"),
          columns=["pred"],
      )
  
      assert metric == 0.2537094475
      pd.testing.assert_frame_equal(predictions, expected)
  
imports: import numpy
  import pandas
  from skforecast.ForecasterBaseline import ForecasterEquivalentDate
  from skforecast.model_selection import backtesting_forecaster
  from .fixtures_ForecasterEquivalentDate import y
label_desc: Use image node_id 1 for calling a global function with example usage: test_backtesting_with_ForecasterEquivalentDate() without return types