code: def test_strategy_mean_seasonal_simple(n_seasons, sp):
      """Create 2d matrix (seasons on rows, time points of each season on columns)."""
      values = np.random.normal(size=(n_seasons, sp))
      y = pd.Series(values.ravel())
  
      expected = values.mean(axis=0)
      assert expected.shape == (sp,)
  
      f = NaiveForecaster(strategy="mean", sp=sp)
      f.fit(y)
      fh = np.arange(1, sp + 1)
      y_pred = f.predict(fh)
  
      np.testing.assert_array_equal(y_pred, expected)
  
imports: import numpy
  import pandas
  import pytest
  from sktime.datatypes._utilities import get_cutoff
  from sktime.forecasting.base import ForecastingHorizon
  from sktime.forecasting.naive import NaiveForecaster
  from sktime.forecasting.tests._config import TEST_OOS_FHS, TEST_SPS, TEST_WINDOW_LENGTHS_INT
  from sktime.utils._testing.forecasting import _assert_correct_pred_time_index
  from sktime.utils.validation.forecasting import check_fh
label_desc: Use image node_id 5 for calling a global function with example usage: test_strategy_mean_seasonal_simple(n_seasons, sp) without return types