code: def test_seasonality_type_auto_with_season_strictly_pos(
      index: str, seasonality_type: str
  ):
      """Tests the detection of the seasonality type using the internal auto algorithm
      when data that has seasonality and is strictly positive.
  
      Tests various index types and tests for both additive and multiplicative
      seasonality.
  
      Parameters
      ----------
      index : str
          Type of index. Options are: "RangeIndex" and "DatetimeIndex"
      seasonality_type : str
          The seasonality type to pass to setup
      """
      # Create base data
      N = 100
      y_trend = np.arange(100, 100 + N)
      y_season = 100 * (
          1 + np.sin(y_trend)
      )  # No negative values when creating final y
      y = pd.Series(y_trend + y_season)
  
      # RangeIndex is default index
      if index == "DatetimeIndex":
          dates = pd.date_range(
              start="2020-01-01", periods=N, freq="MS"
          )
          y.index = dates
  
      # -------------------------------------------------------------------------#
      # Test 1: Additive Seasonality
      # -------------------------------------------------------------------------#
      err_msg = "Expected additive seasonality, got multiplicative"
      exp = TSForecastingExperiment()
      exp.setup(
          data=y, seasonality_type=seasonality_type, session_id=42
      )
      assert exp.seasonality_type == "add", err_msg
  
      # # -------------------------------------------------------------------------#
      # # Test 2A: Multiplicative Seasonality (1)
      # # -------------------------------------------------------------------------#
      # y = pd.Series(y_trend * y_season)
      # y.index = dates
  
      # err_msg = "Expected multiplicative seasonality, got additive (1)"
      # exp = TSForecastingExperiment()
      # exp.setup(data=y, session_id=42)
      # assert exp.seasonality_type == "mul", err_msg
  
      # -------------------------------------------------------------------------#
      # Test 2B: Multiplicative Seasonality (2)
      # -------------------------------------------------------------------------#
      y = get_data("airline", verbose=False)
  
      err_msg = "Expected multiplicative seasonality, got additive (2)"
      exp = TSForecastingExperiment()
      exp.setup(
          data=y, seasonality_type=seasonality_type, session_id=42
      )
      assert exp.seasonality_type == "mul", err_msg
  
imports: import math
  import numpy
  import pandas
  import pytest
  from time_series_test_utils import _get_seasonal_values, _get_seasonal_values_alphanumeric, _return_data_seasonal_types_strictly_pos, _return_setup_args_raises, _return_splitter_args
  from pycaret.datasets import get_data
  from pycaret.time_series import TSForecastingExperiment
label_desc: Use image node_id 20 for calling a global function with example usage: test_seasonality_type_auto_with_season_strictly_pos(index, seasonality_type) without return types