code: def test_fourier_smoke(index, forecast_index):
      f = Fourier(12, 2)
      f.in_sample(index)
      steps = 83 if forecast_index is None else len(forecast_index)
      warn = None
      if (
          is_int_index(index)
          and np.any(np.diff(index) != 1)
          or (
              type(index) is pd.Index
              and max(index) > 2**63
              and forecast_index is None
          )
      ):
          warn = UserWarning
      with pytest_warns(warn):
          f.out_of_sample(steps, index, forecast_index)
      assert isinstance(f.period, float)
      assert isinstance(f.order, int)
      str(f)
      hash(f)
      with pytest.raises(
          ValueError, match=r"2 \* order must be <= period"
      ):
          Fourier(12, 7)
  
imports: from statsmodels.compat.pandas import MONTH_END, PD_LT_1_0_0, QUARTER_END, YEAR_END, is_int_index
  from statsmodels.compat.pytest import pytest_warns
  from collections.abc import Hashable
  import numpy
  import pandas
  import pytest
  from statsmodels.tsa.deterministic import CalendarFourier, CalendarSeasonality, CalendarTimeTrend, DeterministicProcess, DeterministicTerm, Fourier, Seasonality, TimeTrend
label_desc: Use image node_id 6 for calling a global function with example usage: test_fourier_smoke(index, forecast_index) without return types