code: def test_hyndman_blog():
      # This is the exact code Hyndman ran in his blog post on the matter:
      # https://robjhyndman.com/hyndsight/longseasonality/
      n = 2000
      m = 200
      y = np.random.RandomState(1).normal(size=n) + (
          np.arange(1, n + 1) % 100 / 30
      )
  
      trans = FourierFeaturizer(m=m, k=5).fit(y)
      _, xreg = trans.transform(y)
  
      arima = pm.auto_arima(
          y,
          X=xreg,
          seasonal=False,
          maxiter=1,  # very short
          start_p=4,
          max_p=5,
          d=0,
          max_q=1,
          start_q=0,
          simple_differencing=True,
      )  # type: pm.ARIMA
  
      # Show we can forecast 10 in the future
      _, xreg_test = trans.transform(y, n_periods=10)
      arima.predict(n_periods=10, X=xreg_test)
  
file_path: pmdarima/pmdarima/preprocessing/exog/tests/test_fourier.py
imports: import numpy
  from numpy.testing import assert_array_almost_equal
  from pmdarima.preprocessing.exog import FourierFeaturizer
  from pmdarima.compat.pytest import pytest_error_str
  import pmdarima
  import pytest
label_desc: Use image node_id 1 for calling a global function with example usage: test_hyndman_blog() without return types