code: def test_ar_raw():
      """Test fitting AR model on raw data."""
      raw = io.read_raw_fif(raw_fname).crop(0, 2).load_data()
      raw.pick(picks="grad")
      # pick MEG gradiometers
      for order in (2, 5, 10):
          coeffs = fit_iir_model_raw(raw, order)[1][1:]
          assert coeffs.shape == (order,)
          assert_allclose(-coeffs[0], 1.0, atol=0.5)
      # let's make sure we're doing something reasonable: first, white noise
      rng = np.random.RandomState(0)
      raw._data = rng.randn(*raw._data.shape)
      raw._data *= 1e-15
      for order in (2, 5, 10):
          coeffs = fit_iir_model_raw(raw, order)[1]
          assert_allclose(coeffs, [1.0] + [0.0] * order, atol=2e-2)
      # Now let's try pink noise
      iir = [1, -1, 0.2]
      raw._data = lfilter([1.0], iir, raw._data)
      for order in (2, 5, 10):
          coeffs = fit_iir_model_raw(raw, order)[1]
          assert_allclose(coeffs, iir + [0.0] * (order - 2), atol=5e-2)
  
file_path: mne-python/mne/time_frequency/tests/test_ar.py
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal
  from scipy.signal import lfilter
  from mne import io
  from mne.time_frequency.ar import _yule_walker, fit_iir_model_raw
label_desc: Use image node_id 2 for calling a global function with example usage: test_ar_raw() without return types