code: def test_rank_epochs(rank_method, proj):
      """Test that raw and epochs give the same results in a simple case."""
      # And a smoke test for epochs
      raw = read_raw_fif(raw_fname, preload=True)
      epochs = make_fixed_length_epochs(raw, preload=True, proj=False)
      rank_raw = compute_rank(raw, rank_method, proj=proj)
      rank_epochs = compute_rank(epochs, rank_method, proj=proj)
      assert rank_raw == rank_epochs
  
file_path: mne-python/mne/tests/test_rank.py
imports: import itertools
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from mne import compute_raw_covariance, make_fixed_length_epochs, pick_info, pick_types, read_cov, read_evokeds
  from mne._fiff.pick import _picks_by_type
  from mne._fiff.proj import _has_eeg_average_ref_proj
  from mne.cov import prepare_noise_cov
  from mne.datasets import testing
  from mne.io import read_raw_fif
  from mne.proj import compute_proj_raw
  from mne.rank import _compute_rank_int, _estimate_rank_raw, _get_rank_sss, compute_rank, estimate_rank
label_desc: Use image node_id 4 for calling a global function with example usage: test_rank_epochs(rank_method, proj) without return types