code: def test_arithmetic_cov():
      """Test arithmetic with noise covariance matrices."""
      cov = read_cov(cov_fname)
      cov_sum = cov + cov
      assert_array_almost_equal(2 * cov.nfree, cov_sum.nfree)
      assert_array_almost_equal(2 * cov.data, cov_sum.data)
      assert cov.ch_names == cov_sum.ch_names
  
      cov += cov
      assert_array_almost_equal(cov_sum.nfree, cov.nfree)
      assert_array_almost_equal(cov_sum.data, cov.data)
      assert cov_sum.ch_names == cov.ch_names
  
imports: import itertools
  import sys
  from inspect import signature
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_equal
  from mne import Epochs, compute_covariance, compute_proj_raw, compute_rank, compute_raw_covariance, create_info, find_events, make_ad_hoc_cov, make_fixed_length_events, merge_events, pick_channels_cov, pick_info, pick_types, read_cov, read_evokeds, write_cov
  from mne._fiff.pick import _DATA_CH_TYPES_SPLIT
  from mne.channels import equalize_channels
  from mne.cov import _auto_low_rank_model, _regularized_covariance, compute_whitener, prepare_noise_cov, regularize, whiten_evoked
  from mne.datasets import testing
  from mne.fixes import _safe_svd
  from mne.io import RawArray, read_info, read_raw_ctf, read_raw_fif
  from mne.preprocessing import maxwell_filter
  from mne.rank import _compute_rank_int
  from mne.utils import _record_warnings, assert_snr, catch_logging
label_desc: Use image node_id 11 for calling a global function with example usage: test_arithmetic_cov() without return types