code: def test_plot_cov():
      """Test plotting of covariances."""
      raw = _get_raw()
      cov = read_cov(cov_fname)
      with pytest.warns(RuntimeWarning, match="projection"):
          fig1, fig2 = cov.plot(
              raw.info, proj=True, exclude=raw.ch_names[6:]
          )
  
      # test complex numbers
      cov["data"] = cov.data * (1 + 1j)
      fig1, fig2 = cov.plot(raw.info)
  
imports: from pathlib import Path
  import matplotlib.pyplot
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  from mne import SourceEstimate, pick_events, read_cov, read_dipole, read_events, read_evokeds, read_source_spaces
  from mne.chpi import compute_chpi_snr
  from mne.datasets import testing
  from mne.filter import create_filter
  from mne.io import read_raw_fif
  from mne.minimum_norm import read_inverse_operator
  from mne.time_frequency import CrossSpectralDensity
  from mne.viz import plot_bem, plot_chpi_snr, plot_csd, plot_events, plot_filter, plot_snr_estimate, plot_source_spectrogram
  from mne.viz.misc import _handle_event_colors
  from mne.viz.utils import _get_color_list
label_desc: Use image node_id 4 for calling a global function with example usage: test_plot_cov() without return types