code: def test_sss_proj():
      """Test `meg` proj option."""
      raw = read_raw_fif(raw_fname)
      raw.crop(0, 1.0).load_data().pick(picks="meg")
      raw.pick(raw.ch_names[:51]).del_proj()
      raw_sss = maxwell_filter(raw, int_order=5, ext_order=2)
      sss_rank = 21  # really low due to channel picking
      assert len(raw_sss.info["projs"]) == 0
      for meg, n_proj, want_rank in (
          ("separate", 6, sss_rank),
          ("combined", 3, sss_rank - 3),
      ):
          proj = compute_proj_raw(
              raw_sss, n_grad=3, n_mag=3, meg=meg, verbose="error"
          )
          this_raw = raw_sss.copy().add_proj(proj).apply_proj()
          assert len(this_raw.info["projs"]) == n_proj
          sss_proj_rank = _compute_rank_int(this_raw)
          cov = compute_raw_covariance(this_raw, verbose="error")
          W, ch_names, rank = compute_whitener(
              cov, this_raw.info, return_rank=True
          )
          assert ch_names == this_raw.ch_names
          assert want_rank == sss_proj_rank == rank  # proper reduction
          if meg == "combined":
              assert (
                  this_raw.info["projs"][0]["data"]["col_names"]
                  == ch_names
              )
          else:
              mag_names = ch_names[2::3]
              assert (
                  this_raw.info["projs"][3]["data"]["col_names"]
                  == mag_names
              )
  
imports: import copy
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_equal
  from scipy import linalg
  from mne import Epochs, compute_proj_epochs, compute_proj_evoked, compute_proj_raw, compute_raw_covariance, convert_forward_solution, create_info, pick_types, read_events, read_forward_solution, read_source_estimate, sensitivity_map
  from mne._fiff.proj import _EEG_AVREF_PICK_DICT, _needs_eeg_average_ref_proj, activate_proj, make_projector, setup_proj
  from mne.cov import compute_whitener, regularize
  from mne.datasets import testing
  from mne.io import RawArray, read_raw_fif
  from mne.preprocessing import maxwell_filter
  from mne.proj import _has_eeg_average_ref_proj, make_eeg_average_ref_proj, read_proj, write_proj
  from mne.rank import _compute_rank_int
  from mne.utils import _record_warnings
label_desc: Use image node_id 10 for calling a global function with example usage: test_sss_proj() without return types