code: def test_lcmv_maxfiltered(mf_data, use_rank):
      """Test LCMV on maxfiltered data."""
      epochs, data_cov, fwd = mf_data
      rank = compute_rank(data_cov, info=epochs.info)
      assert rank == {"mag": 71}
      ctx = nullcontext()
      if use_rank == "computed":
          use_rank = rank
      elif use_rank is None:
          ctx = pytest.warns(RuntimeWarning, match="rank as it exceeds")
      with catch_logging() as log, ctx:
          make_lcmv(
              epochs.info, fwd, data_cov, rank=use_rank, verbose=True
          )
      log = log.getvalue()
      n = 102 if use_rank == "full" else 71
      assert f"Making LCMV beamformer with rank {{'mag': {n}}}" in log
  
imports: from contextlib import nullcontext
  from copy import deepcopy
  from inspect import signature
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less
  from scipy import linalg
  from scipy.spatial.distance import cdist
  import mne
  from mne import EvokedArray, VolSourceEstimate, VolVectorSourceEstimate, compute_rank, convert_forward_solution, pick_channels_cov, read_forward_solution, read_vectorview_selection
  from mne._fiff.compensator import set_current_comp
  from mne._fiff.constants import FIFF
  from mne.beamformer import Beamformer, apply_lcmv, apply_lcmv_cov, apply_lcmv_epochs, apply_lcmv_raw, make_dics, make_lcmv, read_beamformer
  from mne.beamformer._compute_beamformer import _prepare_beamformer_input
  from mne.datasets import testing
  from mne.minimum_norm import apply_inverse, make_inverse_operator
  from mne.minimum_norm.tests.test_inverse import _assert_free_ori_match
  from mne.simulation import simulate_evoked
  from mne.transforms import apply_trans, invert_transform
  from mne.utils import _record_warnings, catch_logging, object_diff
label_desc: Use image node_id 14 for calling a global function with example usage: test_lcmv_maxfiltered(mf_data, use_rank) without return types