code: def test_resolution_matrix_lcmv():
      """Test computation of resolution matrix for LCMV beamformers."""
      # read forward solution
      forward = mne.read_forward_solution(fname_fwd)
  
      # remove bad channels
      forward = mne.pick_channels_forward(forward, exclude="bads")
  
      # forward operator with fixed source orientations
      forward_fxd = mne.convert_forward_solution(
          forward, surf_ori=True, force_fixed=True
      )
  
      # evoked info
      info = mne.io.read_info(fname_evoked)
      mne.pick_info(
          info, mne.pick_types(info, meg=True), copy=False
      )  # good MEG
  
      # noise covariance matrix
      # ad-hoc to avoid discrepancies due to regularisation of real noise
      # covariance matrix
      noise_cov = mne.make_ad_hoc_cov(info)
  
      # Resolution matrix for Beamformer
      data_cov = noise_cov.copy()  # to test a property of LCMV
  
      # compute beamformer filters
      # reg=0. to make sure noise_cov and data_cov are as similar as possible
      filters = make_lcmv(
          info,
          forward_fxd,
          data_cov,
          reg=0.0,
          noise_cov=noise_cov,
          pick_ori=None,
          rank=None,
          weight_norm=None,
          reduce_rank=False,
          verbose=False,
      )
  
      # Compute resolution matrix for beamformer
      resmat_lcmv = make_lcmv_resolution_matrix(
          filters, forward_fxd, info
      )
  
      # for noise_cov==data_cov and whitening, the filter weights should be the
      # transpose of leadfield
  
      # create filters with transposed whitened leadfield as weights
      forward_fxd = mne.pick_channels_forward(
          forward_fxd, info["ch_names"]
      )
      filters_lfd = deepcopy(filters)
      filters_lfd["weights"][:] = forward_fxd["sol"]["data"].T
  
      # compute resolution matrix for filters with transposed leadfield
      resmat_fwd = make_lcmv_resolution_matrix(
          filters_lfd, forward_fxd, info
      )
  
      # pairwise correlation for rows (CTFs) of resolution matrices for whitened
      # LCMV beamformer and transposed leadfield should be 1
      # Some rows are off by about 0.1 - not yet clear why
      corr = []
  
      for f, lf in zip(resmat_fwd, resmat_lcmv):
          corr.append(np.corrcoef(f, lf)[0, 1])
  
      # all row correlations should at least be above ~0.8
      assert_allclose(corr, 1.0, atol=0.2)
  
      # Maximum row correlation should at least be close to 1
      assert_allclose(np.max(corr), 1.0, atol=0.01)
  
imports: from copy import deepcopy
  import numpy
  from numpy.testing import assert_allclose
  import mne
  from mne.beamformer import make_lcmv, make_lcmv_resolution_matrix
  from mne.datasets import testing
label_desc: Use image node_id 1 for calling a global function with example usage: test_resolution_matrix_lcmv() without return types