code: def test_dig_mri_distances(
      dig_kinds, exclude, count, bounds, outliers
  ):
      """Test the trans obtained by coregistration."""
      info = read_info(fname_raw)
      dists = dig_mri_distances(
          info,
          fname_trans,
          "sample",
          subjects_dir,
          dig_kinds=dig_kinds,
          exclude_frontal=exclude,
      )
      assert dists.shape == (count,)
      assert bounds[0] < np.mean(dists) < bounds[1]
      assert np.sum(dists > 0.03) == outliers
  
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal, assert_equal
  from mne import decimate_surface, dig_mri_distances, get_montage_volume_labels, pick_types, read_surface, write_surface
  from mne._fiff.constants import FIFF
  from mne.channels import make_dig_montage
  from mne.datasets import testing
  from mne.io import read_info
  from mne.surface import _compute_nearest, _get_ico_surface, _marching_cubes, _normal_orth, _project_onto_surface, _read_patch, _tessellate_sphere, _voxel_neighbors, fast_cross_3d, get_head_surf, get_meg_helmet_surf, read_curvature
  from mne.transforms import _get_trans
  from mne.utils import _record_warnings, catch_logging, object_diff, requires_freesurfer
label_desc: Use image node_id 9 for calling a global function with example usage: test_dig_mri_distances(dig_kinds, exclude, count, bounds, outliers) without return types