code: def test_position_information(three_chanpos_fname):
      """Test reading file with 3 channels - one without position information."""
      nan = np.nan
      EXPECTED_LOCATIONS_FROM_FILE = (
          np.array(
              [
                  [
                      -4.0,
                      1.0,
                      7.0,
                      0.0,
                      0.0,
                      0.0,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                  ],
                  [
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                  ],
                  [
                      -5.0,
                      2.0,
                      8.0,
                      0.0,
                      0.0,
                      0.0,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                      nan,
                  ],
              ]
          )
          * 0.01
      )  # 0.01 is to scale cm to meters
  
      EXPECTED_LOCATIONS_FROM_MONTAGE = np.array(
          [
              [
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
              ],
              [
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
              ],
              [
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
                  nan,
              ],
          ]
      )
  
      raw = read_raw_eeglab(
          input_fname=three_chanpos_fname,
          preload=True,
          montage_units="cm",
      )
      assert_array_equal(
          np.array([ch["loc"] for ch in raw.info["chs"]]),
          EXPECTED_LOCATIONS_FROM_FILE,
      )
  
      # To accommodate the new behavior so that:
      # read_raw_eeglab(.. montage=montage) and raw.set_montage(montage)
      # behaves the same we need to flush the montage. otherwise we get
      # a mix of what is in montage and in the file
      raw = read_raw_eeglab(
          input_fname=three_chanpos_fname,
          preload=True,
          montage_units="cm",
      ).set_montage(
          None
      )  # Flush the montage builtin within input_fname
  
      _assert_array_allclose_nan(
          np.array([ch["loc"] for ch in raw.info["chs"]]),
          EXPECTED_LOCATIONS_FROM_MONTAGE,
      )
  
imports: import os
  import shutil
  from copy import deepcopy
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_equal
  from scipy import io
  import mne
  from mne import read_epochs_eeglab, write_events
  from mne.annotations import events_from_annotations, read_annotations
  from mne.channels import read_custom_montage
  from mne.datasets import testing
  from mne.io import read_raw_eeglab
  from mne.io.eeglab._eeglab import _readmat
  from mne.io.eeglab.eeglab import _dol_to_lod, _get_montage_information
  from mne.io.tests.test_raw import _test_raw_reader
  from mne.utils import Bunch, _check_pymatreader_installed
label_desc: Use image node_id 11 for calling a global function with example usage: test_position_information(three_chanpos_fname) without return types