code: def test_bdf_multiple_annotation_channels():
      """Test BDF with multiple annotation channels."""
      raw = read_raw_bdf(bdf_multiple_annotations_path)
      assert len(raw.annotations) == 10
      descriptions = np.array(
          [
              "signal_start",
              "EEG-check#1",
              "TestStim#1",
              "TestStim#2",
              "TestStim#3",
              "TestStim#4",
              "TestStim#5",
              "TestStim#6",
              "TestStim#7",
              "Ligths-Off#1",
          ],
          dtype="<U12",
      )
      assert_array_equal(descriptions, raw.annotations.description)
  
imports: import datetime
  from contextlib import nullcontext
  from functools import partial
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_equal
  from scipy.io import loadmat
  from mne import Annotations, pick_types
  from mne._fiff.pick import channel_indices_by_type, get_channel_type_constants
  from mne.annotations import _ndarray_ch_names, events_from_annotations, read_annotations
  from mne.datasets import testing
  from mne.io import edf, read_raw_bdf, read_raw_edf, read_raw_fif, read_raw_gdf
  from mne.io.edf.edf import _edf_str, _parse_prefilter_string, _read_annotations_edf, _read_ch, _read_edf_header, _read_header
  from mne.io.tests.test_raw import _test_raw_reader
  from mne.tests.test_annotations import _assert_annotations_equal
label_desc: Use image node_id 24 for calling a global function with example usage: test_bdf_multiple_annotation_channels() without return types