code: def _simulate_artinis_brite23():
      """Simulate artinis Brite23 channel data from numpy data.
  
      This is to test data that is imported with missing or incorrect montage
      info. This data can then be used to test the set_montage function.
      """
      np.random.seed(0)
      data = np.random.normal(size=(46, 100))
      sd_names = [
          "S1_D1",
          "S2_D1",
          "S3_D1",
          "S4_D1",
          "S3_D2",
          "S4_D2",
          "S5_D2",
          "S4_D3",
          "S5_D3",
          "S6_D3",
          "S5_D4",
          "S6_D4",
          "S7_D4",
          "S6_D5",
          "S7_D5",
          "S8_D5",
          "S7_D6",
          "S8_D6",
          "S9_D6",
          "S8_D7",
          "S9_D7",
          "S10_D7",
          "S11_D7",
      ]
      ch_names = []
      ch_types = []
      for name in sd_names:
          ch_names.append(name + " hbo")
          ch_types.append("hbo")
          ch_names.append(name + " hbr")
          ch_types.append("hbr")
      sfreq = 10.0  # Hz
      info = create_info(
          ch_names=ch_names, ch_types=ch_types, sfreq=sfreq
      )
      raw = RawArray(data, info)
  
      return raw
  
file_path: mne-python/mne/channels/tests/test_standard_montage.py
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_raises
  from mne import create_info
  from mne._fiff._digitization import _get_dig_eeg, _get_fid_coords
  from mne._fiff.constants import FIFF
  from mne.channels import compute_native_head_t, make_standard_montage
  from mne.channels.montage import HEAD_SIZE_DEFAULT, get_builtin_montages
  from mne.io import RawArray
  from mne.preprocessing.nirs import beer_lambert_law, optical_density
  from mne.transforms import _angle_between_quats, _get_trans, rot_to_quat
label_desc: Use image node_id 6 for calling a global function with example usage: _simulate_artinis_brite23() and returns: raw