code: def test_basic_reading_and_min_process(fname):
      """Test reading SNIRF files and minimum typical processing."""
      raw = read_raw_snirf(fname, preload=True)
      # SNIRF data can contain several types, so only apply appropriate functions
      if "fnirs_cw_amplitude" in raw:
          raw = optical_density(raw)
      if "fnirs_od" in raw:
          raw = beer_lambert_law(raw, ppf=6)
      assert "hbo" in raw
      assert "hbr" in raw
  
imports: import shutil
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_almost_equal, assert_equal
  from mne._fiff.constants import FIFF
  from mne.datasets.testing import data_path, requires_testing_data
  from mne.io import read_raw_nirx, read_raw_snirf
  from mne.io.tests.test_raw import _test_raw_reader
  from mne.preprocessing.nirs import _reorder_nirx, beer_lambert_law, optical_density, short_channels, source_detector_distances
  from mne.transforms import _get_trans, apply_trans
  from mne.utils import catch_logging
label_desc: Use image node_id 2 for calling a global function with example usage: test_basic_reading_and_min_process(fname) without return types