code: def test_annotate_nan(meas_date):
      """Tests automatic NaN annotation generation."""
      # Load data
      raw = mne.io.read_raw_fif(raw_fname)
      sfreq = 100
      raw.resample(sfreq)
      if meas_date is None:
          raw.set_meas_date(None)
  
      # No Nans, annotate returns empty annots
      assert not np.isnan(raw._data).any()
      annot_nan = annotate_nan(raw)
      assert len(annot_nan) == 0
  
      # but orig_time should be meas_date
      assert annot_nan.orig_time == raw.info["meas_date"]
  
      # insert block of NaN from 1s to 3s for one channel
      nan_ch_idx = 0
      raw._data[nan_ch_idx, 1 * sfreq : 3 * sfreq] = np.nan
  
      # annotate_nan accurately finds this
      annot_nan = annotate_nan(raw)
      onset = np.array([1.0])
      if raw.info["meas_date"]:
          onset += raw.first_time
      assert_array_equal(annot_nan.onset, onset)
      assert_array_equal(annot_nan.duration, np.array([2]))
      assert_array_equal(annot_nan.description, np.array(["BAD_NAN"]))
      assert len(annot_nan.ch_names) == 1
      assert annot_nan.ch_names[0] == (raw.ch_names[nan_ch_idx],)
  
      # Set the NaN annotations to the raw object
      raw.set_annotations(annot_nan)
  
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_array_equal
  import mne
  from mne.preprocessing import annotate_nan
label_desc: Use image node_id 1 for calling a global function with example usage: test_annotate_nan(meas_date) without return types