code: def test_grand_average_len_1():
      """Test if mne.grand_average handles a sequence of length 1 correctly."""
      # returns a list of length 1
      evokeds = read_evokeds(ave_fname, condition=[0], proj=True)
  
      with pytest.warns(RuntimeWarning, match="Only a single dataset"):
          gave = grand_average(evokeds)
  
      assert_allclose(gave.data, evokeds[0].data)
  
imports: from copy import deepcopy
  from datetime import datetime, timezone
  from io import StringIO
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from scipy import sparse
  from mne import pick_types, read_cov, read_evokeds
  from mne._fiff.pick import _picks_by_type
  from mne.epochs import make_fixed_length_epochs
  from mne.io import read_raw_fif
  from mne.time_frequency import tfr_morlet
  from mne.utils import _PCA, _apply_scaling_array, _apply_scaling_cov, _array_equal_nan, _cal_to_julian, _custom_lru_cache, _dt_to_julian, _freq_mask, _get_inst_data, _julian_to_cal, _julian_to_dt, _reg_pinv, _ReuseCycle, _time_mask, _undo_scaling_array, _undo_scaling_cov, compute_corr, create_slices, grand_average, hashfunc, numerics, object_diff, object_hash, object_size, random_permutation, sum_squared
  from mne.utils.numerics import _LRU_CACHE_MAXSIZES, _LRU_CACHES
label_desc: Use image node_id 18 for calling a global function with example usage: test_grand_average_len_1() without return types