code: def test_warnings():
      """Test that ICA warns on certain input data conditions."""
      raw = read_raw_fif(raw_fname).crop(0, 5).load_data()
      events = read_events(event_name)
      epochs = Epochs(raw, events=events, baseline=None, preload=True)
      ica = ICA(
          n_components=2, max_iter=1, method="infomax", random_state=0
      )
  
      # not high-passed
      with epochs.info._unlock():
          epochs.info["highpass"] = 0.0
      with pytest.warns(
          RuntimeWarning, match="should be high-pass filtered"
      ):
          ica.fit(epochs)
  
      # baselined
      with epochs.info._unlock():
          epochs.info["highpass"] = 1.0
      epochs.baseline = (epochs.tmin, 0)
      with pytest.warns(
          RuntimeWarning, match="epochs.*were baseline-corrected"
      ):
          ica.fit(epochs)
  
      # cleaning baseline-corrected data
      with epochs.info._unlock():
          epochs.info["highpass"] = 1.0
      epochs.baseline = None
      ica.fit(epochs)
  
      epochs.baseline = (epochs.tmin, 0)
      with pytest.warns(
          RuntimeWarning, match="consider baseline-correcting.*" "again"
      ):
          ica.apply(epochs)
  
imports: import os
  import shutil
  from contextlib import nullcontext
  from pathlib import Path
  import matplotlib.pyplot
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_equal
  from scipy import linalg, stats
  from scipy.io import loadmat, savemat
  from mne import Annotations, Epochs, EpochsArray, EvokedArray, Info, create_info, make_ad_hoc_cov, pick_channels_regexp, pick_types, read_events
  from mne._fiff.pick import _DATA_CH_TYPES_SPLIT, get_channel_type_constants
  from mne.cov import read_cov
  from mne.datasets import testing
  from mne.event import make_fixed_length_events
  from mne.io import RawArray, read_raw_ctf, read_raw_eeglab, read_raw_fif
  from mne.io.eeglab.eeglab import _check_load_mat
  from mne.preprocessing import ICA
  from mne.preprocessing import ica_find_ecg_events, ica_find_eog_events, read_ica
  from mne.preprocessing.ica import _ica_explained_variance, _sort_components, corrmap, get_score_funcs, read_ica_eeglab
  from mne.rank import _compute_rank_int
  from mne.utils import _record_warnings, catch_logging, check_version
label_desc: Use image node_id 5 for calling a global function with example usage: test_warnings() without return types