code: def test_export_edf_signal_clipping(
      tmp_path, physical_range, exceeded_bound
  ):
      """Test if exporting data exceeding physical min/max clips and emits a warning."""
      raw = read_raw_fif(fname_raw)
      raw.pick(picks=["eeg", "ecog", "seeg"]).load_data()
      temp_fname = tmp_path / "test.edf"
      with pytest.warns(RuntimeWarning, match=f"The {exceeded_bound}"):
          raw.export(temp_fname, physical_range=physical_range)
      raw_read = read_raw_edf(temp_fname, preload=True)
      assert raw_read.get_data().min() >= physical_range[0]
      assert raw_read.get_data().max() <= physical_range[1]
  
imports: from contextlib import nullcontext
  from datetime import datetime, timezone
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from mne import Annotations, Epochs, create_info, read_epochs_eeglab, read_evokeds, read_evokeds_mff
  from mne.datasets import misc, testing
  from mne.export import export_evokeds, export_evokeds_mff
  from mne.fixes import _compare_version
  from mne.io import RawArray, read_raw_brainvision, read_raw_edf, read_raw_eeglab, read_raw_fif
  from mne.tests.test_epochs import _get_data
  from mne.utils import _check_edfio_installed, _record_warnings, _resource_path, object_diff
label_desc: Use image node_id 10 for calling a global function with example usage: test_export_edf_signal_clipping(tmp_path, physical_range, exceeded_bound) without return types