code: def test_interpolation_ctf_comp():
      """Test interpolation with compensated CTF data."""
      raw_fname = testing_path / "CTF" / "somMDYO-18av.ds"
      raw = read_raw_ctf(raw_fname, preload=True)
      raw.info["bads"] = [raw.ch_names[5], raw.ch_names[-5]]
      raw.interpolate_bads(mode="fast", origin=(0.0, 0.0, 0.04))
      assert raw.info["bads"] == []
  
imports: from itertools import compress
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_equal
  from mne import Epochs, pick_channels, pick_types, read_events
  from mne._fiff.constants import FIFF
  from mne._fiff.proj import _has_eeg_average_ref_proj
  from mne.channels import make_dig_montage
  from mne.channels.interpolation import _make_interpolation_matrix
  from mne.datasets import testing
  from mne.io import RawArray, read_raw_ctf, read_raw_fif, read_raw_nirx
  from mne.preprocessing.nirs import beer_lambert_law, optical_density, scalp_coupling_index
  from mne.utils import _record_warnings
label_desc: Use image node_id 6 for calling a global function with example usage: test_interpolation_ctf_comp() without return types