code: def test_inverse_ctf_comp():
      """Test interpolation with compensated CTF data."""
      raw = mne.io.read_raw_ctf(fname_raw_ctf).crop(0, 0)
      raw.apply_gradient_compensation(1)
      sphere = make_sphere_model()
      cov = make_ad_hoc_cov(raw.info)
      src = mne.setup_volume_source_space(
          pos=dict(rr=[[0.0, 0.0, 0.01]], nn=[[0.0, 1.0, 0.0]])
      )
      fwd = make_forward_solution(
          raw.info, None, src, sphere, eeg=False
      )
      raw.apply_gradient_compensation(0)
      with pytest.raises(
          RuntimeError, match="Compensation grade .* not match"
      ):
          make_inverse_operator(raw.info, fwd, cov, loose=1.0)
      raw.apply_gradient_compensation(1)
      inv = make_inverse_operator(raw.info, fwd, cov, loose=1.0)
      apply_inverse_raw(raw, inv, 1.0 / 9.0)  # smoke test
      raw.apply_gradient_compensation(0)
      with pytest.raises(
          RuntimeError, match="Compensation grade .* not match"
      ):
          apply_inverse_raw(raw, inv, 1.0 / 9.0)
  
imports: import copy
  import re
  from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_array_less, assert_equal
  from scipy import sparse
  import mne
  from mne import Covariance, EvokedArray, SourceEstimate, combine_evoked, compute_raw_covariance, convert_forward_solution, make_ad_hoc_cov, make_forward_solution, make_sphere_model, pick_channels_forward, pick_types, pick_types_forward, read_cov, read_evokeds, read_forward_solution
  from mne.datasets import testing
  from mne.epochs import Epochs, EpochsArray, make_fixed_length_epochs
  from mne.event import read_events
  from mne.forward import apply_forward, is_fixed_orient, restrict_forward_to_stc
  from mne.io import read_info, read_raw_fif
  from mne.label import label_sign_flip, read_label
  from mne.minimum_norm import INVERSE_METHODS, apply_inverse, apply_inverse_cov, apply_inverse_epochs, apply_inverse_raw, apply_inverse_tfr_epochs, compute_rank_inverse, make_inverse_operator, prepare_inverse_operator, read_inverse_operator, write_inverse_operator
  from mne.source_estimate import VolSourceEstimate, read_source_estimate
  from mne.source_space._source_space import _get_src_nn
  from mne.surface import _normal_orth
  from mne.time_frequency import EpochsTFR
  from mne.utils import _record_warnings, catch_logging
label_desc: Use image node_id 33 for calling a global function with example usage: test_inverse_ctf_comp() without return types