code: def test_apply_mne_inverse_raw():
      """Test MNE with precomputed inverse operator on Raw."""
      start = 3
      stop = 10
      raw = read_raw_fif(fname_raw)
      label_lh = read_label(str(fname_label) % "Aud-lh")
      data, times = raw[0, start:stop]
      inverse_operator = read_inverse_operator(fname_full)
      with pytest.raises(ValueError, match="has not been prepared"):
          apply_inverse_raw(
              raw, inverse_operator, lambda2, prepared=True
          )
      inverse_operator = prepare_inverse_operator(
          inverse_operator, nave=1, lambda2=lambda2, method="dSPM"
      )
      for pick_ori in [None, "normal", "vector"]:
          stc = apply_inverse_raw(
              raw,
              inverse_operator,
              lambda2,
              "dSPM",
              label=label_lh,
              start=start,
              stop=stop,
              nave=1,
              pick_ori=pick_ori,
              buffer_size=None,
              prepared=True,
          )
  
          stc2 = apply_inverse_raw(
              raw,
              inverse_operator,
              lambda2,
              "dSPM",
              label=label_lh,
              start=start,
              stop=stop,
              nave=1,
              pick_ori=pick_ori,
              buffer_size=3,
              prepared=True,
          )
  
          if pick_ori is None:
              assert np.all(stc.data > 0)
              assert np.all(stc2.data > 0)
  
          assert stc.subject == "sample"
          assert stc2.subject == "sample"
          assert_array_almost_equal(stc.times, times)
          assert_array_almost_equal(stc2.times, times)
          assert_array_almost_equal(stc.data, stc2.data)
  
      with pytest.raises(
          TypeError, match="must be an instance of BaseRaw"
      ):
          apply_inverse_raw(
              EpochsArray(raw.get_data()[np.newaxis], raw.info),
              inverse_operator,
              1.0,
          )
  
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 28 for calling a global function with example usage: test_apply_mne_inverse_raw() without return types