code: def _get_data():
      """Read in data used in tests."""
      # read forward model
      forward = mne.read_forward_solution(fname_fwd)
      # read data
      raw = mne.io.read_raw_fif(fname_raw, preload=True)
      events = mne.read_events(fname_event)
      event_id, tmin, tmax = 1, -0.1, 0.15
  
      # decimate for speed
      left_temporal_channels = read_vectorview_selection(
          "Left-temporal"
      )
      picks = mne.pick_types(
          raw.info, meg=True, selection=left_temporal_channels
      )
      picks = picks[::2]
      raw.pick([raw.ch_names[ii] for ii in picks])
      del picks
  
      raw.info.normalize_proj()  # avoid projection warnings
  
      epochs = mne.Epochs(
          raw,
          events,
          event_id,
          tmin,
          tmax,
          proj=True,
          baseline=(None, 0.0),
          preload=True,
          reject=reject,
      )
  
      noise_cov = mne.compute_covariance(epochs, tmin=None, tmax=0.0)
  
      data_cov = mne.compute_covariance(epochs, tmin=0.01, tmax=0.15)
  
      return epochs, data_cov, noise_cov, forward
  
imports: import os
  import sys
  from pathlib import Path
  import numpy
  import pytest
  import mne
  from mne import pick_channels_cov, read_vectorview_selection
  from mne._fiff.pick import _picks_to_idx
  from mne.datasets import testing
  from mne.utils import Bunch, _check_ch_locs, _check_fname, _check_info_inv, _check_option, _check_range, _check_sphere, _check_subject, _on_missing, _path_like, _safe_input, _suggest, _validate_type, catch_logging, check_fname, check_random_state, check_version
label_desc: Use image node_id 3 for calling a global function with example usage: _get_data() and returns: epochs,  data_cov,  noise_cov,  forward