code: def _load_data():
      """Load data."""
      # It is more memory efficient to load data in a separate
      # function so it's loaded on-demand
      raw = io.read_raw_fif(raw_fname).pick(["eeg", "stim"])
      events = read_events(event_name)
      # subselect channels for speed
      picks = pick_types(raw.info, meg=False, eeg=True, exclude=[])[:15]
      epochs = Epochs(
          raw,
          events,
          event_id,
          tmin,
          tmax,
          picks=picks,
          preload=True,
          reject=dict(eeg=80e-6),
      )
      evoked = epochs.average()
      return raw.load_data(), epochs.load_data(), evoked
  
file_path: mne-python/mne/preprocessing/tests/test_interpolate.py
imports: import itertools
  from pathlib import Path
  import numpy
  import pytest
  from mne import Epochs, create_info, io, pick_types, read_events
  from mne.channels import make_standard_montage
  from mne.preprocessing import equalize_bads, interpolate_bridged_electrodes
  from mne.preprocessing.interpolate import _find_centroid_sphere
  from mne.transforms import _cart_to_sph
label_desc: Use image node_id 1 for calling a global function with example usage: _load_data() and returns: raw,  epochs,  evoked