code: def evoked_csd_sphere():
      """Get the MATLAB EEG data."""
      data = loadmat(eeg_fname)["data"]
      coords = loadmat(coords_fname)["coords"] * 1e-3
      csd = loadmat(csd_fname)["csd"]
      sphere = np.array((0, 0, 0, 0.08500060886258405))  # meters
      sfreq = 256  # sampling rate
      # swap coordinates' shape
      pos = np.rollaxis(coords, 1)
      # swap coordinates' positions
      pos[:, [0]], pos[:, [1]] = pos[:, [1]], pos[:, [0]]
      # invert first coordinate
      pos[:, [0]] *= -1
      dists = np.linalg.norm(pos, axis=-1)
      assert_allclose(
          dists, sphere[-1], rtol=1e-2
      )  # close to spherical, meters
      # assign channel names to coordinates
      ch_names = [str(ii) for ii in range(len(pos))]
      dig_ch_pos = dict(zip(ch_names, pos))
      montage = make_dig_montage(ch_pos=dig_ch_pos, coord_frame="head")
      # create info
      info = create_info(ch_names=ch_names, sfreq=sfreq, ch_types="eeg")
      # make Evoked object
      evoked = EvokedArray(data=data, info=info, tmin=-1)
      evoked.set_montage(montage)
      return evoked, csd, sphere
  
file_path: mne-python/mne/preprocessing/tests/test_csd.py
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from scipy import linalg
  from scipy.io import loadmat
  from mne import Epochs, EvokedArray, create_info, find_events, pick_types, read_epochs
  from mne._fiff.constants import FIFF
  from mne.channels import make_dig_montage
  from mne.datasets import testing
  from mne.io import RawArray, read_raw_fif
  from mne.preprocessing import compute_bridged_electrodes, compute_current_source_density
  from mne.utils import object_diff
label_desc: Use image node_id 1 for calling a global function with example usage: evoked_csd_sphere() and returns: evoked,  csd,  sphere