code: def test_xdawn_picks():
      """Test picking with Xdawn."""
      data = np.random.RandomState(0).randn(10, 2, 10)
      info = create_info(2, 1000.0, ("eeg", "misc"))
      epochs = EpochsArray(data, info)
      xd = Xdawn(correct_overlap=False)
      xd.fit(epochs)
      epochs_out = xd.apply(epochs)["1"]
      assert epochs_out.info["ch_names"] == epochs.ch_names
      assert not (epochs_out.get_data([0])[:, 0] != data[:, 0]).any()
      assert_array_equal(epochs_out.get_data([1])[:, 0], data[:, 1])
  
file_path: mne-python/mne/preprocessing/tests/test_xdawn.py
imports: from pathlib import Path
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal
  from scipy import stats
  from mne import Epochs, EpochsArray, compute_raw_covariance, create_info, pick_types, read_events
  from mne.decoding import Vectorizer
  from mne.fixes import _safe_svd
  from mne.io import read_raw_fif
  from mne.preprocessing.xdawn import Xdawn, _XdawnTransformer
label_desc: Use image node_id 3 for calling a global function with example usage: test_xdawn_picks() without return types