code: def _get_conditions():
      noise_level = 20
      n_time_1 = 20
      n_time_2 = 13
      normfactor = np.hanning(20).sum()
      rng = np.random.RandomState(42)
      condition1_1d = rng.randn(n_time_1, n_space) * noise_level
      for c in condition1_1d:
          c[:] = (
              np.convolve(c, np.hanning(20), mode="same") / normfactor
          )
  
      condition2_1d = rng.randn(n_time_2, n_space) * noise_level
      for c in condition2_1d:
          c[:] = (
              np.convolve(c, np.hanning(20), mode="same") / normfactor
          )
  
      pseudoekp = 10 * np.hanning(25)[None, :]
      condition1_1d[:, 25:] += pseudoekp
      condition2_1d[:, 25:] -= pseudoekp
  
      condition1_2d = condition1_1d[:, :, np.newaxis]
      condition2_2d = condition2_1d[:, :, np.newaxis]
      return condition1_1d, condition2_1d, condition1_2d, condition2_2d
  
imports: import os
  from functools import partial
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_array_equal, assert_equal
  from scipy import linalg, sparse, stats
  from mne import MixedSourceEstimate, SourceEstimate, SourceSpaces, VolSourceEstimate
  from mne.stats import combine_adjacency, ttest_ind_no_p
  from mne.stats.cluster_level import f_oneway, permutation_cluster_1samp_test, permutation_cluster_test, spatio_temporal_cluster_1samp_test, spatio_temporal_cluster_test, summarize_clusters_stc, ttest_1samp_no_p
  from mne.utils import _record_warnings, catch_logging
label_desc: Use image node_id 1 for calling a global function with example usage: _get_conditions() and returns: condition1_1d,  condition2_1d,  condition1_2d,  condition2_2d