code: def test_permutation_large_n_samples(numba_conditional):
      """Test that non-replacement works with large N."""
      X = np.random.RandomState(0).randn(72, 1) + 1
      for n_samples in (11, 72):
          tails = (0, 1) if n_samples <= 20 else (0,)
          for tail in tails:
              H0 = permutation_cluster_1samp_test(
                  X[:n_samples],
                  threshold=1e-4,
                  tail=tail,
                  out_type="mask",
              )[-1]
              assert H0.shape == (1024,)
              assert len(np.unique(H0)) >= 1024 - (H0 == 0).sum()
  
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 4 for calling a global function with example usage: test_permutation_large_n_samples(numba_conditional) without return types