code: def test_get_clusters_table_not_modifying_stat_image(affine_eye):
      shape = (9, 10, 11)
      data = np.zeros(shape)
      data[2:4, 5:7, 6:8] = 5.0
      data[0:3, 0:3, 0:3] = 6.0
  
      stat_img = nib.Nifti1Image(data, affine_eye)
      data_orig = get_data(stat_img).copy()
  
      # test one cluster should be removed
      clusters_table = get_clusters_table(
          stat_img,
          4,
          cluster_threshold=10,
          two_sided=True,
      )
      assert np.allclose(data_orig, get_data(stat_img))
      assert len(clusters_table) == 1
  
      # test no clusters should be removed
      stat_img = nib.Nifti1Image(data, affine_eye)
      clusters_table = get_clusters_table(
          stat_img,
          4,
          cluster_threshold=7,
          two_sided=False,
      )
      assert np.allclose(data_orig, get_data(stat_img))
      assert len(clusters_table) == 2
  
      # test cluster threshold is None
      stat_img = nib.Nifti1Image(data, affine_eye)
      clusters_table = get_clusters_table(
          stat_img,
          4,
          cluster_threshold=None,
          two_sided=False,
      )
      assert np.allclose(data_orig, get_data(stat_img))
      assert len(clusters_table) == 2
  
file_path: nilearn/nilearn/reporting/tests/test_reporting.py
imports: import nibabel
  import numpy
  import pytest
  from nilearn.image import get_data
  from nilearn.plotting import _set_mpl_backend
  from nilearn.reporting import get_clusters_table
  from nilearn.reporting.get_clusters_table import _cluster_nearest_neighbor, _local_max
label_desc: Use image node_id 5 for calling a global function with example usage: test_get_clusters_table_not_modifying_stat_image(affine_eye) without return types