code: def test_plot_stat_map_colorbar_variations(
      params, img_3d_mni, affine_mni, rng
  ):
      """Smoke test for plot_stat_map with different colorbar configurations."""
      data_positive = get_data(img_3d_mni)
      data_negative = -data_positive
      data_heterogeneous = data_positive * rng.standard_normal(
          size=data_positive.shape
      )
      img_negative = Nifti1Image(data_negative, affine_mni)
      img_heterogeneous = Nifti1Image(data_heterogeneous, affine_mni)
      for img in [img_3d_mni, img_negative, img_heterogeneous]:
          plot_stat_map(img, cut_coords=(80, -120, -60), **params)
          plt.close()
  
imports: import matplotlib.pyplot
  import numpy
  import pytest
  from nibabel import Nifti1Image
  from nilearn.conftest import _rng
  from nilearn.datasets import load_mni152_template
  from nilearn.image import get_data
  from nilearn.image.resampling import coord_transform
  from nilearn.plotting import plot_stat_map
  from nilearn.plotting.find_cuts import find_cut_slices
label_desc: Use image node_id 7 for calling a global function with example usage: test_plot_stat_map_colorbar_variations(params, img_3d_mni, affine_mni, rng) without return types