code: def test_searchlight_small_radius():
      frames = 30
      data_img, cond, mask_img = _make_searchlight_test_data(frames)
      cv, n_jobs = define_cross_validation()
  
      # Small radius : only one pixel is selected
      sl = searchlight.SearchLight(
          mask_img,
          process_mask_img=mask_img,
          radius=0.5,
          n_jobs=n_jobs,
          scoring="accuracy",
          cv=cv,
          verbose=1,
      )
      sl.fit(data_img, cond)
  
      assert np.where(sl.scores_ == 1)[0].size == 1
      assert sl.scores_[2, 2, 2] == 1.0
  
file_path: nilearn/nilearn/decoding/tests/test_searchlight.py
imports: import numpy
  from nibabel import Nifti1Image
  from sklearn.model_selection import KFold
  from nilearn.conftest import _rng
  from nilearn.decoding import searchlight
label_desc: Use image node_id 3 for calling a global function with example usage: test_searchlight_small_radius() without return types