def METHOD_NAME():
    frames = 30
    data_img, cond, mask_img = _make_searchlight_test_data(frames)
    cv, n_jobs = define_cross_validation()
    sl = searchlight.SearchLight(
        mask_img,
        process_mask_img=mask_img,
        radius=1,
        n_jobs=n_jobs,
        scoring="accuracy",
        cv=cv,
    )
    sl.fit(data_img, cond)
    assert np.where(sl.scores_ == 1)[0].size == 7
    assert sl.scores_[2, 2, 2] == 1.0
    assert sl.scores_[1, 2, 2] == 1.0
    assert sl.scores_[2, 1, 2] == 1.0
    assert sl.scores_[2, 2, 1] == 1.0
    assert sl.scores_[3, 2, 2] == 1.0
    assert sl.scores_[2, 3, 2] == 1.0
    assert sl.scores_[2, 2, 3] == 1.0