code: def test_ledoit_wolf_small():
      # Compare our blocked implementation to the naive implementation
      X_small = X[:, :4]
      lw = LedoitWolf()
      lw.fit(X_small)
      shrinkage_ = lw.shrinkage_
  
      assert_almost_equal(
          shrinkage_, _naive_ledoit_wolf_shrinkage(X_small)
      )
  
file_path: scikit-learn/sklearn/covariance/tests/test_covariance.py
imports: import numpy
  import pytest
  from sklearn import datasets
  from sklearn.covariance import OAS, EmpiricalCovariance, LedoitWolf, ShrunkCovariance, empirical_covariance, ledoit_wolf, ledoit_wolf_shrinkage, oas, shrunk_covariance
  from sklearn.covariance._shrunk_covariance import _ledoit_wolf
  from sklearn.utils._testing import assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal
  from .._shrunk_covariance import _oas
label_desc: Use image node_id 6 for calling a global function with example usage: test_ledoit_wolf_small() without return types