code: def test_score_samples():
      X_train = [[1, 1], [1, 2], [2, 1]]
      clf1 = EllipticEnvelope(contamination=0.2).fit(X_train)
      clf2 = EllipticEnvelope().fit(X_train)
      assert_array_equal(
          clf1.score_samples([[2.0, 2.0]]),
          clf1.decision_function([[2.0, 2.0]]) + clf1.offset_,
      )
      assert_array_equal(
          clf2.score_samples([[2.0, 2.0]]),
          clf2.decision_function([[2.0, 2.0]]) + clf2.offset_,
      )
      assert_array_equal(
          clf1.score_samples([[2.0, 2.0]]),
          clf2.score_samples([[2.0, 2.0]]),
      )
  
imports: import numpy
  import pytest
  from sklearn.covariance import EllipticEnvelope
  from sklearn.exceptions import NotFittedError
  from sklearn.utils._testing import assert_almost_equal, assert_array_almost_equal, assert_array_equal
label_desc: Use image node_id 2 for calling a global function with example usage: test_score_samples() without return types