code: def test_qda_prior_copy():
      """Check that altering `priors` without `fit` doesn't change `priors_`"""
      priors = np.array([0.5, 0.5])
      qda = QuadraticDiscriminantAnalysis(priors=priors).fit(X, y)
  
      # we expect the following
      assert_array_equal(qda.priors_, qda.priors)
  
      # altering `priors` without `fit` should not change `priors_`
      priors[0] = 0.2
      assert qda.priors_[0] != qda.priors[0]
  
imports: import numpy
  import pytest
  from scipy import linalg
  from sklearn.cluster import KMeans
  from sklearn.covariance import LedoitWolf, ShrunkCovariance, ledoit_wolf
  from sklearn.datasets import make_blobs
  from sklearn.discriminant_analysis import LinearDiscriminantAnalysis, QuadraticDiscriminantAnalysis, _cov
  from sklearn.preprocessing import StandardScaler
  from sklearn.utils import _IS_WASM, check_random_state
  from sklearn.utils._testing import _convert_container, assert_allclose, assert_almost_equal, assert_array_almost_equal, assert_array_equal
label_desc: Use image node_id 18 for calling a global function with example usage: test_qda_prior_copy() without return types