code: def test_lda_transform():
      # Test LDA transform.
      clf = LinearDiscriminantAnalysis(solver="svd", n_components=1)
      X_transformed = clf.fit(X, y).transform(X)
      assert X_transformed.shape[1] == 1
      clf = LinearDiscriminantAnalysis(solver="eigen", n_components=1)
      X_transformed = clf.fit(X, y).transform(X)
      assert X_transformed.shape[1] == 1
  
      clf = LinearDiscriminantAnalysis(solver="lsqr", n_components=1)
      clf.fit(X, y)
      msg = "transform not implemented for 'lsqr'"
  
      with pytest.raises(NotImplementedError, match=msg):
          clf.transform(X)
  
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 5 for calling a global function with example usage: test_lda_transform() without return types