code: def test_pca_on_uncentered_data():
      pca1 = PCA(solver="svd")
      pca1.fit(X)
  
      pca2 = PCA(solver="eigen")
      pca2.fit(X)
      assert_almost_equal(
          pca1.e_vals_normalized_, pca2.e_vals_normalized_
      )
  
file_path: mlxtend/mlxtend/feature_extraction/tests/test_principal_component_analysis.py
imports: import numpy
  from numpy.testing import assert_allclose, assert_almost_equal
  from mlxtend.data import iris_data
  from mlxtend.feature_extraction import PrincipalComponentAnalysis
  from mlxtend.preprocessing import standardize
  from mlxtend.utils import assert_raises
label_desc: Use image node_id 11 for calling a global function with example usage: test_pca_on_uncentered_data() without return types