code: def test_evals():
      pca = PCA(n_components=2, solver="eigen")
      pca.fit(X_std)
  
      expected = [2.93035378, 0.92740362, 0.14834223, 0.02074601]
      assert_almost_equal(pca.e_vals_, expected, decimal=5)
  
      pca = PCA(n_components=2, solver="svd")
      pca.fit(X_std)
      assert_almost_equal(pca.e_vals_, expected, decimal=5)
  
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 6 for calling a global function with example usage: test_evals() without return types