code: def test_eigenvalues(self):
      F = load_df_from_R("ca$eig")[: self.ca.n_components]
      P = self.ca._eigenvalues_summary
      np.testing.assert_allclose(F["eigenvalue"], P["eigenvalue"])
      np.testing.assert_allclose(
          F["percentage of variance"], P["% of variance"]
      )
      np.testing.assert_allclose(
          F["cumulative percentage of variance"],
          P["% of variance (cumulative)"],
      )
  
imports: from __future__ import annotations
  import math
  import tempfile
  import numpy
  import pandas
  import pytest
  import rpy2.robjects
  import sklearn.utils.estimator_checks
  import sklearn.utils.validation
  from rpy2.robjects import r
  from scipy import sparse
  import prince
  from tests import load_df_from_R
label_desc: Use image node_id 6 for calling the TestCA obj's underlying member method code with example usage: obj.test_eigenvalues() without return types