code: def test_evals():
      lda = LDA(n_discriminants=2)
      lda.fit(X, y).transform(X)
      np.set_printoptions(suppress=True)
      print("%s" % lda.e_vals_)
      assert_almost_equal(
          lda.e_vals_, [20.90, 0.14, 0.0, 0.0], decimal=2
      )
  
file_path: mlxtend/mlxtend/feature_extraction/tests/test_linear_discriminant_analysis.py
imports: import numpy
  import pytest
  from numpy.testing import assert_almost_equal
  from mlxtend.data import iris_data
  from mlxtend.feature_extraction import LinearDiscriminantAnalysis
  from mlxtend.preprocessing import standardize
label_desc: Use image node_id 4 for calling a global function with example usage: test_evals() without return types