code: def test_ic_equivalence(ic, ic_sig):
      # consistency check
  
      assert ic(np.array(2), 10, 2).dtype == float
      assert ic_sig(np.array(2), 10, 2).dtype == float
  
      assert_almost_equal(
          ic(-10.0 / 2.0 * np.log(2.0), 10, 2) / 10,
          ic_sig(2, 10, 2),
          decimal=14,
      )
  
      assert_almost_equal(
          ic_sig(np.log(2.0), 10, 2, islog=True),
          ic_sig(2, 10, 2),
          decimal=14,
      )
  
file_path: statsmodels/statsmodels/tools/tests/test_eval_measures.py
imports: import numpy
  from numpy.testing import assert_almost_equal, assert_equal
  import pytest
  from statsmodels.tools.eval_measures import aic, aic_sigma, aicc, aicc_sigma, bias, bic, bic_sigma, hqic, hqic_sigma, iqr, maxabs, meanabs, medianabs, medianbias, mse, rmse, rmspe, vare
label_desc: Use image node_id 2 for calling a global function with example usage: test_ic_equivalence(ic, ic_sig) without return types