code: def test_cdf(self):
      #'\nsquare of standard normal random variable is chisquare with dof=1 distributed'
      cdftr = self.dist.cdf(xx, *self.trargs, **self.trkwds)
      sfctr = 1 - self.dist.sf(
          xx, *self.trargs, **self.trkwds
      )  # sf complement
      cdfst = self.statsdist.cdf(xx, *self.stargs, **self.stkwds)
      assert_almost_equal(cdfst, cdftr, 14)
      assert_almost_equal(cdfst, sfctr, 14)
  
imports: import numpy
  from numpy.testing import assert_almost_equal
  from scipy import stats
  from statsmodels.sandbox.distributions.extras import ExpTransf_gen, LogTransf_gen, squarenormalg, absnormalg, negsquarenormalg, squaretg
label_desc: Use image node_id 1 for calling the CheckDistEquivalence obj's underlying member method code with example usage: obj.test_cdf() without return types