code: def test_loglaplace():
      # if x is laplace then y = exp(x) is loglaplace
      # parameters are tricky
      # the stats.loglaplace parameter is the inverse scale of x
      loglaplaceexpg = ExpTransf_gen(stats.laplace)
  
      cdfst = stats.loglaplace.cdf(3, 3)
      # 0.98148148148148151
      # the parameters are shape, loc and scale of underlying laplace
      cdftr = loglaplaceexpg._cdf(3, 0, 1.0 / 3)
      assert_almost_equal(cdfst, cdftr, 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 2 for calling a global function with example usage: test_loglaplace() without return types