code: def test_nonuniform_scale_samples_logunif():
      """
      Test the rescaling of samples for logarithmic uniform  distribution
      """
      problem = {
          "num_vars": 1,
          "dists": ["logunif"],
          "bounds": [[1e-22, 1e-18]],
          "names": ["x1"],
      }
      actual = latin.sample(problem, 10000)
      rng = np.random.default_rng()
      x = stats.loguniform.rvs(
          size=100000, a=1e-22, b=1e-18, random_state=rng
      )
      res = stats.cramervonmises_2samp(actual[:, 0], x)
      zero_hypothesis_rejected = True
      if res.pvalue > 0.05:
          zero_hypothesis_rejected = False
      assert zero_hypothesis_rejected is False
  
imports: from pytest import raises
  from numpy.testing import assert_equal, assert_allclose
  import numpy
  from scipy import stats
  import pytest
  from SALib.util import read_param_file, _scale_samples, _unscale_samples, compute_groups_matrix
  from SALib.sample import latin
label_desc: Use image node_id 16 for calling a global function with example usage: test_nonuniform_scale_samples_logunif() without return types