code: def _test_lognormal(hd: StdMeanLogNormal):
      samples = hd.rvs_many(size=100)
      samples_median = np.median(samples)
      assert -5 < samples_median < 5
      samples_std = np.std(samples)
      assert 0 < samples_std < 4
      assert np.isclose(hd.pdf(0.0), 0.0)
      assert np.isclose(hd.pdf(1.0), 0.28777602476804065)
      assert np.isclose(hd.pdf(5.0), 0.029336304593386688)
      assert np.isclose(hd.cdf(0.0), 0.0)
      assert np.isclose(hd.cdf(1.0), 0.49999999998280026)
      assert np.isclose(
          abs(hd.cdf(5.0) - 0.8771717397015799), 0.12282826029842009
      )
  
imports: import math
  import os
  from collections import Counter
  import joblib
  import numpy
  import pytest
  from neuraxle.base import Identity
  from neuraxle.hyperparams.distributions import Choice, LogNormal, LogUniform, Normal, PriorityChoice, RandInt, Uniform, get_index_in_list_with_bool
  from neuraxle.hyperparams.scipy_distributions import Gaussian, Histogram, Poisson, ScipyContinuousDistributionWrapper, ScipyDiscreteDistributionWrapper, ScipyLogUniform, StdMeanLogNormal
  from neuraxle.hyperparams.space import HyperparameterSpace
  from scipy.stats import gamma, norm, randint, uniform
label_desc: Use image node_id 18 for calling a global function with example usage: _test_lognormal(hd) without return types