code: def _test_histogram(hist_dist: Histogram):
      assert min(HIST_DATA) <= hist_dist.rvs() <= max(HIST_DATA)
      assert 1.0 > hist_dist.pdf(x=1.0) > 0.0
      assert hist_dist.pdf(x=np.max(HIST_DATA)) == 0.0
      assert hist_dist.pdf(x=np.min(HIST_DATA)) < 0.05
      assert hist_dist.cdf(x=np.max(HIST_DATA)) == 1.0
      assert 0.55 > hist_dist.cdf(x=np.median(HIST_DATA)) > 0.45
      assert hist_dist.cdf(x=np.min(HIST_DATA)) == 0.0
  
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 4 for calling a global function with example usage: _test_histogram(hist_dist) without return types