new_contents: from __future__ import print_function, division
  import imgaug as ia
  from imgaug import parameters as iap
  from imgaug.parameters import (
      Binomial, Choice, DiscreteUniform, Poisson, Normal, Laplace, ChiSquare,
      Weibull, Uniform, Beta, Deterministic, Clip, Discretize, Multiply, Add,
      Absolute, RandomSign, ForceSign, Positive, Negative,
      SimplexNoise, FrequencyNoise, Sigmoid
  )
  from scipy import misc
  import numpy as np
  
  def main():
      params = [
          ("Binomial(0.1)", Binomial(0.1)),
          ("Choice", Choice([0, 1, 2])),
          ("Choice with p", Choice([0, 1, 2], p=[0.1, 0.2, 0.7])),
          ("DiscreteUniform(0, 10)", DiscreteUniform(0, 10)),
          ("Poisson(0)", Poisson(0)),
          ("Poisson(5)", Poisson(5)),
          ("Discretize(Poisson(5))", Discretize(Poisson(5))),
          ("Normal(0, 1)", Normal(0, 1)),
          ("Normal(1, 1)", Normal(1, 1)),
          ("Normal(1, 2)", Normal(0, 2)),
          ("Normal(Choice([-1, 1]), 2)", Normal(Choice([-1, 1]), 2)),
          ("Discretize(Normal(0, 1.0))", Discretize(Normal(0, 1.0))),
          ("Positive(Normal(0, 1.0))", Positive(Normal(0, 1.0))),
          ("Positive(Normal(0, 1.0), mode='reroll')", Positive(Normal(0, 1.0), mode="reroll")),
          ("Negative(Normal(0, 1.0))", Negative(Normal(0, 1.0))),
          ("Negative(Normal(0, 1.0), mode='reroll')", Negative(Normal(0, 1.0), mode="reroll")),
          ("Laplace(0, 1.0)", Laplace(0, 1.0)),
          ("Laplace(1.0, 3.0)", Laplace(1.0, 3.0)),
          ("Laplace([-1.0, 1.0], 1.0)", Laplace([-1.0, 1.0], 1.0)),
          ("ChiSquare(1)", ChiSquare(1)),
          ("ChiSquare([1, 6])", ChiSquare([1, 6])),
          ("Weibull(0.5)", Weibull(0.5)),
          ("Weibull((1.0, 3.0))", Weibull((1.0, 3.0))),
          ("Uniform(0, 10)", Uniform(0, 10)),
          ("Beta(0.5, 0.5)", Beta(0.5, 0.5)),
          ("Deterministic(1)", Deterministic(1)),
          ("Clip(Normal(0, 1), 0, None)", Clip(Normal(0, 1), minval=0, maxval=None)),
          ("Multiply(Uniform(0, 10), 2)", Multiply(Uniform(0, 10), 2)),
          ("Add(Uniform(0, 10), 5)", Add(Uniform(0, 10), 5)),
          ("Absolute(Normal(0, 1))", Absolute(Normal(0, 1))),
          ("RandomSign(Poisson(1))", RandomSign(Poisson(1))),
          ("RandomSign(Poisson(1), 0.9)", RandomSign(Poisson(1), 0.9))
      ]
  
      params_arithmetic = [
          ("Normal(0, 1.0)", Normal(0.0, 1.0)),
          ("Normal(0, 1.0) + 5", Normal(0.0, 1.0) + 5),
          ("Normal(0, 1.0) * 10", Normal(0.0, 1.0) * 10),
          ("Normal(0, 1.0) / 10", Normal(0.0, 1.0) / 10),
          ("Normal(0, 1.0) ** 2", Normal(0.0, 1.0) ** 2)
      ]
  
      params_noise = [
          ("SimplexNoise", SimplexNoise()),
          ("Sigmoid(SimplexNoise)", Sigmoid(SimplexNoise())),
          ("SimplexNoise(linear)", SimplexNoise(upscale_method="linear")),
          ("SimplexNoise(nearest)", SimplexNoise(upscale_method="nearest")),
          ("FrequencyNoise((-4, 4))", FrequencyNoise(exponent=(-4, 4))),
          ("FrequencyNoise(-2)", FrequencyNoise(exponent=-2)),
          ("FrequencyNoise(2)", FrequencyNoise(exponent=2))
      ]
  
      images_params = [param.draw_distribution_graph() for (title, param) in params]
      images_arithmetic = [param.draw_distribution_graph() for (title, param) in params_arithmetic]
      images_noise = [param.draw_distribution_graph(size=(1000, 10, 10)) for (title, param) in params_noise]
  
      misc.imshow(np.vstack(images_params))
      misc.imshow(np.vstack(images_arithmetic))
      misc.imshow(np.vstack(images_noise))
  
  if __name__ == "__main__":
      main()
  
subject: Add parameters check