class_docstr: Distribution based on log/exp transformation
  
  the constructor can be called with a distribution class
  and generates the distribution of the transformed random variable
class_docstr_tok: ["Distribution","based","on","log\/exp","transformation","the","constructor","can","be","called","with","a","distribution","class","and","generates","the","distribution","of","the","transformed","random","variable"]
code: def __init__(self, kls, *args, **kwargs):
      # explicit for self.__dict__.update(kwargs)
      if "numargs" in kwargs:
          self.numargs = kwargs["numargs"]
      else:
          self.numargs = 1
      if "name" in kwargs:
          name = kwargs["name"]
      else:
          name = "Log transformed distribution"
      if "a" in kwargs:
          a = kwargs["a"]
      else:
          a = 0
  
      super().__init__(a=a, name=name)
      self.kls = kls
  
imports: from scipy import stats
  from scipy.stats import distributions
  import numpy
label_desc: Use image node_id 1 to create a new LogTransf_gen object from inherited base classes: distributions with example: obj = LogTransf_gen(kls)