class_docstr: nobs iid compound poisson distributions, not a process in time
      
class_docstr_tok: ["nobs","iid","compound","poisson","distributions",",","not","a","process","in","time"]
code: def __init__(self, lambd, randfn=np.random.normal):
      if len(lambd) != len(randfn):
          raise ValueError(
              "lambd and randfn need to have the same number of elements"
          )
  
      self.nobj = len(lambd)
      self.randfn = randfn
      self.lambd = np.asarray(lambd)
  
imports: import numpy
  from scipy import stats, signal
  import matplotlib.pyplot
label_desc: Use image node_id 1 to create a new CompoundPoisson object  with example: obj = CompoundPoisson(lambd, randfn)