class_docstr: Decorator for evaluation functions, it evaluates the objective function
  and adds noise by calling the function(s) provided in the *noise*
  argument. The noise functions are called without any argument, consider
  using the :class:`~deap.base.Toolbox` or Python's
  :func:`functools.partial` to provide any required argument. If a single
  function is provided it is applied to all objectives of the evaluation
  function. If a list of noise functions is provided, it must be of length
  equal to the number of objectives. The noise argument also accept
  :obj:`None`, which will leave the objective without noise.
  
  This decorator adds a :func:`noise` method to the decorated
  function.
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code: def __init__(self, noise):
      try:
          self.rand_funcs = tuple(noise)
      except TypeError:
          self.rand_funcs = repeat(noise)
  
imports: from math import hypot, sqrt
  from functools import wraps
  from itertools import repeat
label_desc: Use image node_id 1 to create a new noise object from inherited base classes: object with example: obj = noise(noise)