parameters: (self, problem=None, trials=1, rho=0.1, seed=0)
docstring: Inject noise to a problem in the decision space.
      The solution to the resulting problem is robust the the noise in the rho area.
  
      USAGE: problem.robust(problem=PyGMO.ackley(10), trials=1, rho=0.1, seed=0)
  
      * problem: PyGMO problem to be transformed to its robust version
      * trials: number of trials to average around
      * rho: Parameter controlling the magnitude of noise
      * seed: Seed for the underlying RNG
docstring_summary: Inject noise to a problem in the decision space.
      The solution to the resulting problem is robust the the noise in the rho area.
docstring_tokens: Inject noise to a problem in the decision space . The solution to the resulting problem is robust the the noise in the rho area .
function: def _robust_ctor(self, problem=None, trials=1, rho=0.1, seed=0):
      """
      Inject noise to a problem in the decision space.
      The solution to the resulting problem is robust the the noise in the rho area.
  
      USAGE: problem.robust(problem=PyGMO.ackley(10), trials=1, rho=0.1, seed=0)
  
      * problem: PyGMO problem to be transformed to its robust version
      * trials: number of trials to average around
      * rho: Parameter controlling the magnitude of noise
      * seed: Seed for the underlying RNG
      """
      arg_list = []
      if problem is None:
          problem = ackley(10)
      arg_list.append(problem)
      arg_list.append(trials)
      arg_list.append(rho)
      arg_list.append(seed)
      self._orig_init(*arg_list)
function_tokens: def _robust_ctor ( self , problem = None , trials = 1 , rho = 0.1 , seed = 0 ) : arg_list = [ ] if problem is None : problem = ackley ( 10 ) arg_list . append ( problem ) arg_list . append ( trials ) arg_list . append ( rho ) arg_list . append ( seed ) self . _orig_init ( * arg_list )