(self, flag=True, full_copy=False, max_processes=None)
Sets the flag to enable/disable the use of python multiprocessing module.
      Use this option when you have more than one core on your CPU and when your
      evaluation function is very slow.
      The parameter "full_copy" defines where the individual data should be copied back
      after the evaluation or not. This parameter is useful when you change the
      individual in the evaluation function.

      :param flag: True (default) or False
      :param full_copy: True or False (default)
      :param max_processes: None (default) or an integer value

      .. warning:: Use this option only when your evaluation function is slow, se you
                   will get a good tradeoff between the process communication speed and the
                   parallel evaluation.

      .. versionadded:: 0.6
         The `setMultiProcessing` method.
Sets the flag to enable/disable the use of python multiprocessing module.
      Use this option when you have more than one core on your CPU and when your
      evaluation function is very slow.
      The parameter "full_copy" defines where the individual data should be copied back
      after the evaluation or not. This parameter is useful when you change the
      individual in the evaluation function.
Sets the flag to enable / disable the use of python multiprocessing module . Use this option when you have more than one core on your CPU and when your evaluation function is very slow . The parameter full_copy defines where the individual data should be copied back after the evaluation or not . This parameter is useful when you change the individual in the evaluation function .
def setMultiProcessing(self, flag=True, full_copy=False, max_processes=None):
      """ Sets the flag to enable/disable the use of python multiprocessing module.
      Use this option when you have more than one core on your CPU and when your
      evaluation function is very slow.
      The parameter "full_copy" defines where the individual data should be copied back
      after the evaluation or not. This parameter is useful when you change the
      individual in the evaluation function.

      :param flag: True (default) or False
      :param full_copy: True or False (default)
      :param max_processes: None (default) or an integer value

      .. warning:: Use this option only when your evaluation function is slow, se you
                   will get a good tradeoff between the process communication speed and the
                   parallel evaluation.

      .. versionadded:: 0.6
         The `setMultiProcessing` method.

      """
      self.multiProcessing = (flag, full_copy, max_processes)
def setMultiProcessing ( self , flag = True , full_copy = False , max_processes = None ) : self . multiProcessing = ( flag , full_copy , max_processes )