(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.

        Pyevolve will automaticly check if your Python version has **multiprocessing**
        support and if you have more than one single CPU core. If you don't have support
        or have just only one core, Pyevolve will not use the **multiprocessing**
        feature.

        Pyevolve uses the **multiprocessing** to execute the evaluation function over
        the individuals, so the use of this feature will make sense if you have a
        truly slow evaluation function (which is commom in GAs).

        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, so you'll
                     get a good tradeoff between the process communication speed and the
                     parallel evaluation. The use of the **multiprocessing** doesn't means
                     always a better performance.

        .. note:: To enable the multiprocessing option, you **MUST** add the *__main__* check
                  on your application, otherwise, it will result in errors. See more on the
                  `Python Docs <http://docs.python.org/library/multiprocessing.html#multiprocessing-programming>`__
                  site.

        .. 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.
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 .
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.

        Pyevolve will automaticly check if your Python version has **multiprocessing**
        support and if you have more than one single CPU core. If you don't have support
        or have just only one core, Pyevolve will not use the **multiprocessing**
        feature.

        Pyevolve uses the **multiprocessing** to execute the evaluation function over
        the individuals, so the use of this feature will make sense if you have a
        truly slow evaluation function (which is commom in GAs).

        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, so you'll
                     get a good tradeoff between the process communication speed and the
                     parallel evaluation. The use of the **multiprocessing** doesn't means
                     always a better performance.

        .. note:: To enable the multiprocessing option, you **MUST** add the *__main__* check
                  on your application, otherwise, it will result in errors. See more on the
                  `Python Docs <http://docs.python.org/library/multiprocessing.html#multiprocessing-programming>`__
                  site.

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

        """
        if type(flag) != BooleanType:
            Util.raiseException("Multiprocessing option must be True or False", TypeError)

        if type(full_copy) != BooleanType:
            Util.raiseException("Multiprocessing 'full_copy' option must be True or False", TypeError)

        self.internalPop.setMultiProcessing(flag, full_copy, max_processes)
def setMultiProcessing ( self , flag = True , full_copy = False , max_processes = None ) : if type ( flag ) != BooleanType : Util . raiseException ( "Multiprocessing option must be True or False" , TypeError ) if type ( full_copy ) != BooleanType : Util . raiseException ( "Multiprocessing 'full_copy' option must be True or False" , TypeError ) self . internalPop . setMultiProcessing ( flag , full_copy , max_processes )