How to use the opentuner.search.manipulator.ConfigurationManipulator function in opentuner

def setUp(self):
        """
        Set up a few configurations. The values of the PermutationParameter are:
        config1 - 0 1 2 3 4 5 6 7 8 9
        config2 - 4 3 2 1 0 9 8 7 6 5
        config3 - 1 0 4 2 7 9 5 3 6 8

        """
        self.manipulator = manipulator.ConfigurationManipulator()
        self.param1 = manipulator.PermutationParameter("param1", [0,1,2,3,4,5,6,7,8,9])
        self.manipulator.add_parameter(self.param1)

        self.cfg = self.manipulator.seed_config()
        self.config1 = self.manipulator.seed_config()
        self.config2 = self.manipulator.seed_config()
        self.config3 = self.manipulator.seed_config()

        # repeating values
        self.config4 = self.manipulator.seed_config()
        self.config5 = self.manipulator.seed_config()


        self.param1.set_value(self.config1, [0,1,2,3,4,5,6,7,8,9])
        self.param1.set_value(self.config2, [4,3,2,1,0,9,8,7,6,5])
        self.param1.set_value(self.config3, [1,0,4,2,7,9,5,3,6,8])

def main(args, cfg, jvmOptions):
	logging.basicConfig(level=logging.INFO)
	manipulator = ConfigurationManipulator()

	params = dict(cfg.items() + jvmOptions.items())
	#print "\nFeature variables...."
	for key in params.keys():
		#print "\t", key
  		manipulator.add_parameter(params.get(key))
	
	mi = StreamJitMI(args,jvmOptions, manipulator, FixedInputManager(),
                    MinimizeTime())

	m = TuningRunMain(mi, args)
	m.main()

def build_manipulator(api_config):
        """Build a ConfigurationManipulator object to be used by opentuner.

        Parameters
        ----------
        api_config : dict-like of dict-like
            Configuration of the optimization variables. See API description.

        Returns
        -------
        manipulator : ConfigurationManipulator
            Some over complexified class required by opentuner to run.
        """
        manipulator = ConfigurationManipulator()

        for pname in api_config:
            ptype = api_config[pname]["type"]
            pspace = api_config[pname].get("space", None)
            pmin, pmax = api_config[pname].get("range", (None, None))

            if ptype == "real":
                if pspace in ("linear", "logit"):
                    ot_param = FloatParameter(pname, pmin, pmax)
                elif pspace in ("log", "bilog"):
                    LogFloatParameter_ = ClippedParam(LogFloatParameter)
                    ot_param = LogFloatParameter_(pname, pmin, pmax)
                else:
                    assert False, "unsupported param space = %s" % pspace
            elif ptype == "int":
                if pspace in ("linear", "logit"):

def main():
    parser = argparse.ArgumentParser(parents=opentuner.argparsers())
    args = parser.parse_args()
    manipulator = ConfigurationManipulator()
    manipulator.add_parameter(IntegerParameter('x', -200, 200))
    interface = DefaultMeasurementInterface(args=args,
                                            manipulator=manipulator,
                                            project_name='examples',
                                            program_name='api_test',
                                            program_version='0.1')
    api = TuningRunManager(interface, args)
    for x in range(500):
        desired_result = api.get_next_desired_result()
        if desired_result is None:
          # The search space for this example is very small, so sometimes
          # the techniques have trouble finding a config that hasn't already
          # been tested.  Change this to a continue to make it try again.
          break
        cfg = desired_result.configuration.data
        result = Result(time=test_func(cfg))

def create_test_tuning_run(db):
  parser = argparse.ArgumentParser(parents=opentuner.argparsers())
  args = parser.parse_args()
  args.database = db
  manipulator = ConfigurationManipulator()
  manipulator.add_parameter(IntegerParameter('x', -200, 200))
  interface = DefaultMeasurementInterface(args=args,
                                          manipulator=manipulator,
                                          project_name='examples',
                                          program_name='api_test',
                                          program_version='0.1')
  api = TuningRunManager(interface, args)
  return api

def build_manipulator(api_config):
        """Build a ConfigurationManipulator object to be used by opentuner.

        Parameters
        ----------
        api_config : dict-like of dict-like
            Configuration of the optimization variables. See API description.

        Returns
        -------
        manipulator : ConfigurationManipulator
            Some over complexified class required by opentuner to run.
        """
        manipulator = ConfigurationManipulator()

        for pname in api_config:
            ptype = api_config[pname]["type"]
            pspace = api_config[pname].get("space", None)
            pmin, pmax = api_config[pname].get("range", (None, None))

            if ptype == "real":
                if pspace in ("linear", "logit"):
                    ot_param = FloatParameter(pname, pmin, pmax)
                elif pspace in ("log", "bilog"):
                    LogFloatParameter_ = ClippedParam(LogFloatParameter)
                    ot_param = LogFloatParameter_(pname, pmin, pmax)
                else:
                    assert False, "unsupported param space = %s" % pspace
            elif ptype == "int":
                if pspace in ("linear", "logit"):

def manipulator(self):
    m = manipulator.ConfigurationManipulator()
    m.add_parameter(manipulator.IntegerParameter('-O', 0, 3))
    for flag in self.cc_flags:
      m.add_parameter(manipulator.EnumParameter(flag, ['on', 'off', 'default']))
    for param in self.cc_params:
      defaults = self.cc_param_defaults[param]
      if defaults['max'] <= defaults['min']:
        defaults['max'] = float('inf')
      defaults['max'] = min(defaults['max'],
                            max(1, defaults['default']) * args.scaler)
      defaults['min'] = max(defaults['min'],
                            old_div(max(1, defaults['default']), args.scaler))

      if param == 'l1-cache-line-size':
        # gcc requires this to be a power of two or it internal errors
        m.add_parameter(manipulator.PowerOfTwoParameter(param, 4, 256))
      elif defaults['max'] > 128: