change json format to ConfigSpace format dict<dict> -> configspace

        Parameters
        ----------
        data: JSON object
            search space of this experiment

def handle_update_search_space(self, data):
        """change json format to ConfigSpace format dict<dict> -> configspace

        Parameters
        ----------
        data: JSON object
            search space of this experiment
        """
        search_space = data
        cs = CS.ConfigurationSpace()
        for var in search_space:
            _type = str(search_space[var]["_type"])
            if _type == 'choice':
                cs.add_hyperparameter(CSH.CategoricalHyperparameter(
                    var, choices=search_space[var]["_value"]))
            elif _type == 'randint':
                cs.add_hyperparameter(CSH.UniformIntegerHyperparameter(
                    var, lower=0, upper=search_space[var]["_value"][0]))
            elif _type == 'uniform':
                cs.add_hyperparameter(CSH.UniformFloatHyperparameter(
                    var, lower=search_space[var]["_value"][0], upper=search_space[var]["_value"][1]))
            elif _type == 'quniform':
                cs.add_hyperparameter(CSH.UniformFloatHyperparameter(
                    var, lower=search_space[var]["_value"][0], upper=search_space[var]["_value"][1], 
                    q=search_space[var]["_value"][2]))
            elif _type == 'loguniform':
                cs.add_hyperparameter(CSH.UniformFloatHyperparameter(
                    var, lower=search_space[var]["_value"][0], upper=search_space[var]["_value"][1], 
                    log=True))
            elif _type == 'qloguniform':
                cs.add_hyperparameter(CSH.UniformFloatHyperparameter(
                    var, lower=search_space[var]["_value"][0], upper=search_space[var]["_value"][1], 
                    q=search_space[var]["_value"][2], log=True))
            elif _type == 'normal':
                cs.add_hyperparameter(CSH.NormalFloatHyperparameter(
                    var, mu=search_space[var]["_value"][1], sigma=search_space[var]["_value"][2]))
            elif _type == 'qnormal':
                cs.add_hyperparameter(CSH.NormalFloatHyperparameter(
                    var, mu=search_space[var]["_value"][1], sigma=search_space[var]["_value"][2], 
                    q=search_space[var]["_value"][3]))
            elif _type == 'lognormal':
                cs.add_hyperparameter(CSH.NormalFloatHyperparameter(
                    var, mu=search_space[var]["_value"][1], sigma=search_space[var]["_value"][2], 
                    log=True))
            elif _type == 'qlognormal':
                cs.add_hyperparameter(CSH.NormalFloatHyperparameter(
                    var, mu=search_space[var]["_value"][1], sigma=search_space[var]["_value"][2], 
                    q=search_space[var]["_value"][3], log=True))
            else:
                raise ValueError(
                    'unrecognized type in search_space, type is {}'.format(_type))

        self.search_space = cs