pyclustering/cluster/kmeans.py
def __calculate_total_wce(self):
        """!
        @brief Calculate total within cluster errors that is depend on metric that was chosen for K-Means algorithm.

        """

        dataset_differences = self.__calculate_dataset_difference(len(self.__clusters))

        self.__total_wce = 0
        for index_cluster in range(len(self.__clusters)):
            for index_point in self.__clusters[index_cluster]:
                self.__total_wce += dataset_differences[index_cluster][index_point]
def __calculate_total_wce(self):
        """!
        @brief Calculate total within cluster errors that is depend on metric that was chosen for K-Means algorithm.

        """

        dataset_differences = self.__calculate_dataset_difference(len(self.__clusters))

        self.__total_wce = 0
        for index_cluster in range(len(self.__clusters)):
            for index_point in self.__clusters[index_cluster]:
                self.__total_wce += dataset_differences[index_cluster][index_point]
!
        @brief Calculate total within cluster errors that is depend on metric that was chosen for K-Means algorithm.