def __create_distance_calculator_numpy(self):
if self.__type == type_metric.EUCLIDEAN:<EOL><INDENT>return euclidean_distance_numpy<EOL><DEDENT>elif self.__type == type_metric.EUCLIDEAN_SQUARE:<EOL><INDENT>return euclidean_distance_square_numpy<EOL><DEDENT>elif self.__type == type_metric.MANHATTAN:<EOL><INDENT>return manhattan_distance_numpy<EOL><DEDENT>elif self.__type == type_metric.CHEBYSHEV:<EOL><INDENT>return chebyshev_distance_numpy<EOL><DEDENT>elif self.__type == type_metric.MINKOWSKI:<EOL><INDENT>return lambda object1, object2: minkowski_distance_numpy(object1, object2, self.__args.get('<STR_LIT>', <NUM_LIT:2>))<EOL><DEDENT>elif self.__type == type_metric.CANBERRA:<EOL><INDENT>return canberra_distance_numpy<EOL><DEDENT>elif self.__type == type_metric.CHI_SQUARE:<EOL><INDENT>return chi_square_distance_numpy<EOL><DEDENT>elif self.__type == type_metric.USER_DEFINED:<EOL><INDENT>return self.__func<EOL><DEDENT>else:<EOL><INDENT>raise ValueError("<STR_LIT>", self.__type)<EOL><DEDENT>
!
        @brief Creates distance metric calculator that uses numpy.

        @return (callable) Callable object of distance metric calculator.