pyclustering/cluster/center_initializer.py
def __check_parameters(self):
        """!
        @brief Checks input parameters of the algorithm and if something wrong then corresponding exception is thrown.

        """
        if (self.__amount <= 0) or (self.__amount > len(self.__data)):
            raise AttributeError("Amount of cluster centers '" + str(self.__amount) + "' should be at least 1 and "
                                 "should be less or equal to amount of points in data.")

        if self.__candidates != kmeans_plusplus_initializer.FARTHEST_CENTER_CANDIDATE:
            if (self.__candidates <= 0) or (self.__candidates > len(self.__data)):
                raise AttributeError("Amount of center candidates '" + str(self.__candidates) + "' should be at least 1 "
                                     "and should be less or equal to amount of points in data.")

        if len(self.__data) == 0:
            raise AttributeError("Data is empty.")
def __check_parameters(self):
        """!
        @brief Checks input parameters of the algorithm and if something wrong then corresponding exception is thrown.

        """
        if (self.__amount <= 0) or (self.__amount > len(self.__data)):
            raise AttributeError("Amount of cluster centers '" + str(self.__amount) + "' should be at least 1 and "
                                 "should be less or equal to amount of points in data.")

        if self.__candidates != kmeans_plusplus_initializer.FARTHEST_CENTER_CANDIDATE:
            if (self.__candidates <= 0) or (self.__candidates > len(self.__data)):
                raise AttributeError("Amount of center candidates '" + str(self.__candidates) + "' should be at least 1 "
                                     "and should be less or equal to amount of points in data.")

        if len(self.__data) == 0:
            raise AttributeError("Data is empty.")
def __check_parameters ( self ) : if ( self . __amount <= 0 ) or ( self . __amount > len ( self . __data ) ) : raise AttributeError ( "Amount of cluster centers '" + str ( self . __amount ) + "' should be at least 1 and " "should be less or equal to amount of points in data." ) if self . __candidates != kmeans_plusplus_initializer . FARTHEST_CENTER_CANDIDATE : if ( self . __candidates <= 0 ) or ( self . __candidates > len ( self . __data ) ) : raise AttributeError ( "Amount of center candidates '" + str ( self . __candidates ) + "' should be at least 1 " "and should be less or equal to amount of points in data." ) if len ( self . __data ) == 0 : raise AttributeError ( "Data is empty." )
!
        @brief Checks input parameters of the algorithm and if something wrong then corresponding exception is thrown.
! @brief Checks input parameters of the algorithm and if something wrong then corresponding exception is thrown .