def __init__(self, data, number_cluster, number_represent_points = <NUM_LIT:5>, compression = <NUM_LIT:0.5>, ccore = True):
self.__pointer_data = self.__prepare_data_points(data)<EOL>self.__clusters = None<EOL>self.__representors = None<EOL>self.__means = None<EOL>self.__number_cluster = number_cluster<EOL>self.__number_represent_points = number_represent_points<EOL>self.__compression = compression<EOL>self.__ccore = ccore<EOL>if self.__ccore:<EOL><INDENT>self.__ccore = ccore_library.workable()<EOL><DEDENT>self.__validate_arguments()<EOL>
!
        @brief Constructor of clustering algorithm CURE.

        @param[in] data (array_like): Input data that should be processed.
        @param[in] number_cluster (uint): Number of clusters that should be allocated.
        @param[in] number_represent_points (uint): Number of representative points for each cluster.
        @param[in] compression (double): Coefficient defines level of shrinking of representation points toward the mean of the new created cluster after merging on each step. Usually it destributed from 0 to 1.
        @param[in] ccore (bool): If True then CCORE (C++ solution) will be used for solving.