def __init__(self, data, maximum_clusters, threshold, ccore=True, **kwargs):
        """!
        @brief Creates classical BSAS algorithm.

        @param[in] data (list): Input data that is presented as list of points (objects), each point should be represented by list or tuple.
        @param[in] maximum_clusters: Maximum allowable number of clusters that can be allocated during processing.
        @param[in] threshold: Threshold of dissimilarity (maximum distance) between points.
        @param[in] ccore (bool): If True than DLL CCORE (C++ solution) will be used for solving.
        @param[in] **kwargs: Arbitrary keyword arguments (available arguments: 'metric').

        <b>Keyword Args:</b><br>
            - metric (distance_metric): Metric that is used for distance calculation between two points.

        """

        self._data = data;
        self._amount = maximum_clusters;
        self._threshold = threshold;
        self._metric = kwargs.get('metric', distance_metric(type_metric.EUCLIDEAN));
        self._ccore = ccore and self._metric.get_type() != type_metric.USER_DEFINED;

        self._clusters = [];
        self._representatives = [];

        if self._ccore is True:
            self._ccore = ccore_library.workable();
def __init__ ( self , data , maximum_clusters , threshold , ccore = True , ** kwargs ) : self . _data = data ; self . _amount = maximum_clusters ; self . _threshold = threshold ; self . _metric = kwargs . get ( 'metric' , distance_metric ( type_metric . EUCLIDEAN ) ) ; self . _ccore = ccore and self . _metric . get_type ( ) != type_metric . USER_DEFINED ; self . _clusters = [ ] ; self . _representatives = [ ] ; if self . _ccore is True : self . _ccore = ccore_library . workable ( ) ;
!
        @brief Creates classical BSAS algorithm.

        @param[in] data (list): Input data that is presented as list of points (objects), each point should be represented by list or tuple.
        @param[in] maximum_clusters: Maximum allowable number of clusters that can be allocated during processing.
        @param[in] threshold: Threshold of dissimilarity (maximum distance) between points.
        @param[in] ccore (bool): If True than DLL CCORE (C++ solution) will be used for solving.
        @param[in] **kwargs: Arbitrary keyword arguments (available arguments: 'metric').

        <b>Keyword Args:</b><br>
            - metric (distance_metric): Metric that is used for distance calculation between two points.