pyclustering/cluster/birch.py
def __get_nearest_feature(self, point, feature_collection):
        """!
        @brief Find nearest entry for specified point.
        
        @param[in] point (list): Pointer to point from input dataset.
        @param[in] feature_collection (list): Feature collection that is used for obtaining nearest feature for the specified point.
        
        @return (double, uint) Tuple of distance to nearest entry to the specified point and index of that entry.
        
        """
        
        minimum_distance = float("Inf");
        index_nearest_feature = -1;
        
        for index_entry in range(0, len(feature_collection)):
            point_entry = cfentry(1, linear_sum([ point ]), square_sum([ point ]));
            
            distance = feature_collection[index_entry].get_distance(point_entry, self.__measurement_type);
            if (distance < minimum_distance):
                minimum_distance = distance;
                index_nearest_feature = index_entry;
                
        return (minimum_distance, index_nearest_feature);
def __get_nearest_feature(self, point, feature_collection):
        """!
        @brief Find nearest entry for specified point.
        
        @param[in] point (list): Pointer to point from input dataset.
        @param[in] feature_collection (list): Feature collection that is used for obtaining nearest feature for the specified point.
        
        @return (double, uint) Tuple of distance to nearest entry to the specified point and index of that entry.
        
        """
        
        minimum_distance = float("Inf");
        index_nearest_feature = -1;
        
        for index_entry in range(0, len(feature_collection)):
            point_entry = cfentry(1, linear_sum([ point ]), square_sum([ point ]));
            
            distance = feature_collection[index_entry].get_distance(point_entry, self.__measurement_type);
            if (distance < minimum_distance):
                minimum_distance = distance;
                index_nearest_feature = index_entry;
                
        return (minimum_distance, index_nearest_feature);
def __get_nearest_feature ( self , point , feature_collection ) : minimum_distance = float ( "Inf" ) index_nearest_feature = - 1 for index_entry in range ( 0 , len ( feature_collection ) ) : point_entry = cfentry ( 1 , linear_sum ( [ point ] ) , square_sum ( [ point ] ) ) distance = feature_collection [ index_entry ] . get_distance ( point_entry , self . __measurement_type ) if ( distance < minimum_distance ) : minimum_distance = distance index_nearest_feature = index_entry return ( minimum_distance , index_nearest_feature )
!
        @brief Find nearest entry for specified point.
        
        @param[in] point (list): Pointer to point from input dataset.
        @param[in] feature_collection (list): Feature collection that is used for obtaining nearest feature for the specified point.
        
        @return (double, uint) Tuple of distance to nearest entry to the specified point and index of that entry.
!