(self, Y, threshold=0)
Construct a Pareto set.

        Stores a Pareto set and calculates the cell bounds covering the non-dominated region.
        The latter is needed for certain multiobjective acquisition functions.
        E.g., the :class:`~.acquisition.HVProbabilityOfImprovement`.

        :param Y: output data points, size N x R
        :param threshold: approximation threshold for the generic divide and conquer strategy
            (default 0: exact calculation)
Construct a Pareto set.
Construct a Pareto set .
def __init__(self, Y, threshold=0):
        """
        Construct a Pareto set.

        Stores a Pareto set and calculates the cell bounds covering the non-dominated region.
        The latter is needed for certain multiobjective acquisition functions.
        E.g., the :class:`~.acquisition.HVProbabilityOfImprovement`.

        :param Y: output data points, size N x R
        :param threshold: approximation threshold for the generic divide and conquer strategy
            (default 0: exact calculation)
        """
        super(Pareto, self).__init__()
        self.threshold = threshold
        self.Y = Y

        # Setup data structures
        self.bounds = BoundedVolumes.empty(Y.shape[1], np_int_type)
        self.front = DataHolder(np.zeros((0, Y.shape[1])), 'pass')

        # Initialize
        self.update()
def __init__ ( self , Y , threshold = 0 ) : super ( Pareto , self ) . __init__ ( ) self . threshold = threshold self . Y = Y # Setup data structures self . bounds = BoundedVolumes . empty ( Y . shape [ 1 ] , np_int_type ) self . front = DataHolder ( np . zeros ( ( 0 , Y . shape [ 1 ] ) ) , 'pass' ) # Initialize self . update ( )