(self, models)
:param models: A list of (possibly multioutput) GPflow representing our belief of the objectives.
:param models: A list of (possibly multioutput) GPflow representing our belief of the objectives.
: param models : A list of ( possibly multioutput ) GPflow representing our belief of the objectives .
def __init__(self, models):
        """
        :param models: A list of (possibly multioutput) GPflow representing our belief of the objectives.
        """
        super(HVProbabilityOfImprovement, self).__init__(models)
        num_objectives = self.data[1].shape[1]
        assert num_objectives > 1

        # Keep empty for now - it is updated in _setup()
        self.pareto = Pareto(np.empty((0, num_objectives)))
        self.reference = DataHolder(np.ones((1, num_objectives)))
def __init__ ( self , models ) : super ( HVProbabilityOfImprovement , self ) . __init__ ( models ) num_objectives = self . data [ 1 ] . shape [ 1 ] assert num_objectives > 1 # Keep empty for now - it is updated in _setup() self . pareto = Pareto ( np . empty ( ( 0 , num_objectives ) ) ) self . reference = DataHolder ( np . ones ( ( 1 , num_objectives ) ) )