def __call__(self, d):
    p = (d.vector_sum()[1] if d.cyclic else self._weighted_average(d))
    p = (self.value_scale[1] * (p + self.value_scale[0]))
    s = (self.selectivity_scale[1] * (self.selectivity(d) + self.selectivity_scale[0]))
    return {'': Pref(preference=p, selectivity=s)}
def __call__(self, d):
    p = (d.vector_sum()[1] if d.cyclic else self._weighted_average(d))
    p = (self.value_scale[1] * (p + self.value_scale[0]))
    s = (self.selectivity_scale[1] * (self.selectivity(d) + self.selectivity_scale[0]))
    return {: Pref(preference=p, selectivity=s)}