def __init__(self, value):
value = value
mean = lambda x: BF.delta(x, x) * value
super().__init__(mean=mean)
def __init__(self, scale, jitter=0.):
self.scale = var2link(scale)
covariance = lambda x, y: BF.exp(-BF.abs(x - y) /
(scale)) + BF.delta(x, y) * jitter
super().__init__(covariance=covariance)
def __init__(self, frequency, jitter=0.):
self.frequency = var2link(frequency)
covariance = lambda x, y: BF.cos(2 * np.pi * self.frequency *
(x - y)) + BF.delta(x, y) * jitter
super().__init__(covariance=covariance)
def __init__(self, frequency, scale, jitter=0.):
self.frequency = var2link(frequency)
self.scale = var2link(scale)
covariance = lambda x, y: BF.exp(-2 * BF.sin(np.pi * self.frequency * (
x - y))**2 / scale**2) + BF.delta(x, y) * jitter
super().__init__(covariance=covariance)
def __init__(self, magnitude, jitter=0.):
self.magnitude = var2link(magnitude)
covariance = lambda x, y: magnitude * BF.delta(x, y) + BF.delta(
x, y) * jitter
super().__init__(covariance=covariance)
