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)