def __mul__(self, other):
if isinstance(other, CovarianceFunction):
return CovarianceFunction(covariance=lambda x, y: self.covariance(x, y)*other.covariance(x, y))
if isinstance(other, (Variable, PartialLink)):
other = var2link(other)
return CovarianceFunction(covariance=lambda x, y: self.covariance(x, y) * other)
elif isinstance(other, (int, float)):
return CovarianceFunction(covariance=lambda x, y: self.covariance(x, y) * other)
else:
raise ValueError("Only covarianceFunctions and numbers can be multiplied with CovarianceFunctions")
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, 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, 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, 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)
def get_joint_instance(self, query_points):
x = var2link(query_points)
return MultivariateNormalVariable(
loc=self.mean_function(x),
covariance_matrix=self.covariance_function(x),
name=self.name + "(" + query_points.name + ")")
