CovarianceKernel (pmrf.CovarianceKernel)

class pmrf.CovarianceKernel(*, name: str | None = None)

Bases: Module, ABC

Abstract base class for covariance kernel functions.

These kernels are used in a Gaussian Process for discrepancy modeling.

__add__(other: CovarianceKernel) → CovarianceKernel
abstractmethod __call__(x1: Array, x2: Array, key=None) → Array

Evaluate the kernel between two points.

Parameters:

  • x1 (jnp.ndarray) – First input point.

  • x2 (jnp.ndarray) – Second input point.

  • key (jax.random.PRNGKey, optional) – Random key for stochastic kernels.

Returns:

Kernel covariance scalar.

Return type:

jnp.ndarray

__mul__(other: CovarianceKernel) → CovarianceKernel