AbstractCovarianceKernel

class pmrf.covariance_kernels.AbstractCovarianceKernel

Bases: Module

Abstract base class for covariance kernel functions.

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

__add__(other: AbstractCovarianceKernel) → AbstractCovarianceKernel

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: AbstractCovarianceKernel | TypeAliasForwardRef('Param') | float) → AbstractCovarianceKernel