Scale#

class tinygp.kernels.quasisep.Scale(kernel: Quasisep, scale: JAXArray | float)[source]#

Bases: Wrapper

The product of a scalar and a quasiseparable kernel

coord_to_sortable(X: tinygp.helpers.JAXArray) → tinygp.helpers.JAXArray#

A helper function used to convert coordinates to sortable 1-D values

By default, this is the identity, but in cases where X is structured (e.g. multivariate inputs), this can be used to appropriately unwrap that structure.

design_matrix() → tinygp.helpers.JAXArray#: The design matrix for the process

evaluate(X1: tinygp.helpers.JAXArray, X2: tinygp.helpers.JAXArray) → tinygp.helpers.JAXArray#: The kernel evaluated via the quasiseparable representation

evaluate_diag(X: tinygp.helpers.JAXArray) → tinygp.helpers.JAXArray#: For quasiseparable kernels, the variance is simple to compute

observation_model(X: tinygp.helpers.JAXArray) → tinygp.helpers.JAXArray#: The observation model for the process

stationary_covariance() → tinygp.helpers.JAXArray[source]#: The stationary covariance of the process

to_general_qsm(X1: tinygp.helpers.JAXArray, X2: tinygp.helpers.JAXArray) → GeneralQSM#: The generalized quasiseparable representation of this kernel

to_symm_qsm(X: tinygp.helpers.JAXArray) → SymmQSM#: The symmetric quasiseparable representation of this kernel

transition_matrix(X1: tinygp.helpers.JAXArray, X2: tinygp.helpers.JAXArray) → tinygp.helpers.JAXArray#: The transition matrix between two coordinates

Scale

Contents

Scale#