Matern52#
- class tinygp.kernels.quasisep.Matern52(scale: JAXArray | float, sigma: JAXArray | float = <factory>)[source]#
Bases:
Quasisep
A scalable implementation of
tinygp.kernels.stationary.Matern52
This kernel takes the form:
\[k(\tau)=\sigma^2\,\left(1+f\,\tau + \frac{f^2\,\tau^2}{3}\right) \,\exp(-f\,\tau)\]for \(\tau = |x_i - x_j|\) and \(f = \sqrt{5} / \ell\).
- Parameters:
scale – The parameter \(\ell\).
sigma (optional) – The parameter \(\sigma\). Defaults to a value of 1. Specifying the explicit value here provides a slight performance boost compared to independently multiplying the kernel with a prefactor.
- 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.
- 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 [source]#
The observation model for the process
- to_general_qsm(X1: tinygp.helpers.JAXArray, X2: tinygp.helpers.JAXArray) GeneralQSM #
The generalized quasiseparable representation of this kernel