gpmp.parameter module

The gpmp.parameter module provides structured helpers around covariance-parameter vectors. It assigns names, paths, normalizations, and display metadata to parameters, especially in reports and model-container code.

This module is a convenience layer on top of the lower-level GPmp API. The core model and kernel routines remain independent from it: they accept plain arrays for covariance parameters and do not require Param objects.

Use this module when you need a human-readable object for a covariance vector, not when calling gpmp.core or gpmp.kernel directly.

Normalization convention

Param stores normalized values. The supported normalizations are:

  • "none": stored value equals physical value.

  • "log": stored value is log(value).

  • "log_inv": stored value is -log(value).

For the anisotropic Matérn convention, param_from_covparam_anisotropic(covparam) interprets covparam = [log(sigma2), -log(rho_0), ..., -log(rho_{d-1})] and attaches names sigma2, rho_0, …

Access patterns

Use get_by_name for a named scalar, get_by_path for hierarchical groups, and denormalized_values to inspect physical values. Bounds stored in Param are metadata for display and diagnostics. They are not enforced by Param itself.

Structured parameter objects for GPmp.

This package is a helper layer for naming, normalizing, and displaying parameter vectors. The lower-level gpmp.core and gpmp.kernel APIs operate on plain arrays and do not depend on gpmp.parameter.

class gpmp.parameter.Normalization(value)[source]
gpmp.parameter.make_anisotropic_param(d: int | None = None, values: List[float] | ndarray[tuple[Any, ...], dtype[floating]] | None = None, logsigma2_bounds: Tuple[float, float] | None = None, loginvrho_bounds: Tuple[float, float] | None = None, name_prefix: str = '') → Param[source]

Build a Param object for anisotropic covariance [sigma2, rho_1, …, rho_d].

If values is provided, its length must be d + 1. If not, d must be specified and default values [0.0, -1.0, …, -1.0] are used.

Returns a Param object with [log, log_inv, …, log_inv] normalization.