romcomma.user.run.gpr§

gpr(name, repo, is_read, is_covariant, is_isotropic, ignore_exceptions=False, kernel_parameters=None, likelihood_variance=None, is_calibrated=True, is_tested=True, **kwargs)[source]§

Undertake GPR on a Fold, or recursively across the Folds in a Repository.

Parameters:

  • name (str) – The MOGP name.

  • repo (Repository) – A Fold to house the MOGP, or a Repository containing Folds to house the GPs.

  • is_read (bool | None) – If True, MOGP kernel data and likelihood_variance are read from fold.folder/name, otherwise defaults are used. If None, the nearest ancestor MOGP in the independence/isotropy hierarchy is recursively constructed from its nearest ancestor MOGP if necessary, then read and broadcast available.

  • is_covariant (bool | None) – Whether the outputs are independent of each other or not. If None, independent is run then broadcast to run dependent.

  • is_isotropic (bool | None) – Whether the kernel is isotropic. If None, isotropic is run, then broadcast to run anisotropic.

  • ignore_exceptions (bool) – Whether to continue when the MOGP provider throws an exception.

  • kernel_parameters (Data | None) – If not None, this replaces the Kernel specified by the MOGP default.

  • likelihood_variance (ndarray | None) – If not None this replaces the likelihood_variance specified by the MOGP default.

  • is_calibrated (bool) – Whether to is_calibrated each MOGP.

  • is_tested (bool) – Whether to test_data each MOGP.

  • kwargs – A Dict of implementation-dependent passes straight to MOGP.Optimize().

Returns:

A list of the names of the GPs which have been constructed. The MOGP.Data are user.results.Aggregated over folds

Raises:

FileNotFoundError – If repo is not a Fold, and contains no Folds.

Return type:

List[str]