openghg_inversions.rhime.sampling#

RHIME sampling helpers.

class openghg_inversions.rhime.sampling.RhimeSampler(*, draws: int = 1000, burn: int = 0, tune: int = 1000, chains: int = 4, nuts_sampler: Literal['pymc', 'nutpie', 'numpyro', 'blackjax'] | str = 'pymc', progressbar: bool = False, sample_kwargs: dict[str, Any] | None = None, sample_prior_predictive: bool | int = True, sample_posterior_predictive: bool | Sequence[str] = ('y',), posterior_predictive_kwargs: dict[str, Any] | None = None)#

Bases: object

PyMC sampler configuration and execution for RHIME models.

Parameters:

  • draws – Number of post-tuning draws requested from PyMC.

  • burn – Number of draws to discard from each chain after sampling.

  • tune – Number of PyMC tuning draws.

  • chains – Number of MCMC chains.

  • nuts_sampler – PyMC NUTS backend name.

  • progressbar – Whether PyMC progress output should be shown.

  • sample_kwargs – Extra keyword arguments forwarded to pm.sample.

  • sample_prior_predictive – Whether to append prior predictive draws.

  • sample_posterior_predictive – Whether to append posterior predictive draws, or variable names to sample.

  • posterior_predictive_kwargs – Extra keyword arguments forwarded to pm.sample_posterior_predictive.

burn: int#
chains: int#
draws: int#
nuts_sampler: Literal['pymc', 'nutpie', 'numpyro', 'blackjax']#
posterior_predictive_kwargs: dict[str, Any] | None#
progressbar: bool#
sample(model: Model, *, variable_roles: Mapping[str, str] | None = None) → InferenceData#

Sample a built RHIME model and append requested predictive groups.

Parameters:

  • model – Concrete PyMC model to sample.

  • variable_roles – Optional semantic-role manifest from a RhimeModelBuildResult. Posterior-predictive entries may be role names. The historical default "y" resolves to the explicit concentration role when a custom model has no variable named y.

sample_kwargs: dict[str, Any] | None#
sample_posterior_predictive: bool | tuple[str, ...]#
sample_prior_predictive: bool | int#
tune: int#
openghg_inversions.rhime.sampling.sample_rhime_model(model_build_result: RhimeModelBuildResult, sampler: RhimeSampler) → InferenceData#

Sample a built RHIME graph at the named sampler boundary.

Parameters:

  • model_build_result – Concrete graph and semantic variable roles.

  • sampler – Configured sampler used for posterior and predictive draws.

Returns:

Sampled posterior and predictive groups.