elisa.infer.samplers.ensemble.emcee#

class EmceeSampler(numpyro_model: Callable, init_params: dict[str, float] | None = None, ignore_nan: bool = False, seed: int = 42, model_args: tuple = (), model_kwargs: dict | None = None)[source]#

Methods

`get_random_state`(seed)	Get the random state for the sampler.
`get_sampling_fn`(chains, warmup, steps, ...)	Generate the sampling function.
`run`([warmup, steps, chains, thinning, ...])	Run the sampler.

get_sampling_fn(chains: int, warmup: int, steps: int, thinning: int, tune: bool | None, warmup_kwargs: dict, sampling_kwargs: dict)[source]#: Generate the sampling function.

get_random_state(seed: int) → Generator[source]#: Get the random state for the sampler.