elisa.infer.samplers.ensemble.zeus#

class ZeusSampler(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) → tuple[source]#: Get the random state for the sampler.

class DifferentialMove(tune=True, mu0=1.0)[source]#

Improved DifferentialMove of zeus for reproducibility.

Methods

get_direction

get_direction(X: ndarray[tuple[Any, ...], dtype[float]], mu: float)[source]#