netket.sampler.MetropolisSamplerState

class netket.sampler.MetropolisSamplerState

Bases: SamplerState

State for a Metropolis sampler.

Contains the current configuration, the RNG state and the (optional) state of the transition rule.

Inheritance

Attributes

acceptance

The fraction of accepted moves across all chains.

The rate is computed since the last reset of the sampler. Will return None if no sampling has been performed since then.

n_accepted

Total number of moves accepted across all processes since the last reset.

n_steps

Total number of moves performed across all processes since the last reset.

σ: Array

Current batch of configurations in the Markov chain.

log_prob: Array

Log probabilities of the current batch of configurations σ in the Markov chain.

rng: Array

State of the random number generator (key, in jax terms).

rule_state: Any | None

Optional state of the transition rule.

n_steps_proc: int

Number of moves performed along the chains in this process since the last reset.

n_accepted_proc: Array

Number of accepted transitions among the chains in this process since the last reset.

Methods

replace(**kwargs)

Replace the values of the fields of the object with the values of the keyword arguments. If the object is a dataclass, dataclasses.replace will be used. Otherwise, a new object will be created with the same type as the original object.

Return type:

TypeVar(P, bound= Pytree)

Parameters:

• self (P)

• kwargs (Any)