Struct lattice_qcd_rs::simulation::monte_carlo::metropolis_hastings::MetropolisHastings

pub struct MetropolisHastings { /* private fields */ }

Metropolis Hastings algorithm. Very slow, use MetropolisHastingsDeltaDiagnostic instead when applicable.

This a very general method that can manage every LatticeState but the tread off is that it is much slower than a dedicated algorithm knowing the from of the hamiltonian. If you want to use your own hamiltonian I advice to implement you own method too.

Note that this method does not do a sweep but change random link matrix, for a sweep there is super::MetropolisHastingsSweep.

Example

See the example of super::McWrapper

Implementations

impl MetropolisHastings

pub fn new(number_of_update: usize, spread: Real) -> Option<Self>

spread should be between 0 and 1 both not included and number_of_update should be greater than 0. 0.1_f64 is a good choice for this parameter.

number_of_update is the number of times a link matrix is randomly changed. spread is the spread factor for the random matrix change ( used in su3::random_su3_close_to_unity).

pub const fn number_of_update(&self) -> usize

Get the number of attempted updates per steps.

pub const fn spread(&self) -> Real

Get the spread parameter.

Trait Implementations

impl Clone for MetropolisHastings

fn clone(&self) -> MetropolisHastings

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MetropolisHastings

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for MetropolisHastings

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for MetropolisHastings

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Display for MetropolisHastings

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<State, const D: usize> MonteCarloDefault<State, D> for MetropolisHastingswhere State: LatticeState<D> + LatticeStateNew<D>,

type Error = <State as LatticeStateNew<D>>::Error

Error returned while getting the next element.

fn potential_next_element<Rng>( &mut self, state: &State, rng: &mut Rng ) -> Result<State, Self::Error>where Rng: Rng + ?Sized,

Generate a radom element from the previous element (like a Markov chain).

fn probability_of_replacement(old_state: &State, new_state: &State) -> Real

probability of the next element to replace the current one.

fn next_element_default<Rng>( &mut self, state: State, rng: &mut Rng ) -> Result<State, Self::Error>where Rng: Rng + ?Sized,

Get the next element in the chain either the old state or a new one replacing it.

impl PartialEq<MetropolisHastings> for MetropolisHastings

fn eq(&self, other: &MetropolisHastings) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for MetropolisHastings

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>where __S: Serializer,

Serialize this value into the given Serde serializer.

impl Copy for MetropolisHastings

impl StructuralPartialEq for MetropolisHastings