Type Alias FlowNutsSettings 

pub type FlowNutsSettings = NutsSettings<FlowSettings>;

Aliased Type

pub struct FlowNutsSettings {

    pub num_tune: u64,
    pub num_draws: u64,
    pub maxdepth: u64,
    pub mindepth: u64,
    pub store_gradient: bool,
    pub store_unconstrained: bool,
    pub store_transformed: bool,
    pub max_energy_error: f64,
    pub store_divergences: bool,
    pub adapt_options: FlowSettings,
    pub check_turning: bool,
    pub target_integration_time: Option<f64>,
    pub trajectory_kind: KineticEnergyKind,
    pub num_chains: usize,
    pub seed: u64,
    pub extra_doublings: u64,
}

Fields

num_tune: u64

The number of tuning steps, where we fit the step size and geometry.

num_draws: u64

The number of draws after tuning

maxdepth: u64

The maximum tree depth during sampling. The number of leapfrog steps is smaller than 2 ^ maxdepth.

mindepth: u64

The minimum tree depth during sampling. The number of leapfrog steps is larger than 2 ^ mindepth.

store_gradient: bool

Store the gradient in the SampleStats

store_unconstrained: bool

Store each unconstrained parameter vector in the sampler stats

store_transformed: bool

Store the transformed gradient and value in the sampler stats

max_energy_error: f64

If the energy error is larger than this threshold we treat the leapfrog step as a divergence.

store_divergences: bool

Store detailed information about each divergence in the sampler stats

adapt_options: FlowSettings

Settings for geometry adaptation.

check_turning: bool

target_integration_time: Option<f64>

trajectory_kind: KineticEnergyKind

Selects the kinetic-energy form and the corresponding integrator.

• KineticEnergyKind::Euclidean: standard leapfrog (default for most settings).
• KineticEnergyKind::ExactNormal: geodesic leapfrog exact for a standard-normal potential.
• KineticEnergyKind::Microcanonical: isokinetic ESH-dynamics leapfrog (microcanonical HMC); momentum is constrained to the unit sphere.

num_chains: usize

seed: u64

extra_doublings: u64

Number of extra doublings to perform after reaching maxdepth. This can be used to increase the effective sample size at the cost of more expensive sampling.

Trait Implementations

impl Default for FlowNutsSettings

fn default() -> Self

Returns the “default value” for a type.

impl Settings for FlowNutsSettings

type Chain<M: Math> = NutsChain<M, ChaCha8Rng, ExternalTransformAdaptation>

fn new_chain<M: Math, R: Rng + ?Sized>( &self, chain: u64, math: M, rng: &mut R, ) -> Self::Chain<M>

fn hint_num_tune(&self) -> usize

fn hint_num_draws(&self) -> usize

fn num_chains(&self) -> usize

fn seed(&self) -> u64

fn stats_options<M: Math>( &self, ) -> <Self::Chain<M> as SamplerStats<M>>::StatsOptions

fn sampler_name(&self) -> &'static str

fn adaptation_name(&self) -> &'static str

fn stat_names<M: Math>(&self, math: &M) -> Vec<String>

fn data_names<M: Math>(&self, math: &M) -> Vec<String>

fn stat_types<M: Math>(&self, math: &M) -> Vec<(String, ItemType)>

fn stat_type<M: Math>(&self, math: &M, name: &str) -> ItemType

fn data_types<M: Math>(&self, math: &M) -> Vec<(String, ItemType)>

fn data_type<M: Math>(&self, math: &M, name: &str) -> ItemType

fn stat_dims_all<M: Math>(&self, math: &M) -> Vec<(String, Vec<String>)>

fn stat_dims<M: Math>(&self, math: &M, name: &str) -> Vec<String>

fn stat_dim_sizes<M: Math>(&self, math: &M) -> HashMap<String, u64>

fn data_dims_all<M: Math>(&self, math: &M) -> Vec<(String, Vec<String>)>

fn data_dims<M: Math>(&self, math: &M, name: &str) -> Vec<String>

fn stat_coords<M: Math>(&self, math: &M) -> HashMap<String, Value>

fn stat_event_dims<M: Math>(&self, math: &M) -> Vec<(String, Option<String>)>