Struct IntegratorSettings 

pub struct IntegratorSettings {

    pub n_bins: usize,
    pub bin_number_evolution: Option<Vec<usize>>,
    pub min_samples_for_update: usize,
    pub n_start: usize,
    pub n_increase: usize,
    pub n_max: usize,
    pub target_relative_accuracy: Option<f64>,
    pub target_absolute_accuracy: Option<f64>,
    pub integrated_phase: IntegratedPhase,
    pub discrete_dim_learning_rate: f64,
    pub continuous_dim_learning_rate: f64,
    pub train_on_avg: bool,
    pub show_max_wgt_info: bool,
    pub max_prob_ratio: f64,
    pub seed: u64,
    pub observables_output: ObservablesOutputSettings,
}

Fields

n_bins: usize

Number of bins maintained along each continuous integration dimension.

bin_number_evolution: Option<Vec<usize>>

Optional per-iteration bin counts, overriding the fixed n_bins value as training proceeds.

min_samples_for_update: usize

Minimum accumulated samples before an adaptive grid or discrete probability is updated.

n_start: usize

Number of samples in the first Monte Carlo iteration.

n_increase: usize

Samples added to each successive Monte Carlo iteration.

n_max: usize

Hard upper bound on the total number of integrand evaluations.

target_relative_accuracy: Option<f64>

Stop once the estimated relative uncertainty reaches this value, if configured.

target_absolute_accuracy: Option<f64>

Stop once the estimated absolute uncertainty reaches this value, if configured.

integrated_phase: IntegratedPhase

Complex component to integrate: real, imaginary, or both.

discrete_dim_learning_rate: f64

Update rate for learned probabilities over discrete sampling choices.

continuous_dim_learning_rate: f64

Update rate for adaptive grids over continuous integration dimensions.

train_on_avg: bool

Train adaptive distributions on iteration averages instead of individual sample weights.

show_max_wgt_info: bool

Include maximum-weight diagnostics in integration progress and result data.

max_prob_ratio: f64

Cap the ratio used when turning sampled weights into adaptive probabilities.

seed: u64

Seed for deterministic initialization of Monte Carlo random-number streams.

observables_output: ObservablesOutputSettings

File formats used when writing observable histograms and distributions.

Trait Implementations

impl Clone for IntegratorSettings

fn clone(&self) -> IntegratorSettings

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for IntegratorSettings

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

Formats the value using the given formatter.

impl<__Context> Decode<__Context> for IntegratorSettings

fn decode<D: Decoder<Context = __Context>>( decoder: &mut D, ) -> Result<Self, DecodeError>

Attempt to decode this type with the given Decode.

impl Default for IntegratorSettings

fn default() -> Self

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for IntegratorSettings

where IntegratorSettings: Default,

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Encode for IntegratorSettings

fn encode<__E: Encoder>(&self, encoder: &mut __E) -> Result<(), EncodeError>

Encode a given type.

impl JsonSchema for IntegratorSettings

fn schema_name() -> Cow<'static, str>

The name of the generated JSON Schema.

fn schema_id() -> Cow<'static, str>

Returns a string that uniquely identifies the schema produced by this type.

fn json_schema(generator: &mut SchemaGenerator) -> Schema

Generates a JSON Schema for this type.

fn inline_schema() -> bool

Whether JSON Schemas generated for this type should be included directly in parent schemas, rather than being re-used where possible using the $ref keyword.

impl PartialEq for IntegratorSettings

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl Serialize for IntegratorSettings

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for IntegratorSettings