Struct PronyKernel 

pub struct PronyKernel<S: Scalar> {
    pub amplitudes: Vec<S>,
    pub rates: Vec<S>,
}

Prony series (Sum of Exponentials) kernel.

K(τ) = Σᵢ aᵢ * exp(-bᵢ * τ)

This is the most efficient kernel type for numerical integration because it can be computed recursively without storing full history.

Fields

amplitudes: Vec<S>

Amplitudes aᵢ

rates: Vec<S>

Decay rates bᵢ

Implementations

impl<S: Scalar> PronyKernel<S>

pub fn new(amplitudes: Vec<S>, rates: Vec<S>) -> Self

Create a new Prony series kernel.

Arguments

• amplitudes - Amplitudes aᵢ
• rates - Decay rates bᵢ (must be positive)

pub fn single(a: S, b: S) -> Self

Create a single exponential kernel.

pub fn two_term(a1: S, b1: S, a2: S, b2: S) -> Self

Create a two-term Prony series (generalized Maxwell model).

pub fn num_terms(&self) -> usize

Number of terms in the series.

Trait Implementations

impl<S: Clone + Scalar> Clone for PronyKernel<S>

fn clone(&self) -> PronyKernel<S>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<S: Debug + Scalar> Debug for PronyKernel<S>

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

Formats the value using the given formatter.

impl<S: Scalar> Kernel<S> for PronyKernel<S>

fn evaluate(&self, tau: S) -> S

Evaluate the kernel at time lag τ.

fn as_prony(&self) -> Option<(Vec<S>, Vec<S>)>

Check if the kernel is a sum of exponentials (Prony series).