Struct Kww 

pub struct Kww;

Kohlrausch–Williams–Watts (KWW) stretched exponential: A · exp(−(x/τ)^β).

Parameters (in order): [amplitude, tau, beta]

• amplitude (A) is the value at x == 0 (where (0/τ)^β = 0 ⇒ exp(0) = 1).
• tau (τ > 0) is the characteristic relaxation time.
• beta (0 < β ≤ 1) is the stretching exponent: β = 1 recovers a plain exponential, β < 1 gives a stretched (multi-timescale) relaxation.

Defined for x ≥ 0. For x < 0 the base x/τ is negative and a fractional β would yield a NaN, so the kernel returns 0.0 there. The numpy benchmark formula is identical — np.where(x >= 0, A·exp(−(x/τ)^β), 0) — so numpy↔Rust parity is exact.

Trait Implementations

impl Model for Kww

fn jacobian(&self, x: &[f64], params: &[f64]) -> Vec<f64>

Central finite-difference Jacobian. ∂/∂β involves ln(x/τ) which diverges as x → 0⁺, so a numerical Jacobian is used (matching log_normal).

fn eval(&self, x: &[f64], params: &[f64]) -> f64

Evaluate the model at coordinate x with the given params.

fn param_names(&self) -> Vec<Cow<'static, str>>

Ordered parameter names, matching the layout expected by eval and jacobian.

fn jacobian_into(&self, x: &[f64], params: &[f64], out: &mut [f64])

Fill a pre-allocated slice with Jacobian values (one entry per parameter).

fn eval_slice_into(&self, xs: &[f64], params: &[f64], out: &mut [f64])

Batch evaluation of a 1-D model: fill out[i] = eval([xs[i]], params).

fn jac_slice_into(&self, xs: &[f64], params: &[f64], out: &mut [f64])

Batch Jacobian for a 1-D model: fill out in row-major layout [i * params.len() + j] = d(model)/d(params[j]) at xs[i].

fn n_dims(&self) -> usize

Number of coordinate dimensions consumed from x. Defaults to 1.