Struct AsymIr 

pub struct AsymIr;

Asymmetric IR band: a Gaussian multiplied by a logistic sigmoid.

f(x) = A·exp(−(x − c)²/(2σ²)) · 1/(1 + exp(−k·(x − c))).

Parameters (in order): [amplitude, center, sigma, k]. amplitude is the Gaussian scale (peak ≈ A/2 at center because of the sigmoid); k is the asymmetry. The sigmoid exponent is clamped to ≤ 50 to avoid overflow — the numpy oracle clamps identically (np.clip(-k*(x-c), None, 50.0)), so numpy↔Rust parity is exact.

Trait Implementations

impl Model for AsymIr

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

Evaluate the model at coordinate x with the given params.

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

Jacobian — one derivative per parameter, in the same order as param_names().

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.