Struct Pearson7 

pub struct Pearson7;

Pearson VII peak: A / [1 + ((x − c)/σ)² · (2^{1/m} − 1)]^m.

Parameters (in order): [amplitude, center, sigma, m]

• amplitude is the peak height attained at x == center.
• center is the peak location.
• sigma is the half-width at half-maximum (the 2^{1/m}−1 factor normalizes so σ is the HWHM for any shape exponent).
• m is the shape exponent: m → 1 gives a Lorentzian, m → ∞ a Gaussian.

The numpy benchmark oracle is identical — A / (1 + ((x−c)/σ)² · (2**(1/m) − 1))**m — so numpy↔Rust parity is exact.

Trait Implementations

impl Model for Pearson7

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

Central finite-difference Jacobian (the 2^{1/m} term makes the analytic m-derivative awkward, 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.