Struct Gaussian2D 

pub struct Gaussian2D;

Axis-aligned 2-D Gaussian peak.

Formula (no rotation):

f(x, y) = A · exp( −(x − cₓ)² / (2·σₓ²) − (y − c_y)² / (2·σ_y²) )

Parameters (in order): [amplitude, center_x, center_y, sigma_x, sigma_y]

• amplitude — peak value at (center_x, center_y) (not area).
• center_x, center_y — peak location.
• sigma_x, sigma_y — standard deviations along each axis (FWHM ≈ 2.355·σ).

MVP note: a theta rotation parameter is intentionally omitted to keep the first 2-D kernel minimal; rotated Gaussians are a follow-up unit.

Trait Implementations

impl Model for Gaussian2D

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

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

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

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

fn n_dims(&self) -> usize

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

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].