Struct SplitPearson7 

pub struct SplitPearson7;

Split Pearson VII: a Pearson VII with a different width AND exponent on each side.

f(x) = A / [1 + ((x − c)/σ_i)²·(2^{1/m_i} − 1)]^{m_i}, with (σ_i, m_i) = (σ_L, m_L) for x < c, else (σ_R, m_R).

Parameters (in order): [amplitude, center, sigma_l, sigma_r, m_l, m_r]. amplitude is the peak height at x == center (continuous: both branches give A there). numpy oracle identical via np.where(x < c, left, right).

Trait Implementations

impl Model for SplitPearson7

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.