Struct MaternKernel 

pub struct MaternKernel {
    pub variant: MaternVariant,
    pub length_scale: f64,
    pub signal_variance: f64,
}

Matern kernel with selectable smoothness parameter nu.

• nu = 1/2: k = sigma^2 * exp(-r / l) (once-differentiable)
• nu = 3/2: k = sigma^2 * (1 + sqrt(3)*r/l) * exp(-sqrt(3)*r/l)
• nu = 5/2: k = sigma^2 * (1 + sqrt(5)r/l + 5r^2/(3*l^2)) * exp(-sqrt(5)*r/l)

Fields

variant: MaternVariant

Smoothness parameter

length_scale: f64

Length scale

signal_variance: f64

Signal variance

Implementations

impl MaternKernel

pub fn new( variant: MaternVariant, length_scale: f64, signal_variance: f64, ) -> Self

pub fn one_half(length_scale: f64, signal_variance: f64) -> Self

Create a Matern-1/2 kernel.

pub fn three_halves(length_scale: f64, signal_variance: f64) -> Self

Create a Matern-3/2 kernel.

pub fn five_halves(length_scale: f64, signal_variance: f64) -> Self

Create a Matern-5/2 kernel.

Trait Implementations

impl Clone for MaternKernel

fn clone(&self) -> MaternKernel

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for MaternKernel

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for MaternKernel

fn default() -> Self

Returns the “default value” for a type.

impl SurrogateKernel for MaternKernel

fn eval(&self, x1: &ArrayView1<'_, f64>, x2: &ArrayView1<'_, f64>) -> f64

Evaluate the kernel between two input vectors.

fn get_log_params(&self) -> Vec<f64>

Return current hyperparameters as a flat vector (log-scale).

fn set_log_params(&mut self, params: &[f64])

Set hyperparameters from a flat vector (log-scale).

fn clone_box(&self) -> Box<dyn SurrogateKernel>

Clone the kernel into a boxed trait object.

fn name(&self) -> &str

Name of the kernel (for debug display).

fn covariance_matrix(&self, x: &Array2<f64>) -> Array2<f64>

Compute the full covariance matrix for a set of inputs.

fn cross_covariance(&self, x1: &Array2<f64>, x2: &Array2<f64>) -> Array2<f64>

Compute the cross-covariance matrix between two sets of inputs.

fn n_params(&self) -> usize

Number of hyperparameters.