Struct RbfKernel 

pub struct RbfKernel {
    pub length_scale: f64,
    pub signal_variance: f64,
}

Squared Exponential / RBF kernel.

k(x, x’) = sigma^2 * exp(-0.5 * ||x - x’||^2 / length_scale^2)

Fields

length_scale: f64

Length scale

signal_variance: f64

Signal variance

Implementations

impl RbfKernel

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

Create a new RBF kernel.

Trait Implementations

impl Clone for RbfKernel

fn clone(&self) -> RbfKernel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for RbfKernel

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

Formats the value using the given formatter.

impl Default for RbfKernel

fn default() -> Self

Returns the “default value” for a type.

impl SurrogateKernel for RbfKernel

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.