Struct egobox_moe::GpConstantSquaredExponentialSurrogate

pub struct GpConstantSquaredExponentialSurrogate(pub GaussianProcess<f64, ConstantMean, SquaredExponentialCorr>);

GP surrogate with Constant regression model and SquaredExponential correlation model.

See GaussianProcess

Tuple Fields

0: GaussianProcess<f64, ConstantMean, SquaredExponentialCorr>

Trait Implementations

impl Clone for GpConstantSquaredExponentialSurrogate

fn clone(&self) -> GpConstantSquaredExponentialSurrogate

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for GpConstantSquaredExponentialSurrogate

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

Formats the value using the given formatter.

impl Display for GpConstantSquaredExponentialSurrogate

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

Formats the value using the given formatter.

impl GpParameterized for GpConstantSquaredExponentialSurrogate

fn theta(&self) -> &Array1<f64>

fn variance(&self) -> f64

fn noise_variance(&self) -> f64

fn likelihood(&self) -> f64

impl GpSurrogate for GpConstantSquaredExponentialSurrogate

fn predict(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Predict output values at n points given as (n, xdim) matrix.

fn predict_var(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Predict variance values at n points given as (n, xdim) matrix.

fn predict_values(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

👎Deprecated since 0.17.0: renamed predict

Predict output values at n points given as (n, xdim) matrix.

impl GpSurrogateExt for GpConstantSquaredExponentialSurrogate

fn predict_gradients(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Predict derivatives at n points and return (n, xdim) matrix where each column is the partial derivatives wrt the ith component

fn predict_var_gradients(&self, x: &ArrayView2<'_, f64>) -> Result<Array2<f64>>

Predict derivatives of the variance at n points and return (n, xdim) matrix where each column is the partial derivatives wrt the ith component

fn sample(&self, x: &ArrayView2<'_, f64>, n_traj: usize) -> Result<Array2<f64>>

Sample trajectories

impl FullGpSurrogate for GpConstantSquaredExponentialSurrogate