rgpycrumbs.surfaces.gradient_se

Classes

GradientSE

Gradient-enhanced Squared Exponential (SE) surface implementation.

Functions

negative_mll_se_grad(log_params, x, y_flat, D_plus_1)
_grad_se_solve(x, y_full, noise_scalar, length_scale)
_grad_se_predict(x_query, x_obs, alpha, length_scale)
_grad_se_var(x_query, x_obs, K_inv, length_scale)

Module Contents

rgpycrumbs.surfaces.gradient_se.negative_mll_se_grad(log_params, x, y_flat, D_plus_1)

rgpycrumbs.surfaces.gradient_se._grad_se_solve(x, y_full, noise_scalar, length_scale)

rgpycrumbs.surfaces.gradient_se._grad_se_predict(x_query, x_obs, alpha, length_scale)

rgpycrumbs.surfaces.gradient_se._grad_se_var(x_query, x_obs, K_inv, length_scale)

class rgpycrumbs.surfaces.gradient_se.GradientSE(x, y, gradients=None, smoothing=0.0001, length_scale=None, optimize=True, **_kwargs)

Bases: rgpycrumbs.surfaces._base.BaseGradientSurface

Gradient-enhanced Squared Exponential (SE) surface implementation.

Added in version 1.0.0.

_fit(smoothing, length_scale, optimize)

Internal method to perform parameter optimization.

_solve()

Internal method to solve the linear system for weights.

_predict_chunk(chunk)

Internal method for batch prediction.

_var_chunk(chunk)

Internal method for batch variance.