Documentation
Classes
Product

Product

The Product kernel takes two kernels \(k_1\) and \(k_2\) and combines them via

Python Reference (opens in a new tab)

Constructors

constructor()

Signature

new Product(opts?: object): Product;

Parameters

NameTypeDescription
opts?object-
opts.k1?anyThe first base-kernel of the product-kernel
opts.k2?anyThe second base-kernel of the product-kernel

Returns

Product

Defined in: generated/gaussian_process/kernels/Product.ts:21 (opens in a new tab)

Properties

_isDisposed

boolean = false

Defined in: generated/gaussian_process/kernels/Product.ts:19 (opens in a new tab)

_isInitialized

boolean = false

Defined in: generated/gaussian_process/kernels/Product.ts:18 (opens in a new tab)

_py

PythonBridge

Defined in: generated/gaussian_process/kernels/Product.ts:17 (opens in a new tab)

id

string

Defined in: generated/gaussian_process/kernels/Product.ts:14 (opens in a new tab)

opts

any

Defined in: generated/gaussian_process/kernels/Product.ts:15 (opens in a new tab)

Accessors

py

Signature

py(): PythonBridge;

Returns

PythonBridge

Defined in: generated/gaussian_process/kernels/Product.ts:36 (opens in a new tab)

Signature

py(pythonBridge: PythonBridge): void;

Parameters

NameType
pythonBridgePythonBridge

Returns

void

Defined in: generated/gaussian_process/kernels/Product.ts:40 (opens in a new tab)

Methods

__call__()

Return the kernel k(X, Y) and optionally its gradient.

Signature

__call__(opts: object): Promise<ArrayLike[]>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Left argument of the returned kernel k(X, Y)
opts.Y?ArrayLike[]Right argument of the returned kernel k(X, Y). If undefined, k(X, X) is evaluated instead.
opts.eval_gradient?booleanDetermines whether the gradient with respect to the log of the kernel hyperparameter is computed. Default Value false

Returns

Promise<ArrayLike[]>

Defined in: generated/gaussian_process/kernels/Product.ts:105 (opens in a new tab)

clone_with_theta()

Returns a clone of self with given hyperparameters theta.

Signature

clone_with_theta(opts: object): Promise<any>;

Parameters

NameTypeDescription
optsobject-
opts.theta?ArrayLikeThe hyperparameters

Returns

Promise<any>

Defined in: generated/gaussian_process/kernels/Product.ts:154 (opens in a new tab)

diag()

Returns the diagonal of the kernel k(X, X).

The result of this method is identical to np.diag(self(X)); however, it can be evaluated more efficiently since only the diagonal is evaluated.

Signature

diag(opts: object): Promise<ArrayLike>;

Parameters

NameTypeDescription
optsobject-
opts.X?ArrayLike[]Argument to the kernel.

Returns

Promise<ArrayLike>

Defined in: generated/gaussian_process/kernels/Product.ts:189 (opens in a new tab)

dispose()

Disposes of the underlying Python resources.

Once dispose() is called, the instance is no longer usable.

Signature

dispose(): Promise<void>;

Returns

Promise<void>

Defined in: generated/gaussian_process/kernels/Product.ts:88 (opens in a new tab)

init()

Initializes the underlying Python resources.

This instance is not usable until the Promise returned by init() resolves.

Signature

init(py: PythonBridge): Promise<void>;

Parameters

NameType
pyPythonBridge

Returns

Promise<void>

Defined in: generated/gaussian_process/kernels/Product.ts:49 (opens in a new tab)

is_stationary()

Returns whether the kernel is stationary.

Signature

is_stationary(opts: object): Promise<any>;

Parameters

NameType
optsobject

Returns

Promise<any>

Defined in: generated/gaussian_process/kernels/Product.ts:222 (opens in a new tab)