ScaleKernel

class baybe.kernels.composite.ScaleKernel

Bases: CompositeKernel

A kernel for decorating existing kernels with an outputscale.

Public methods

__init__(base_kernel[, outputscale_prior, ...])	Method generated by attrs for class ScaleKernel.
from_dict(dictionary)	Create an object from its dictionary representation.
from_json(source, /)	Create an object from its JSON representation.
to_dict()	Create an object's dictionary representation.
to_factory()	Wrap the kernel in a baybe.surrogates.gaussian_process.kernel_factory.PlainKernelFactory.
to_gpytorch(*args, **kwargs)	Create the gpytorch representation of the kernel.
to_json([sink, overwrite])	Create an object's JSON representation.

Public attributes and properties

base_kernel	The base kernel that is being decorated.
outputscale_prior	An optional prior on the output scale.
outputscale_initial_value	An optional initial value for the output scale.

__init__(base_kernel: Kernel, outputscale_prior: Prior | None = None, outputscale_initial_value=None)

Method generated by attrs for class ScaleKernel.

For details on the parameters, see Public attributes and properties.

classmethod from_dict(dictionary: dict)

Create an object from its dictionary representation.

Parameters:

dictionary (dict) – The dictionary representation.

Return type:

TypeVar(_T, bound= SerialMixin)

Returns:

The reconstructed object.

classmethod from_json(source: str | Path | SupportsRead[str], /)

Create an object from its JSON representation.

Parameters:

source (str | Path | SupportsRead[str]) –

The JSON source. Can be:

• A string containing JSON content.

• A file path or Path object pointing to a JSON file.

• A file-like object with a read() method.

Raises:

ValueError – If source is not one of the allowed types.

Return type:

_T

Returns:

The reconstructed object.

to_dict()

Create an object’s dictionary representation.

Return type:

dict

Returns:

The dictionary representation of the object.

to_factory()

Wrap the kernel in a baybe.surrogates.gaussian_process.kernel_factory.PlainKernelFactory.

Return type:

PlainKernelFactory

to_gpytorch(*args, **kwargs)

Create the gpytorch representation of the kernel.

to_json(sink: str | Path | SupportsWrite[str] | None = None, /, *, overwrite: bool = False, **kwargs: Any)

Create an object’s JSON representation.

Parameters:

• sink (str | Path | SupportsWrite[str] | None) –

  The JSON sink. Can be:

  • None (only returns the JSON string).

  • A file path or Path object pointing to a location where to write the JSON content.

  • A file-like object with a write() method.

• overwrite (bool) – Boolean flag indicating if to overwrite the file if it already exists. Only relevant if sink is a file path or Path object.

• **kwargs (Any) – Additional keyword arguments to pass to json.dumps().

Raises:

FileExistsError – If sink points to an already existing file but overwrite is False.

Return type:

str

Returns:

The JSON representation as a string.

base_kernel: Kernel

The base kernel that is being decorated.

outputscale_initial_value: float | None

An optional initial value for the output scale.

outputscale_prior: Prior | None

An optional prior on the output scale.