csle_agents.agents.bayesian_optimization_emukit.bo.gp package

Submodules

csle_agents.agents.bayesian_optimization_emukit.bo.gp.gp_config module

class csle_agents.agents.bayesian_optimization_emukit.bo.gp.gp_config.GPConfig(kernel_config: csle_agents.agents.bayesian_optimization_emukit.bo.kernel.kernel_config.KernelConfig, obs_likelihood_variance: float = 1e-10)[source]

Bases: object

DTO class representing the configuration of a Gaussian Process (GP) based on GPy

create_gp(X: numpy.ndarray[Any, numpy.dtype[Any]], Y: numpy.ndarray[Any, numpy.dtype[Any]], input_dim: int) → emukit.model_wrappers.gpy_model_wrappers.GPyModelWrapper[source]

Creates the GP model

Parameters

  • X – the initial X values

  • Y – the initial Y values

  • input_dim – the dimension of the X-values

Returns

the GP model (wrapped in emukit object)

static from_dict(d: Dict[str, Any]) → csle_agents.agents.bayesian_optimization_emukit.bo.gp.gp_config.GPConfig[source]

Converts a dict representation to an instance

Parameters

d – the dict to convert

Returns

the created instance

static from_json_file(json_file_path: str) → csle_agents.agents.bayesian_optimization_emukit.bo.gp.gp_config.GPConfig[source]

Reads a json file and converts it to a DTO

Parameters

json_file_path – the json file path

Returns

the converted DTO

to_dict() → Dict[str, Any][source]

Gets a dict representation of the object

Returns

A dict representation of the object

Module contents