piglot.objectives.response_objective.ResponseComposition
- class ResponseComposition(objectives: List[ResponseSingleObjective], scalarisation: Scalarisation | None = None)[source]
Bases:
Composition,ABCGeneric class for compositions to use for response-based objectives.
Methods
Abstract method for computing the outer function of the composition
Compute the composition for all objectives.
Compute the latent space representation of the given results.
- composition(inner: ndarray, params: ndarray) ndarray
Abstract method for computing the outer function of the composition
Parameters
- innernp.ndarray
Return value from the inner function
- paramsnp.ndarray
Parameters for the given responses
Returns
- np.ndarray
Composition result
- abstract composition_torch(inner: Tensor, params: Tensor) Tensor[source]
Compute the composition for all objectives.
Parameters
- innertorch.Tensor
Return value from the inner function.
- paramstorch.Tensor
Paratemers for the given responses.
Returns
- torch.Tensor
Composition results.
- abstract get_latent_space(params: ndarray, raw_responses: Dict[str, OutputResult]) Tuple[ndarray, ndarray][source]
Compute the latent space representation of the given results.
Parameters
- paramsnp.ndarray
Parameter values for these results.
- raw_responsesDict[str, OutputResult]
Raw responses from the solver.
Returns
- Tuple[np.ndarray, np.ndarray]
Latent space representation of the results: mean and covariance.